WorldWideScience

Sample records for adaptor proteins networks

  1. PAG - a multipurpose transmembrane adaptor protein

    Czech Academy of Sciences Publication Activity Database

    Hrdinka, Matouš; Hořejší, Václav

    2014-01-01

    Roč. 33, č. 41 (2014), s. 4881-4892 ISSN 0950-9232 R&D Projects: GA ČR(CZ) GBP302/12/G101 Institutional support: RVO:68378050 Keywords : PAG * adaptor protein * membrane raft Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 8.459, year: 2014

  2. Role of adaptor proteins in secretory granule biogenesis and maturation

    Directory of Open Access Journals (Sweden)

    Mathilde L Bonnemaison

    2013-08-01

    Full Text Available In the regulated secretory pathway, secretory granules (SGs store peptide hormones that are released on demand. SGs are formed at the trans-Golgi network (TGN and must undergo a maturation process to become responsive to secretagogues. The production of mature SGs requires concentrating newly synthesized soluble content proteins in granules whose membranes contain the appropriate integral membrane proteins. The mechanisms underlying the sorting of soluble and integral membrane proteins destined for SGs from other proteins are not yet well understood. For soluble proteins, luminal pH and divalent metals can affect aggregation and interaction with surrounding membranes. The trafficking of granule membrane proteins can be controlled by both luminal and cytosolic factors. Cytosolic adaptor proteins, which recognize the cytosolic domains of proteins that span the SG membrane, have been shown to play essential roles in the assembly of functional SGs. Adaptor protein 1A (AP-1A is known to interact with specific motifs in its cargo proteins and with the clathrin heavy chain, contributing to the formation of a clathrin coat. AP-1A is present in patches on immature SG membranes, where it removes cargo and facilitates SG maturation. AP-1A recruitment to membranes can be modulated by PACS-1 (Phosphofurin Acidic Cluster Sorting protein 1, a cytosolic protein which interacts with both AP-1A and cargo that has been phosphorylated by casein kinase II. A cargo/PACS-1/AP-1A complex is necessary to drive the appropriate transport of several cargo proteins within the regulated secretory pathway. The GGA (Golgi-localized, -ear containing, ADP-ribosylation factor binding family of adaptor proteins serve a similar role. We review the functions of AP-1A, PACS-1 and GGAs in facilitating the retrieval of proteins from immature SGs and review examples of cargo proteins whose trafficking within the regulated secretory pathway is governed by adaptor proteins.

  3. Palmitoylated transmembrane adaptor proteins in leukocyte signaling

    Czech Academy of Sciences Publication Activity Database

    Štěpánek, Ondřej; Dráber, Peter; Hořejší, Václav

    2014-01-01

    Roč. 26, č. 5 (2014), s. 895-902 ISSN 0898-6568 R&D Projects: GA ČR(CZ) GBP302/12/G101 Institutional support: RVO:68378050 Keywords : Leukocyte * Adaptor * Palmitoylation Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 4.315, year: 2014

  4. Glucose regulates clathrin adaptors at the trans-Golgi network and endosomes

    Science.gov (United States)

    Aoh, Quyen L.; Graves, Lee M.; Duncan, Mara C.

    2011-01-01

    Glucose is a rich source of energy and the raw material for biomass increase. Many eukaryotic cells remodel their physiology in the presence and absence of glucose. The yeast Saccharomyces cerevisiae undergoes changes in transcription, translation, metabolism, and cell polarity in response to glucose availability. Upon glucose starvation, translation initiation and cell polarity are immediately inhibited, and then gradually recover. In this paper, we provide evidence that, as in cell polarity and translation, traffic at the trans-Golgi network (TGN) and endosomes is regulated by glucose via an unknown mechanism that depends on protein kinase A (PKA). Upon glucose withdrawal, clathrin adaptors exhibit a biphasic change in localization: they initially delocalize from the membrane within minutes and later partially recover onto membranes. Additionally, the removal of glucose induces changes in posttranslational modifications of adaptors. Ras and Gpr1 signaling pathways, which converge on PKA, are required for changes in adaptor localization and changes in posttranslational modifications. Acute inhibition of PKA demonstrates that inhibition of PKA prior to glucose withdrawal prevents several adaptor responses to starvation. This study demonstrates that PKA activity prior to glucose starvation primes membrane traffic at the TGN and endosomes in response to glucose starvation. PMID:21832155

  5. Role of Crk Adaptor Proteins in Cellular Migration and Invasion in Human Breast Cancer

    National Research Council Canada - National Science Library

    Fathers, Kelly E

    2007-01-01

    The Crk adaptor proteins (CrkI, CrkII and CrkL) play an important role during cellular signalling by mediating the formation of protein-protein complexes and are involved in cellular migration, invasion, and adhesion...

  6. Role of Crk Adaptor Proteins in Cellular Migration and Invasion in Human Breast Cancer

    National Research Council Canada - National Science Library

    Fathers, Kelly E

    2008-01-01

    The Crk adaptor proteins (CrkI, CrkII and CrkL) play an important role during cellular signalling by mediating the formation of protein-protein complexes and are involved in cellular migration, invasion, and adhesion...

  7. Arabidopsis adaptor protein 1G is critical for pollen development.

    Science.gov (United States)

    Feng, Chong; Wang, Jia-Gang; Liu, Hai-Hong; Li, Sha; Zhang, Yan

    2017-09-01

    Pollen development is a pre-requisite for sexual reproduction of angiosperms, during which various cellular activities are involved. Pollen development accompanies dynamic remodeling of vacuoles through fission and fusion, disruption of which often compromises pollen viability. We previously reported that the Y subunit of adaptor protein 1 (AP1G) mediates synergid degeneration during pollen tube reception. Here, we demonstrate that AP1G is essential for pollen development. AP1G loss-of-function resulted in male gametophytic lethality due to defective pollen development. By ultrastructural analysis and fluorescence labeling, we demonstrate that AP1G loss-of-function compromised dynamic vacuolar remodeling during pollen development and impaired vacuolar acidification of pollen. Results presented here support a key role of vacuoles in gametophytic pollen development. © 2017 Institute of Botany, Chinese Academy of Sciences.

  8. DMPD: Structure, function and regulation of the Toll/IL-1 receptor adaptor proteins. [Dynamic Macrophage Pathway CSML Database

    Lifescience Database Archive (English)

    Full Text Available 17667936 Structure, function and regulation of the Toll/IL-1 receptor adaptor proteins... (.svg) (.html) (.csml) Show Structure, function and regulation of the Toll/IL-1 receptor adaptor proteins. ...PubmedID 17667936 Title Structure, function and regulation of the Toll/IL-1 receptor adaptor proteins

  9. Eps15: a multifunctional adaptor protein regulating intracellular trafficking

    Directory of Open Access Journals (Sweden)

    van Bergen en Henegouwen Paul MP

    2009-10-01

    Full Text Available Abstract Over expression of receptor tyrosine kinases is responsible for the development of a wide variety of malignancies. Termination of growth factor signaling is primarily determined by the down regulation of active growth factor/receptor complexes. In recent years, considerable insight has been gained in the endocytosis and degradation of growth factor receptors. A crucial player in this process is the EGFR Protein tyrosine kinase Substrate #15, or Eps15. This protein functions as a scaffolding adaptor protein and is involved both in secretion and endocytosis. Eps15 has been shown to bind to AP-1 and AP-2 complexes, to bind to inositol lipids and to several other proteins involved in the regulation of intracellular trafficking. In addition, Eps15 has been detected in the nucleus of mammalian cells. Activation of growth factor receptors induces tyrosine phosphorylation and mono-ubiquitination of Eps15. The role of these post translational modifications of Eps15 is still a mystery. It is proposed that Eps15 and its family members Eps15R and Eps15b are involved in the regulation of membrane morphology, which is required for intracellular vesicle formation and trafficking.

  10. SCIMP, a transmembrane adaptor protein involved in major histocompatibility complex class II signaling

    Czech Academy of Sciences Publication Activity Database

    Dráber, Peter; Vonková, Ivana; Štěpánek, Ondřej; Hrdinka, Matouš; Kucová, Markéta; Skopcová, Tereza; Otáhal, Pavel; Angelisová, Pavla; Hořejší, Václav; Yeung, M.; Weiss, A.; Brdička, Tomáš

    2011-01-01

    Roč. 31, č. 22 (2011), s. 4550-4562 ISSN 0270-7306 R&D Projects: GA MŠk 1M0506; GA ČR GEMEM/09/E011 Institutional research plan: CEZ:AV0Z50520514 Keywords : SCIMP * transmembrane adaptor protein * MHC II Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 5.527, year: 2011

  11. Deletion of the LIME adaptor protein minimally affects T and B cell development and function

    Czech Academy of Sciences Publication Activity Database

    Grégoire, C.; Šímová, Šárka; Wang, Y.; Sansoni, A.; Richelme, S.; Schmidr-Giese, A.; Simeoni, L.; Angelisová, Pavla; Reinhold, D.; Burkhart, S.; Hořejší, Václav; Malissen, B.; Malissen, M.

    2007-01-01

    Roč. 37, č. 11 (2007), s. 3259-3269 ISSN 0014-2980 R&D Projects: GA MŠk 1M0506 Institutional research plan: CEZ:AV0Z50520514 Keywords : LIME * adaptor protein * receptor Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 4.662, year: 2007

  12. Artificial Neural Network for the Prediction of Tyrosine-Based Sorting Signal Recognition by Adaptor Complexes

    Directory of Open Access Journals (Sweden)

    Debarati Mukherjee

    2012-01-01

    Full Text Available Sorting of transmembrane proteins to various intracellular compartments depends on specific signals present within their cytosolic domains. Among these sorting signals, the tyrosine-based motif (YXXØ is one of the best characterized and is recognized by μ-subunits of the four clathrin-associated adaptor complexes (AP-1 to AP-4. Despite their overlap in specificity, each μ-subunit has a distinct sequence preference dependent on the nature of the X-residues. Moreover, combinations of these residues exert cooperative or inhibitory effects towards interaction with the various APs. This complexity makes it impossible to predict a priori, the specificity of a given tyrosine-signal for a particular μ-subunit. Here, we describe the results obtained with a computational approach based on the Artificial Neural Network (ANN paradigm that addresses the issue of tyrosine-signal specificity, enabling the prediction of YXXØ-μ interactions with accuracies over 90%. Therefore, this approach constitutes a powerful tool to help predict mechanisms of intracellular protein sorting.

  13. Insight into Phosphatidylinositol-Dependent Membrane Localization of the Innate Immune Adaptor Protein Toll/Interleukin 1 Receptor Domain-Containing Adaptor Protein

    Science.gov (United States)

    Patra, Mahesh Chandra; Choi, Sangdun

    2018-01-01

    The toll/interleukin 1 receptor (TIR) domain-containing adaptor protein (TIRAP) plays an important role in the toll-like receptor (TLR) 2, TLR4, TLR7, and TLR9 signaling pathways. TIRAP anchors to phosphatidylinositol (PI) 4,5-bisphosphate (PIP2) on the plasma membrane and PI (3,4,5)-trisphosphate (PIP3) on the endosomal membrane and assists in recruitment of the myeloid differentiation primary response 88 protein to activated TLRs. To date, the structure and mechanism of TIRAP’s membrane association are only partially understood. Here, we modeled an all-residue TIRAP dimer using homology modeling, threading, and protein–protein docking strategies. Molecular dynamics simulations revealed that PIP2 creates a stable microdomain in a dipalmitoylphosphatidylcholine bilayer, providing TIRAP with its physiologically relevant orientation. Computed binding free energy values suggest that the affinity of PI-binding domain (PBD) for PIP2 is stronger than that of TIRAP as a whole for PIP2 and that the short PI-binding motif (PBM) contributes to the affinity between PBD and PIP2. Four PIP2 molecules can be accommodated by distinct lysine-rich surfaces on the dimeric PBM. Along with the known PI-binding residues (K15, K16, K31, and K32), additional positively charged residues (K34, K35, and R36) showed strong affinity toward PIP2. Lysine-to-alanine mutations at the PI-binding residues abolished TIRAP’s affinity for PIP2; however, K34, K35, and R36 consistently interacted with PIP2 headgroups through hydrogen bond (H-bond) and electrostatic interactions. TIRAP exhibited a PIP2-analogous intermolecular contact and binding affinity toward PIP3, aided by an H-bond network involving K34, K35, and R36. The present study extends our understanding of TIRAP’s membrane association, which could be helpful in designing peptide decoys to block TLR2-, TLR4-, TLR7-, and TLR9-mediated autoimmune diseases. PMID:29434596

  14. Insight into Phosphatidylinositol-Dependent Membrane Localization of the Innate Immune Adaptor Protein Toll/Interleukin 1 Receptor Domain-Containing Adaptor Protein

    Directory of Open Access Journals (Sweden)

    Mahesh Chandra Patra

    2018-01-01

    Full Text Available The toll/interleukin 1 receptor (TIR domain-containing adaptor protein (TIRAP plays an important role in the toll-like receptor (TLR 2, TLR4, TLR7, and TLR9 signaling pathways. TIRAP anchors to phosphatidylinositol (PI 4,5-bisphosphate (PIP2 on the plasma membrane and PI (3,4,5-trisphosphate (PIP3 on the endosomal membrane and assists in recruitment of the myeloid differentiation primary response 88 protein to activated TLRs. To date, the structure and mechanism of TIRAP’s membrane association are only partially understood. Here, we modeled an all-residue TIRAP dimer using homology modeling, threading, and protein–protein docking strategies. Molecular dynamics simulations revealed that PIP2 creates a stable microdomain in a dipalmitoylphosphatidylcholine bilayer, providing TIRAP with its physiologically relevant orientation. Computed binding free energy values suggest that the affinity of PI-binding domain (PBD for PIP2 is stronger than that of TIRAP as a whole for PIP2 and that the short PI-binding motif (PBM contributes to the affinity between PBD and PIP2. Four PIP2 molecules can be accommodated by distinct lysine-rich surfaces on the dimeric PBM. Along with the known PI-binding residues (K15, K16, K31, and K32, additional positively charged residues (K34, K35, and R36 showed strong affinity toward PIP2. Lysine-to-alanine mutations at the PI-binding residues abolished TIRAP’s affinity for PIP2; however, K34, K35, and R36 consistently interacted with PIP2 headgroups through hydrogen bond (H-bond and electrostatic interactions. TIRAP exhibited a PIP2-analogous intermolecular contact and binding affinity toward PIP3, aided by an H-bond network involving K34, K35, and R36. The present study extends our understanding of TIRAP’s membrane association, which could be helpful in designing peptide decoys to block TLR2-, TLR4-, TLR7-, and TLR9-mediated autoimmune diseases.

  15. New Insights to Clathrin and Adaptor Protein 2 for the Design and Development of Therapeutic Strategies

    Directory of Open Access Journals (Sweden)

    Ebbe Toftgaard Poulsen

    2015-12-01

    Full Text Available The Amyloid Precursor Protein (APP has been extensively studied for its role as the precursor of the β-amyloid protein (Aβ in Alzheimer’s disease (AD. However, our understanding of the normal function of APP is still patchy. Emerging evidence indicates that a dysfunction in APP trafficking and degradation can be responsible for neuronal deficits and progressive degeneration in humans. We recently reported that the Y682 mutation in the 682YENPTY687 domain of APP affects its binding to specific adaptor proteins and leads to its anomalous trafficking, to defects in the autophagy machinery and to neuronal degeneration. In order to identify adaptors that influence APP function, we performed pull-down experiments followed by quantitative mass spectrometry (MS on hippocampal tissue extracts of three month-old mice incubated with either the 682YENPTY687 peptide, its mutated form, 682GENPTY687 or its phosphorylated form, 682pYENPTY687. Our experiments resulted in the identification of two proteins involved in APP internalization and trafficking: Clathrin heavy chain (hc and its Adaptor Protein 2 (AP-2. Overall our results consolidate and refine the importance of Y682 in APP normal functions from an animal model of premature aging and dementia. Additionally, they open the perspective to consider Clathrin hc and AP-2 as potential targets for the design and development of new therapeutic strategies.

  16. The Lnk adaptor protein: a key regulator of normal and pathological hematopoiesis.

    Science.gov (United States)

    Velazquez, Laura

    2012-12-01

    The development and function of blood cells are regulated by specific growth factors/cytokines and their receptors' signaling pathways. In this way, these factors influence cell survival, proliferation and differentiation of hematopoietic cells. Central to this positive and/or negative control are the adaptor proteins. Since their identification 10 years ago, members of the Lnk adaptor protein family have proved to be important activators and/or inhibitors in the hematopoietic, immune and vascular system. In particular, the generation of animal and cellular models for the Lnk and APS proteins has helped establish the physiological role of these molecules through the identification of their specific signaling pathways and the characterization of their binding partners. Moreover, the recent identification of mutations in the LNK gene in myeloproliferative disorders, as well as the correlation of a single nucleotide polymorphism on LNK with hematological, immune and vascular diseases have suggested its involvement in the pathophysiology of these malignancies. The latter findings have thus raised the possibility of addressing Lnk signaling for the treatment of certain human diseases. This review therefore describes the pathophysiological role of this adaptor protein in hematological malignancies and the potential benefits of Lnk therapeutic targeting.

  17. SR proteins are NXF1 adaptors that link alternative RNA processing to mRNA export.

    Science.gov (United States)

    Müller-McNicoll, Michaela; Botti, Valentina; de Jesus Domingues, Antonio M; Brandl, Holger; Schwich, Oliver D; Steiner, Michaela C; Curk, Tomaz; Poser, Ina; Zarnack, Kathi; Neugebauer, Karla M

    2016-03-01

    Nuclear export factor 1 (NXF1) exports mRNA to the cytoplasm after recruitment to mRNA by specific adaptor proteins. How and why cells use numerous different export adaptors is poorly understood. Here we critically evaluate members of the SR protein family (SRSF1-7) for their potential to act as NXF1 adaptors that couple pre-mRNA processing to mRNA export. Consistent with this proposal, >1000 endogenous mRNAs required individual SR proteins for nuclear export in vivo. To address the mechanism, transcriptome-wide RNA-binding profiles of NXF1 and SRSF1-7 were determined in parallel by individual-nucleotide-resolution UV cross-linking and immunoprecipitation (iCLIP). Quantitative comparisons of RNA-binding sites showed that NXF1 and SR proteins bind mRNA targets at adjacent sites, indicative of cobinding. SRSF3 emerged as the most potent NXF1 adaptor, conferring sequence specificity to RNA binding by NXF1 in last exons. Interestingly, SRSF3 and SRSF7 were shown to bind different sites in last exons and regulate 3' untranslated region length in an opposing manner. Both SRSF3 and SRSF7 promoted NXF1 recruitment to mRNA. Thus, SRSF3 and SRSF7 couple alternative splicing and polyadenylation to NXF1-mediated mRNA export, thereby controlling the cytoplasmic abundance of transcripts with alternative 3' ends. © 2016 Müller-McNicoll et al.; Published by Cold Spring Harbor Laboratory Press.

  18. Role of adaptor proteins in motor regulation and membrane transport

    NARCIS (Netherlands)

    M.A. Schlager (Max)

    2010-01-01

    markdownabstract__Abstract__ Active transport along the cytoskeleton is a process essential for proper cellular function. Although much is known about the motor proteins that generate the necessary force and the cytoskeleton that provides the cellular infrastructure, many questions still

  19. The A/ENTH Domain-Containing Protein AtECA4 Is an Adaptor Protein Involved in Cargo Recycling from the trans-Golgi Network/Early Endosome to the Plasma Membrane.

    Science.gov (United States)

    Nguyen, Hong Hanh; Lee, Myoung Hui; Song, Kyungyoung; Ahn, Gyeongik; Lee, Jihyeong; Hwang, Inhwan

    2018-01-06

    Endocytosis and subsequent trafficking pathways are crucial for regulating the activity of plasma membrane-localized proteins. Depending on cellular and physiological conditions, the internalized cargoes are sorted at (and transported from) the trans-Golgi network/early endosome (TGN/EE) to the vacuole for degradation or recycled back to the plasma membrane. How this occurs at the molecular level remains largely elusive. Here, we provide evidence that the ENTH domain-containing protein AtECA4 plays a crucial role in recycling cargoes from the TGN/EE to the plasma membrane in Arabidopsis thaliana. AtECA4:sGFP primarily localized to the TGN/EE and plasma membrane (at low levels). Upon NaCl or mannitol treatment, AtECA4:sGFP accumulated at the TGN/EE at an early time point but was released from the TGN/EE to the cytosol at later time points. The ateca4 mutant showed higher resistance to osmotic stress and more sensitive to exogenous abscisic acid (ABA) than the wild type, as well as increased expression of ABA-inducible genes RD29A and RD29B. Consistently, ABCG25, a plasma membrane-localized ABA exporter, accumulated at the prevacuolar compartment in ateca4, indicating a defect in recycling to the plasma membrane. However, the role of AtECA4 in cargo recycling is not specific to ABCG25, as it also functions in the recycling of BRI1. These results suggest that AtECA4 plays a crucial role in the recycling of endocytosed cargoes from the TGN/EE to the plasma membrane. Copyright © 2018 The Author. Published by Elsevier Inc. All rights reserved.

  20. Targeting 14-3-3 adaptor protein-protein interactions to stimulate central nervous system repair

    Directory of Open Access Journals (Sweden)

    Andrew Kaplan

    2017-01-01

    Full Text Available The goal of developing treatments for central nervous system (CNS injuries is becoming more attainable with the recent identification of various drugs that can repair damaged axons. These discoveries have stemmed from screening efforts, large expression datasets and an improved understanding of the cellular and molecular biology underlying axon growth. It will be important to continue searching for new compounds that can induce axon repair. Here we describe how a family of adaptor proteins called 14-3-3s can be targeted using small molecule drugs to enhance axon outgrowth and regeneration. 14-3-3s bind to many functionally diverse client proteins to regulate their functions. We highlight the recent discovery of the axon-growth promoting activity of fusicoccin-A, a fungus-derived small molecule that stabilizes 14-3-3 interactions with their client proteins. Here we discuss how fusicoccin-A could serve as a starting point for the development of drugs to induce CNS repair.

  1. Nrf2 reduces levels of phosphorylated tau protein by inducing autophagy adaptor protein NDP52

    Science.gov (United States)

    Jo, Chulman; Gundemir, Soner; Pritchard, Susanne; Jin, Youngnam N.; Rahman, Irfan; Johnson, Gail V. W.

    2014-03-01

    Nuclear factor erythroid 2-related factor 2 (Nrf2) is a pivotal transcription factor in the defence against oxidative stress. Here we provide evidence that activation of the Nrf2 pathway reduces the levels of phosphorylated tau by induction of an autophagy adaptor protein NDP52 (also known as CALCOCO2) in neurons. The expression of NDP52, which we show has three antioxidant response elements (AREs) in its promoter region, is strongly induced by Nrf2, and its overexpression facilitates clearance of phosphorylated tau in the presence of an autophagy stimulator. In Nrf2-knockout mice, phosphorylated and sarkosyl-insoluble tau accumulates in the brains concurrent with decreased levels of NDP52. Moreover, NDP52 associates with phosphorylated tau from brain cortical samples of Alzheimer disease cases, and the amount of phosphorylated tau in sarkosyl-insoluble fractions is inversely proportional to that of NDP52. These results suggest that NDP52 plays a key role in autophagy-mediated degradation of phosphorylated tau in vivo.

  2. The Cytoplasmic Adaptor Protein Dok7 Activates the Receptor Tyrosine Kinase MuSK via Dimerization

    Energy Technology Data Exchange (ETDEWEB)

    Bergamin, E.; Hallock, P; Burden, S; Hubbard, S

    2010-01-01

    Formation of the vertebrate neuromuscular junction requires, among others proteins, Agrin, a neuronally derived ligand, and the following muscle proteins: LRP4, the receptor for Agrin; MuSK, a receptor tyrosine kinase (RTK); and Dok7 (or Dok-7), a cytoplasmic adaptor protein. Dok7 comprises a pleckstrin-homology (PH) domain, a phosphotyrosine-binding (PTB) domain, and C-terminal sites of tyrosine phosphorylation. Unique among adaptor proteins recruited to RTKs, Dok7 is not only a substrate of MuSK, but also an activator of MuSK's kinase activity. Here, we present the crystal structure of the Dok7 PH-PTB domains in complex with a phosphopeptide representing the Dok7-binding site on MuSK. The structure and biochemical data reveal a dimeric arrangement of Dok7 PH-PTB that facilitates trans-autophosphorylation of the kinase activation loop. The structure provides the molecular basis for MuSK activation by Dok7 and for rationalizing several Dok7 loss-of-function mutations found in patients with congenital myasthenic syndromes.

  3. The role of small adaptor proteins in the control of oncogenic signaling driven by tyrosine kinases in human cancer

    Science.gov (United States)

    Naudin, Cécile; Chevalier, Clément; Roche, Serge

    2016-01-01

    Protein phosphorylation on tyrosine (Tyr) residues has evolved as an important mechanism to coordinate cell communication in multicellular organisms. The importance of this process has been revealed by the discovery of the prominent oncogenic properties of tyrosine kinases (TK) upon deregulation of their physiological activities, often due to protein overexpression and/or somatic mutation. Recent reports suggest that TK oncogenic signaling is also under the control of small adaptor proteins. These cytosolic proteins lack intrinsic catalytic activity and signal by linking two functional members of a catalytic pathway. While most adaptors display positive regulatory functions, a small group of this family exerts negative regulatory functions by targeting several components of the TK signaling cascade. Here, we review how these less studied adaptor proteins negatively control TK activities and how their loss of function induces abnormal TK signaling, promoting tumor formation. We also discuss the therapeutic consequences of this novel regulatory mechanism in human oncology. PMID:26788993

  4. The role of small adaptor proteins in the control of oncogenic signalingr driven by tyrosine kinases in human cancer.

    Science.gov (United States)

    Naudin, Cécile; Chevalier, Clément; Roche, Serge

    2016-03-08

    Protein phosphorylation on tyrosine (Tyr) residues has evolved as an important mechanism to coordinate cell communication in multicellular organisms. The importance of this process has been revealed by the discovery of the prominent oncogenic properties of tyrosine kinases (TK) upon deregulation of their physiological activities, often due to protein overexpression and/or somatic mutation. Recent reports suggest that TK oncogenic signaling is also under the control of small adaptor proteins. These cytosolic proteins lack intrinsic catalytic activity and signal by linking two functional members of a catalytic pathway. While most adaptors display positive regulatory functions, a small group of this family exerts negative regulatory functions by targeting several components of the TK signaling cascade. Here, we review how these less studied adaptor proteins negatively control TK activities and how their loss of function induces abnormal TK signaling, promoting tumor formation. We also discuss the therapeutic consequences of this novel regulatory mechanism in human oncology.

  5. The Role of Crk Adaptor Proteins in Breast Tumorigenesis and Bone Metastasis

    Science.gov (United States)

    2012-09-01

    points indicated. Treatments included DMSO control or inhibition of Met (0.2uM PHA-665752), Abl (4uM Imatinib ), PI3K (20uM LY-294002), mTOR (0.1uM...CrkL over CrkII, Nat Chem Biol 8, 590–596 (2012). RESEARCH ARTICLE Open Access Crk adaptor proteins act as key signaling integrators for breast...R74 http://breast-cancer-research.com/content/14/3/R74 © 2012 Fathers et al.; licensee BioMed Central Ltd. This is an open access article distributed

  6. Transmembrane adaptor proteins in the high-affinity IgE receptor signaling

    Czech Academy of Sciences Publication Activity Database

    Dráber, Petr; Hálová, Ivana; Levi-Schaffer, F.; Dráberová, Lubica

    2012-01-01

    Roč. 2, 11.1. (2012), s. 95 ISSN 1664-3224 R&D Projects: GA MŠk 1M0506; GA ČR GA301/09/1826; GA ČR GAP302/10/1759; GA AV ČR KAN200520701 Grant - others:AV ČR(CZ) M200520901 Institutional research plan: CEZ:AV0Z50520514 Institutional support: RVO:68378050 Keywords : IgE receptor * LAT/LAT1 * LAX * NTAL/Lab/LAT2 * PAG/Cbp * mast cells * plasma membrane * transmembrane adaptor proteins Subject RIV: EB - Genetics ; Molecular Biology

  7. Association of autoimmune hepatitis with Src homology 2 adaptor protein 3 gene polymorphisms in Japanese patients.

    Science.gov (United States)

    Umemura, Takeji; Joshita, Satoru; Hamano, Hideaki; Yoshizawa, Kaname; Kawa, Shigeyuki; Tanaka, Eiji; Ota, Masao

    2017-11-01

    Autoimmune hepatitis (AIH) is a chronic inflammatory liver disease characterized by an autoimmune reaction to hepatocytes. The Src homology 2 adaptor protein 3 (SH2B3) gene is a member of the SH2B family of adaptor proteins that has been implicated in the integration and regulation of multiple signaling events. SH2B3 is involved in cytokine signaling pathways and serves as a negative mediator of T-cell receptor signaling. Genome-wide association analyses in Caucasians have linked a missense mutation at rs3184504 in SH2B3 with AIH. Accordingly, four selected single-nucleotide polymorphisms (SNPs) in the SH2B3 gene were genotyped in 158 patients with AIH, 327 patients with primary biliary cholangitis, 160 patients with autoimmune pancreatitis, and 325 healthy subjects of Japanese descent. Although the functional rs3184504 was non-polymorphic in 952 subjects, the frequency of the minor rs11065904 T allele was significantly decreased in AIH patients compared with healthy controls (odds ratio (OR)=0.68; corrected P=0.025). Haplotype 2 (rs2238154 A, rs11065904 T and rs739496 G) was associated with resistance to AIH (OR 0.67, P=0.021) as well as to autoimmune pancreatitis (OR=0.70, P=0.035). Our findings suggest that an SNP and haplotype in SH2B3 are associated with AIH.

  8. The Adaptor Protein Rai/ShcC Promotes Astrocyte-Dependent Inflammation during Experimental Autoimmune Encephalomyelitis.

    Science.gov (United States)

    Ulivieri, Cristina; Savino, Maria Teresa; Luccarini, Ilaria; Fanigliulo, Emanuela; Aldinucci, Alessandra; Bonechi, Elena; Benagiano, Marisa; Ortensi, Barbara; Pelicci, Giuliana; D'Elios, Mario Milco; Ballerini, Clara; Baldari, Cosima Tatiana

    2016-07-15

    Th17 cells have been casually associated to the pathogenesis of autoimmune disease. We have previously demonstrated that Rai/ShcC, a member of the Shc family of adaptor proteins, negatively regulates Th17 cell differentiation and lupus autoimmunity. In this study, we have investigated the pathogenic outcome of the Th17 bias associated with Rai deficiency on multiple sclerosis development, using the experimental autoimmune encephalomyelitis (EAE) mouse model. We found that, unexpectedly, EAE was less severe in Rai(-/-) mice compared with their wild-type counterparts despite an enhanced generation of myelin-specific Th17 cells that infiltrated into the CNS. Nevertheless, when adoptively transferred into immunodeficient Rai(+/+) mice, these cells promoted a more severe disease compared with wild-type encephalitogenic Th17 cells. This paradoxical phenotype was caused by a dampened inflammatory response of astrocytes, which were found to express Rai, to IL-17. The results provide evidence that Rai plays opposite roles in Th17 cell differentiation and astrocyte activation, with the latter dominant over the former in EAE, highlighting this adaptor as a potential novel target for the therapy of multiple sclerosis. Copyright © 2016 by The American Association of Immunologists, Inc.

  9. Interactions between the Hepatitis C Virus Nonstructural 2 Protein and Host Adaptor Proteins 1 and 4 Orchestrate Virus Release.

    Science.gov (United States)

    Xiao, Fei; Wang, Stanley; Barouch-Bentov, Rina; Neveu, Gregory; Pu, Szuyuan; Beer, Melanie; Schor, Stanford; Kumar, Sathish; Nicolaescu, Vlad; Lindenbach, Brett D; Randall, Glenn; Einav, Shirit

    2018-03-13

    Hepatitis C virus (HCV) spreads via secreted cell-free particles or direct cell-to-cell transmission. Yet, virus-host determinants governing differential intracellular trafficking of cell-free- and cell-to-cell-transmitted virus remain unknown. The host adaptor proteins (APs) AP-1A, AP-1B, and AP-4 traffic in post-Golgi compartments, and the latter two are implicated in basolateral sorting. We reported that AP-1A mediates HCV trafficking during release, whereas the endocytic adaptor AP-2 mediates entry and assembly. We demonstrated that the host kinases AAK1 and GAK regulate HCV infection by controlling these clathrin-associated APs. Here, we sought to define the roles of AP-4, a clathrin-independent adaptor; AP-1A; and AP-1B in HCV infection. We screened for interactions between HCV proteins and the μ subunits of AP-1A, AP-1B, and AP-4 by mammalian cell-based protein fragment complementation assays. The nonstructural 2 (NS2) protein emerged as an interactor of these adaptors in this screening and by coimmunoprecipitations in HCV-infected cells. Two previously unrecognized dileucine-based motifs in the NS2 C terminus mediated AP binding and HCV release. Infectivity and coculture assays demonstrated that while all three adaptors mediate HCV release and cell-free spread, AP-1B and AP-4, but not AP-1A, mediate cell-to-cell spread. Live-cell imaging revealed HCV cotrafficking with AP-1A, AP-1B, and AP-4 and that AP-4 mediates HCV trafficking in a post-Golgi compartment. Lastly, HCV cell-to-cell spread was regulated by AAK1 and GAK and thus susceptible to treatment with AAK1 and GAK inhibitors. These data provide a mechanistic understanding of HCV trafficking in distinct release pathways and reveal a requirement for APs in cell-to-cell viral spread. IMPORTANCE HCV spreads via cell-free infection or cell-to-cell contact that shields it from antibody neutralization, thereby facilitating viral persistence. Yet, factors governing this differential sorting remain unknown

  10. Alternatively spliced short and long isoforms of adaptor protein intersectin 1 form complexes in mammalian cells

    Directory of Open Access Journals (Sweden)

    Rynditch A. V.

    2012-12-01

    Full Text Available Intersectin 1 (ITSN1 is an adaptor protein involved in membrane trafficking and cell signaling. Long and short isoforms of ITSN1 (ITSN1-L and ITSN1-S are produced by alternative splicing. The aim of our study was to investigate whether ITSN1-L and ITSN1-S could interact in mammalian cells. Methods. During this study we employed immunoprecipitation and confocal microscopy. Results. We have shown that endogenous ITSN1-S co-precipitates with overexpressed ITSN1-L in PC12, 293 and 293T cells. Long and short isoforms of ITSN1 also co-localize in 293T cells. Conclusions. ITSN1-L and ITSN1-S form complexes in mammalian cells.

  11. Receptor tyrosine phosphatase R-PTP-alpha is tyrosine-phosphorylated and associated with the adaptor protein Grb2

    DEFF Research Database (Denmark)

    Su, J; Batzer, A; Sap, J

    1994-01-01

    Receptor tyrosine phosphatases (R-PTPases) have generated interest because of their suspected involvement in cellular signal transduction. The adaptor protein Grb2 has been implicated in coupling receptor tyrosine kinases to Ras. We report that a ubiquitous R-PTPase, R-PTP-alpha, is tyrosine-phos...

  12. Role of the AP-5 adaptor protein complex in late endosome-to-Golgi retrieval.

    Science.gov (United States)

    Hirst, Jennifer; Itzhak, Daniel N; Antrobus, Robin; Borner, Georg H H; Robinson, Margaret S

    2018-01-01

    The AP-5 adaptor protein complex is presumed to function in membrane traffic, but so far nothing is known about its pathway or its cargo. We have used CRISPR-Cas9 to knock out the AP-5 ζ subunit gene, AP5Z1, in HeLa cells, and then analysed the phenotype by subcellular fractionation profiling and quantitative mass spectrometry. The retromer complex had an altered steady-state distribution in the knockout cells, and several Golgi proteins, including GOLIM4 and GOLM1, were depleted from vesicle-enriched fractions. Immunolocalisation showed that loss of AP-5 led to impaired retrieval of the cation-independent mannose 6-phosphate receptor (CIMPR), GOLIM4, and GOLM1 from endosomes back to the Golgi region. Knocking down the retromer complex exacerbated this phenotype. Both the CIMPR and sortilin interacted with the AP-5-associated protein SPG15 in pull-down assays, and we propose that sortilin may act as a link between Golgi proteins and the AP-5/SPG11/SPG15 complex. Together, our findings suggest that AP-5 functions in a novel sorting step out of late endosomes, acting as a backup pathway for retromer. This provides a mechanistic explanation for why mutations in AP-5/SPG11/SPG15 cause cells to accumulate aberrant endolysosomes, and highlights the role of endosome/lysosome dysfunction in the pathology of hereditary spastic paraplegia and other neurodegenerative disorders.

  13. Role of the AP-5 adaptor protein complex in late endosome-to-Golgi retrieval.

    Directory of Open Access Journals (Sweden)

    Jennifer Hirst

    2018-01-01

    Full Text Available The AP-5 adaptor protein complex is presumed to function in membrane traffic, but so far nothing is known about its pathway or its cargo. We have used CRISPR-Cas9 to knock out the AP-5 ζ subunit gene, AP5Z1, in HeLa cells, and then analysed the phenotype by subcellular fractionation profiling and quantitative mass spectrometry. The retromer complex had an altered steady-state distribution in the knockout cells, and several Golgi proteins, including GOLIM4 and GOLM1, were depleted from vesicle-enriched fractions. Immunolocalisation showed that loss of AP-5 led to impaired retrieval of the cation-independent mannose 6-phosphate receptor (CIMPR, GOLIM4, and GOLM1 from endosomes back to the Golgi region. Knocking down the retromer complex exacerbated this phenotype. Both the CIMPR and sortilin interacted with the AP-5-associated protein SPG15 in pull-down assays, and we propose that sortilin may act as a link between Golgi proteins and the AP-5/SPG11/SPG15 complex. Together, our findings suggest that AP-5 functions in a novel sorting step out of late endosomes, acting as a backup pathway for retromer. This provides a mechanistic explanation for why mutations in AP-5/SPG11/SPG15 cause cells to accumulate aberrant endolysosomes, and highlights the role of endosome/lysosome dysfunction in the pathology of hereditary spastic paraplegia and other neurodegenerative disorders.

  14. Shc adaptor proteins are key transducers of mitogenic signaling mediated by the G protein-coupled thrombin receptor

    DEFF Research Database (Denmark)

    Chen, Y; Grall, D; Salcini, A E

    1996-01-01

    The serine protease thrombin activates G protein signaling systems that lead to Ras activation and, in certain cells, proliferation. Whereas the steps leading to Ras activation by G protein-coupled receptors are not well defined, the mechanisms of Ras activation by receptor tyrosine kinases have...... kinase activation, gene induction and cell growth. From these data, we conclude that Shc represents a crucial point of convergence between signaling pathways activated by receptor tyrosine kinases and G protein-coupled receptors....... recently been elucidated biochemically and genetically. The present study was undertaken to determine whether common signaling components are used by these two distinct classes of receptors. Here we report that the adaptor protein Shc, is phosphorylated on tyrosine residues following stimulation...

  15. Highly pathogenic avian influenza virus nucleoprotein interacts with TREX complex adaptor protein Aly/REF.

    Directory of Open Access Journals (Sweden)

    Vinod R M T Balasubramaniam

    Full Text Available We constructed a novel chicken (Gallus gallus lung cDNA library fused inside yeast acting domain vector (pGADT7. Using yeast two-hybrid screening with highly pathogenic avian influenza (HPAI nucleoprotein (NP from the strain (A/chicken/Malaysia/5858/2004(H5N1 as bait, and the Gallus gallus lung cDNA library as prey, a novel interaction between the Gallus gallus cellular RNA export adaptor protein Aly/REF and the viral NP was identified. This interaction was confirmed and validated with mammalian two hybrid studies and co-immunoprecipitation assay. Cellular localization studies using confocal microscopy showed that NP and Aly/REF co-localize primarily in the nucleus. Further investigations by mammalian two hybrid studies into the binding of NP of other subtypes of influenza virus such as the swine A/New Jersey/1976/H1N1 and pandemic A/Malaysia/854/2009(H1N1 to human Aly/REF, also showed that the NP of these viruses interacts with human Aly/REF. Our findings are also supported by docking studies which showed tight and favorable binding between H5N1 NP and human Aly/REF, using crystal structures from Protein Data Bank. siRNA knockdown of Aly/REF had little effect on the export of HPAI NP and other viral RNA as it showed no significant reduction in virus titer. However, UAP56, another component of the TREX complex, which recruits Aly/REF to mRNA was found to interact even better with H5N1 NP through molecular docking studies. Both these proteins also co-localizes in the nucleus at early infection similar to Aly/REF. Intriguingly, knockdown of UAP56 in A549 infected cells shows significant reduction in viral titer (close to 10 fold reduction. Conclusively, our study have opened new avenues for research of other cellular RNA export adaptors crucial in aiding viral RNA export such as the SRSF3, 9G8 and ASF/SF2 that may play role in influenza virus RNA nucleocytoplasmic transport.

  16. The adaptor protein Grb2 is not essential for the establishment of the glomerular filtration barrier.

    Directory of Open Access Journals (Sweden)

    Nicolas Bisson

    Full Text Available The kidney filtration barrier is formed by the combination of endothelial cells, basement membrane and epithelial cells called podocytes. These specialized actin-rich cells form long and dynamic protrusions, the foot processes, which surround glomerular capillaries and are connected by specialized intercellular junctions, the slit diaphragms. Failure to maintain the filtration barrier leads to massive proteinuria and nephrosis. A number of proteins reside in the slit diaphragm, notably the transmembrane proteins Nephrin and Neph1, which are both able to act as tyrosine phosphorylated scaffolds that recruit cytoplasmic effectors to initiate downstream signaling. While association between tyrosine-phosphorylated Neph1 and the SH2/SH3 adaptor Grb2 was shown in vitro to be sufficient to induce actin polymerization, in vivo evidence supporting this finding is still lacking. To test this hypothesis, we generated two independent mouse lines bearing a podocyte-specific constitutive inactivation of the Grb2 locus. Surprisingly, we show that mice lacking Grb2 in podocytes display normal renal ultra-structure and function, thus demonstrating that Grb2 is not required for the establishment of the glomerular filtration barrier in vivo. Moreover, our data indicate that Grb2 is not required to restore podocyte function following kidney injury. Therefore, although in vitro experiments suggested that Grb2 is important for the regulation of actin dynamics, our data clearly shows that its function is not essential in podocytes in vivo, thus suggesting that Grb2 rather plays a secondary role in this process.

  17. The adaptor protein MITA links virus-sensing receptors to IRF3 transcription factor activation.

    Science.gov (United States)

    Zhong, Bo; Yang, Yan; Li, Shu; Wang, Yan-Yi; Li, Ying; Diao, Feici; Lei, Caoqi; He, Xiao; Zhang, Lu; Tien, Po; Shu, Hong-Bing

    2008-10-17

    Viral infection triggers activation of transcription factors such as NF-kappaB and IRF3, which collaborate to induce type I interferons (IFNs) and elicit innate antiviral response. Here, we identified MITA as a critical mediator of virus-triggered type I IFN signaling by expression cloning. Overexpression of MITA activated IRF3, whereas knockdown of MITA inhibited virus-triggered activation of IRF3, expression of type I IFNs, and cellular antiviral response. MITA was found to localize to the outer membrane of mitochondria and to be associated with VISA, a mitochondrial protein that acts as an adaptor in virus-triggered signaling. MITA also interacted with IRF3 and recruited the kinase TBK1 to the VISA-associated complex. MITA was phosphorylated by TBK1, which is required for MITA-mediated activation of IRF3. Our results suggest that MITA is a critical mediator of virus-triggered IRF3 activation and IFN expression and further demonstrate the importance of certain mitochondrial proteins in innate antiviral immunity.

  18. Histone locus regulation by the Drosophila dosage compensation adaptor protein CLAMP.

    Science.gov (United States)

    Rieder, Leila E; Koreski, Kaitlin P; Boltz, Kara A; Kuzu, Guray; Urban, Jennifer A; Bowman, Sarah K; Zeidman, Anna; Jordan, William T; Tolstorukov, Michael Y; Marzluff, William F; Duronio, Robert J; Larschan, Erica N

    2017-07-15

    The conserved histone locus body (HLB) assembles prior to zygotic gene activation early during development and concentrates factors into a nuclear domain of coordinated histone gene regulation. Although HLBs form specifically at replication-dependent histone loci, the cis and trans factors that target HLB components to histone genes remained unknown. Here we report that conserved GA repeat cis elements within the bidirectional histone3-histone4 promoter direct HLB formation in Drosophila In addition, the CLAMP (chromatin-linked adaptor for male-specific lethal [MSL] proteins) zinc finger protein binds these GA repeat motifs, increases chromatin accessibility, enhances histone gene transcription, and promotes HLB formation. We demonstrated previously that CLAMP also promotes the formation of another domain of coordinated gene regulation: the dosage-compensated male X chromosome. Therefore, CLAMP binding to GA repeat motifs promotes the formation of two distinct domains of coordinated gene activation located at different places in the genome. © 2017 Rieder et al.; Published by Cold Spring Harbor Laboratory Press.

  19. Dengue Virus Targets the Adaptor Protein MITA to Subvert Host Innate Immunity

    Science.gov (United States)

    Yu, Chia-Yi; Chang, Tsung-Hsien; Liang, Jian-Jong; Chiang, Ruei-Lin; Lee, Yi-Ling; Liao, Ching-Len; Lin, Yi-Ling

    2012-01-01

    Dengue is one of the most important arboviral diseases caused by infection of four serotypes of dengue virus (DEN). We found that activation of interferon regulatory factor 3 (IRF3) triggered by viral infection and by foreign DNA and RNA stimulation was blocked by DEN-encoded NS2B3 through a protease-dependent mechanism. The key adaptor protein in type I interferon pathway, human mediator of IRF3 activation (MITA) but not the murine homologue MPYS, was cleaved in cells infected with DEN-1 or DEN-2 and with expression of the enzymatically active protease NS2B3. The cleavage site of MITA was mapped to LRR↓96G and the function of MITA was suppressed by dengue protease. DEN replication was reduced with overexpression of MPYS but not with MITA, while DEN replication was enhanced by MPYS knockdown, indicating an antiviral role of MITA/MPYS against DEN infection. The involvement of MITA in DEN-triggered innate immune response was evidenced by reduction of IRF3 activation and IFN induction in cells with MITA knockdown upon DEN-2 infection. NS2B3 physically interacted with MITA, and the interaction and cleavage of MITA could be further enhanced by poly(dA:dT) stimulation. Thus, we identified MITA as a novel host target of DEN protease and provide the molecular mechanism of how DEN subverts the host innate immunity. PMID:22761576

  20. Dengue virus targets the adaptor protein MITA to subvert host innate immunity.

    Science.gov (United States)

    Yu, Chia-Yi; Chang, Tsung-Hsien; Liang, Jian-Jong; Chiang, Ruei-Lin; Lee, Yi-Ling; Liao, Ching-Len; Lin, Yi-Ling

    2012-01-01

    Dengue is one of the most important arboviral diseases caused by infection of four serotypes of dengue virus (DEN). We found that activation of interferon regulatory factor 3 (IRF3) triggered by viral infection and by foreign DNA and RNA stimulation was blocked by DEN-encoded NS2B3 through a protease-dependent mechanism. The key adaptor protein in type I interferon pathway, human mediator of IRF3 activation (MITA) but not the murine homologue MPYS, was cleaved in cells infected with DEN-1 or DEN-2 and with expression of the enzymatically active protease NS2B3. The cleavage site of MITA was mapped to LRR↓(96)G and the function of MITA was suppressed by dengue protease. DEN replication was reduced with overexpression of MPYS but not with MITA, while DEN replication was enhanced by MPYS knockdown, indicating an antiviral role of MITA/MPYS against DEN infection. The involvement of MITA in DEN-triggered innate immune response was evidenced by reduction of IRF3 activation and IFN induction in cells with MITA knockdown upon DEN-2 infection. NS2B3 physically interacted with MITA, and the interaction and cleavage of MITA could be further enhanced by poly(dA:dT) stimulation. Thus, we identified MITA as a novel host target of DEN protease and provide the molecular mechanism of how DEN subverts the host innate immunity.

  1. Dengue virus targets the adaptor protein MITA to subvert host innate immunity.

    Directory of Open Access Journals (Sweden)

    Chia-Yi Yu

    Full Text Available Dengue is one of the most important arboviral diseases caused by infection of four serotypes of dengue virus (DEN. We found that activation of interferon regulatory factor 3 (IRF3 triggered by viral infection and by foreign DNA and RNA stimulation was blocked by DEN-encoded NS2B3 through a protease-dependent mechanism. The key adaptor protein in type I interferon pathway, human mediator of IRF3 activation (MITA but not the murine homologue MPYS, was cleaved in cells infected with DEN-1 or DEN-2 and with expression of the enzymatically active protease NS2B3. The cleavage site of MITA was mapped to LRR↓(96G and the function of MITA was suppressed by dengue protease. DEN replication was reduced with overexpression of MPYS but not with MITA, while DEN replication was enhanced by MPYS knockdown, indicating an antiviral role of MITA/MPYS against DEN infection. The involvement of MITA in DEN-triggered innate immune response was evidenced by reduction of IRF3 activation and IFN induction in cells with MITA knockdown upon DEN-2 infection. NS2B3 physically interacted with MITA, and the interaction and cleavage of MITA could be further enhanced by poly(dA:dT stimulation. Thus, we identified MITA as a novel host target of DEN protease and provide the molecular mechanism of how DEN subverts the host innate immunity.

  2. Expression of the Rai (Shc C) adaptor protein in the human enteric nervous system.

    Science.gov (United States)

    Villanacci, V; Bassotti, G; Ortensi, B; Fisogni, S; Cathomas, G; Maurer, C A; Galletti, A; Salerni, B; Pelicci, G

    2008-03-01

    The adaptor protein Rai (ShcC/N-Shc) is almost exclusively present in the nervous system, although little is documented about its expression in the gut and the enteric nervous system (ENS). As Rai is a physiological substrate of Ret, an important factor for the development of ENS, we have evaluated the expression of Rai in the ENS in various segments of the human gastrointestinal tract. The expression of Rai was assessed by immunohistochemistry in disease-free human gut samples (oesophagus, stomach, small bowel and colon) obtained from subjects undergoing surgical procedures. Rai was not expressed in the epithelia or lymphoid tissue, whereas a moderate level of expression was observed in the endothelial cells of blood vessels and on the outer membrane of smooth muscle cells in both the muscularis mucosae and the muscularis propria. In the ENS, strong positivity was observed only in enteric glial cells, overlapping with GFAP and S100. In conclusion, Rai is expressed in the human gut, especially in the enteric glial cells. We conclude that Rai may provide an additional marker for this cell type.

  3. LIME: a new membrane raft-associated adaptor protein involved in CD4 and CD8 coreceptor signaling

    Czech Academy of Sciences Publication Activity Database

    Brdičková, Naděžda; Brdička, Tomáš; Angelisová, Pavla; Horváth, Ondřej; Špička, Jiří; Hilgert, Ivan; Pačes, Jan; Simeoni, L.; Kliche, S.; Merten, C.; Schraven, B.; Hořejší, Václav

    2003-01-01

    Roč. 198, č. 10 (2003), s. 1453-1462 ISSN 0022-1007 R&D Projects: GA MŠk LN00A079; GA MŠk LN00A026 Grant - others:Wellcome Trust(GB) J1116W24Z Institutional research plan: CEZ:AV0Z5052915 Keywords : immunology * T-lymphocyte * adaptor protein Subject RIV: EC - Immunology Impact factor: 15.302, year: 2003

  4. Recruitment of the Mint3 adaptor is necessary for export of the amyloid precursor protein (APP) from the Golgi complex.

    Science.gov (United States)

    Caster, Amanda H; Kahn, Richard A

    2013-10-04

    The amyloid precursor protein (APP) is a ubiquitously expressed single-pass transmembrane protein that undergoes proteolytic processing by secretases to generate the pathogenic amyloid-β peptide, the major component in Alzheimer plaques. The traffic of APP through the cell determines its exposure to secretases and consequently the cleavages that generate the pathogenic or nonpathogenic peptide fragments. Despite the likely importance of APP traffic to Alzheimer disease, we still lack clear models for the routing and regulation of APP in cells. Like the traffic of most transmembrane proteins, the binding of adaptors to its cytoplasmic tail, which is 47 residues long and contains at least four distinct sorting motifs, regulates that of APP. We tested each of these for effects on the traffic of APP from the Golgi by mutating key residues within them and examining adaptor recruitment at the Golgi and traffic to post-Golgi site(s). We demonstrate strict specificity for recruitment of the Mint3 adaptor by APP at the Golgi, a critical role for Tyr-682 (within the YENPTY motif) in Mint3 recruitment and export of APP from the Golgi, and we identify LAMP1(+) structures as the proximal destination of APP after leaving the Golgi. Together, these data provide a detailed view of the first sorting step in its route to the cell surface and processing by secretases and further highlight the critical role played by Mint3.

  5. Recruitment of the Mint3 Adaptor Is Necessary for Export of the Amyloid Precursor Protein (APP) from the Golgi Complex*

    Science.gov (United States)

    Caster, Amanda H.; Kahn, Richard A.

    2013-01-01

    The amyloid precursor protein (APP) is a ubiquitously expressed single-pass transmembrane protein that undergoes proteolytic processing by secretases to generate the pathogenic amyloid-β peptide, the major component in Alzheimer plaques. The traffic of APP through the cell determines its exposure to secretases and consequently the cleavages that generate the pathogenic or nonpathogenic peptide fragments. Despite the likely importance of APP traffic to Alzheimer disease, we still lack clear models for the routing and regulation of APP in cells. Like the traffic of most transmembrane proteins, the binding of adaptors to its cytoplasmic tail, which is 47 residues long and contains at least four distinct sorting motifs, regulates that of APP. We tested each of these for effects on the traffic of APP from the Golgi by mutating key residues within them and examining adaptor recruitment at the Golgi and traffic to post-Golgi site(s). We demonstrate strict specificity for recruitment of the Mint3 adaptor by APP at the Golgi, a critical role for Tyr-682 (within the YENPTY motif) in Mint3 recruitment and export of APP from the Golgi, and we identify LAMP1+ structures as the proximal destination of APP after leaving the Golgi. Together, these data provide a detailed view of the first sorting step in its route to the cell surface and processing by secretases and further highlight the critical role played by Mint3. PMID:23965993

  6. A Dictyostelium SH2 adaptor protein required for correct DIF-1 signaling and pattern formation.

    Science.gov (United States)

    Sugden, Christopher; Ross, Susan; Annesley, Sarah J; Cole, Christian; Bloomfield, Gareth; Ivens, Alasdair; Skelton, Jason; Fisher, Paul R; Barton, Geoffrey; Williams, Jeffrey G

    2011-05-15

    phototaxis defect, implying that the early and late functions of LrrB are affected in different ways. These observations, coupled with its domain structure, suggest that LrrB is an SH2 adaptor protein active in diverse developmental signaling pathways. Copyright © 2011 Elsevier Inc. All rights reserved.

  7. The murine Nck SH2/SH3 adaptors are important for the development of mesoderm-derived embryonic structures and for regulating the cellular actin network.

    Science.gov (United States)

    Bladt, Friedhelm; Aippersbach, Elke; Gelkop, Sigal; Strasser, Geraldine A; Nash, Piers; Tafuri, Anna; Gertler, Frank B; Pawson, Tony

    2003-07-01

    Mammalian Nck1 and Nck2 are closely related adaptor proteins that possess three SH3 domains, followed by an SH2 domain, and are implicated in coupling phosphotyrosine signals to polypeptides that regulate the actin cytoskeleton. However, the in vivo functions of Nck1 and Nck2 have not been defined. We have mutated the murine Nck1 and Nck2 genes and incorporated beta-galactosidase reporters into the mutant loci. In mouse embryos, the two Nck genes have broad and overlapping expression patterns. They are functionally redundant in the sense that mice deficient for either Nck1 or Nck2 are viable, whereas inactivation of both Nck1 and Nck2 results in profound defects in mesoderm-derived notochord and embryonic lethality at embryonic day 9.5. Fibroblast cell lines derived from Nck1(-/-) Nck2(-/-) embryos have defects in cell motility and in the organization of the lamellipodial actin network. These data suggest that the Nck SH2/SH3 adaptors have important functions in the development of mesodermal structures during embryogenesis, potentially linked to a role in cell movement and cytoskeletal organization.

  8. NTAL (non-T cell activation linker):a transmembrane adaptor protein involved in immunoreceptor signaling

    Czech Academy of Sciences Publication Activity Database

    Brdička, Tomáš; Imrich, Martin; Angelisová, Pavla; Brdičková, Naděžda; Horváth, Ondřej; Špička, Jiří; Hilgert, Ivan; Lusková, Petra; Dráber, Petr; Novák, P.; Engels, N.; Wienands, J.; Simeoni, L.; Osterreicher, J.; Aguado, E.; Malissen, M.; Schraven, B.; Hořejší, Václav

    2002-01-01

    Roč. 196, č. 12 (2002), s. 16180-16185 ISSN 0022-1007 R&D Projects: GA MŠk LN00A026 Keywords : NTAL * transmembrane adaptor * immunoreceptor signaling Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 15.838, year: 2002

  9. The Shc Family Protein Adaptor, Rai, Negatively Regulates T Cell Antigen Receptor Signaling by Inhibiting ZAP-70 Recruitment and Activation

    OpenAIRE

    Ferro, Micol; Savino, Maria Teresa; Ortensi, Barbara; Finetti, Francesca; Genovese, Luca; Masi, Giulia; Ulivieri, Cristina; Benati, Daniela; Pelicci, Giuliana; Baldari, Cosima T.

    2011-01-01

    Rai/ShcC is a member of the Shc family of protein adaptors expressed with the highest abundance in the central nervous system, where it exerts a protective function by coupling neurotrophic receptors to the PI3K/Akt survival pathway. Rai is also expressed, albeit at lower levels, in other cell types, including T and B lymphocytes. We have previously reported that in these cells Rai attenuates antigen receptor signaling, thereby impairing not only cell proliferation but also, opposite to neuro...

  10. Adaptor protein sorting nexin 17 regulates amyloid precursor protein trafficking and processing in the early endosomes

    NARCIS (Netherlands)

    Lee, Jiyeon; Retamal, Claudio; Cuitino, Loreto; Caruano-Yzermans, Amy; Shin, Jung-Eun; van Kerkhof, Peter; Marzolo, Maria-Paz; Bu, Guojun

    2008-01-01

    Accumulation of extracellular amyloid beta peptide (A beta), generated from amyloid precursor protein (APP) processing by beta- and gamma-secretases, is toxic to neurons and is central to the pathogenesis of Alzheimer disease. Production of A beta from APP is greatly affected by the subcellular

  11. G protein-coupled receptors regulate Na+,K+-ATPase activity and endocytosis by modulating the recruitment of adaptor protein 2 and clathrin

    Science.gov (United States)

    Ogimoto, Goichi; Yudowski, Guillermo A.; Barker, Christopher J.; Köhler, Martin; Katz, Adrian I.; Féraille, Eric; Pedemonte, Carlos H.; Berggren, Per-Olof; Bertorello, Alejandro M.

    2000-01-01

    Inhibition of Na+,K+-ATPase (NKA) activity in renal epithelial cells by activation of G protein-coupled receptors is mediated by phosphorylation of the catalytic α-subunit followed by endocytosis of active molecules. We examined whether agonists that counteract this effect do so by dephosphorylation of the α-subunit or by preventing its internalization through a direct interaction with the endocytic network. Oxymetazoline counteracted the action of dopamine on NKA activity, and this effect was achieved not by preventing α-subunit phosphorylation, but by impaired endocytosis of α-subunits into clathrin vesicles and early and late endosomes. Dopamine-induced inhibition of NKA activity and α-subunit endocytosis required the interaction of adaptor protein 2 (AP-2) with the catalytic α-subunit. Phosphorylation of the α-subunit is essential because dopamine failed to promote such interaction in cells lacking the protein kinase C phosphorylation residue (S18A). Confocal microscopy confirmed that oxymetazoline prevents incorporation of NKA molecules into clathrin vesicles by inhibiting the ability of dopamine to recruit clathrin to the plasma membrane. Dopamine decreased the basal levels of inositol hexakisphosphate (InsP6), whereas oxymetazoline prevented this effect. Similar increments (above basal) in the concentration of InsP6 induced by oxymetazoline prevented AP-2 binding to the NKA α-subunit in response to dopamine. In conclusion, inhibition of NKA activity can be reversed by preventing its endocytosis without altering the state of α-subunit phosphorylation; increased InsP6 in response to G protein-coupled receptor signals blocks the recruitment of AP-2 and thereby clathrin-dependent endocytosis of NKA. PMID:10716725

  12. Receptor tyrosine phosphatase R-PTP-alpha is tyrosine-phosphorylated and associated with the adaptor protein Grb2

    DEFF Research Database (Denmark)

    Su, J; Batzer, A; Sap, J

    1994-01-01

    Receptor tyrosine phosphatases (R-PTPases) have generated interest because of their suspected involvement in cellular signal transduction. The adaptor protein Grb2 has been implicated in coupling receptor tyrosine kinases to Ras. We report that a ubiquitous R-PTPase, R-PTP-alpha, is tyrosine......-phosphorylated and associated in vivo with the Grb2 protein. This association can be reproduced in stably and transiently transfected cells, as well as in vitro using recombinant Grb2 protein. Association requires the presence of an intact SH2 domain in Grb2, as well as tyrosine phosphorylation of R-PTP-alpha. This observation...... links a receptor tyrosine phosphatase with a key component of a central cellular signalling pathway and provides a basis for addressing R-PTP-alpha function....

  13. LST1/A is a myeloid leukocyte-specific transmembrane adaptor protein recruiting protein tyrosine phosphatases SHP-1 and SHP-2 to the plasma membrane

    Czech Academy of Sciences Publication Activity Database

    Dráber, Peter; Štěpánek, Ondřej; Hrdinka, Matouš; Drobek, Aleš; Chmátal, Lukáš; Malá, Linda; Ormsby, Tereza; Angelisová, Pavla; Hořejší, Václav; Brdička, Tomáš

    2012-01-01

    Roč. 287, č. 27 (2012), s. 22812-228221 ISSN 0021-9258 R&D Projects: GA ČR GEMEM/09/E011; GA ČR(CZ) GBP302/12/G101; GA MŠk 1M0506 Institutional research plan: CEZ:AV0Z50520514 Institutional support: RVO:68378050 Keywords : adaptor proteins * myeloid cell * signal transduction * tetraspanins * LST1/A Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 4.651, year: 2012

  14. Probing the Energetics of Dynactin Filament Assembly and the Binding of Cargo Adaptor Proteins Using Molecular Dynamics Simulation and Electrostatics-Based Structural Modeling.

    Science.gov (United States)

    Zheng, Wenjun

    2017-01-10

    Dynactin, a large multiprotein complex, binds with the cytoplasmic dynein-1 motor and various adaptor proteins to allow recruitment and transportation of cellular cargoes toward the minus end of microtubules. The structure of the dynactin complex is built around an actin-like minifilament with a defined length, which has been visualized in a high-resolution structure of the dynactin filament determined by cryo-electron microscopy (cryo-EM). To understand the energetic basis of dynactin filament assembly, we used molecular dynamics simulation to probe the intersubunit interactions among the actin-like proteins, various capping proteins, and four extended regions of the dynactin shoulder. Our simulations revealed stronger intersubunit interactions at the barbed and pointed ends of the filament and involving the extended regions (compared with the interactions within the filament), which may energetically drive filament termination by the capping proteins and recruitment of the actin-like proteins by the extended regions, two key features of the dynactin filament assembly process. Next, we modeled the unknown binding configuration among dynactin, dynein tails, and a number of coiled-coil adaptor proteins (including several Bicaudal-D and related proteins and three HOOK proteins), and predicted a key set of charged residues involved in their electrostatic interactions. Our modeling is consistent with previous findings of conserved regions, functional sites, and disease mutations in the adaptor proteins and will provide a structural framework for future functional and mutational studies of these adaptor proteins. In sum, this study yielded rich structural and energetic information about dynactin and associated adaptor proteins that cannot be directly obtained from the cryo-EM structures with limited resolutions.

  15. The structure and polymerase-recognition mechanism of the crucial adaptor protein AND-1 in the human replisome.

    Science.gov (United States)

    Guan, Chengcheng; Li, Jun; Sun, Dapeng; Liu, Yingfang; Liang, Huanhuan

    2017-06-09

    DNA replication in eukaryotic cells is performed by a multiprotein complex called the replisome, which consists of helicases, polymerases, and adaptor molecules. Human a cidic n ucleoplasmic D NA-binding protein 1 (AND-1), also known as WD repeat and high mobility group (HMG)-box DNA-binding protein 1 (WDHD1), is an adaptor molecule crucial for DNA replication. Although structural information for the AND-1 yeast ortholog is available, the mechanistic details for how human AND-1 protein anchors the lagging-strand DNA polymerase α (pol α) to the DNA helicase complex ( C dc45- M CM2-7- G INS, CMG) await elucidation. Here, we report the structures of the N-terminal WD40 and SepB domains of human AND-1, as well as a biochemical analysis of the C-terminal HMG domain. We show that AND-1 exists as a homotrimer mediated by the SepB domain. Mutant study results suggested that a positively charged groove within the SepB domain provides binding sites for pol α. Different from its ortholog protein in budding yeast, human AND-1 is recruited to the CMG complex, mediated by unknown participants other than Go Ichi Ni San. In addition, we show that AND-1 binds to DNA in vitro , using its C-terminal HMG domain. In conclusion, our findings provide important insights into the mechanistic details of human AND-1 function, advancing our understanding of replisome formation during eukaryotic replication. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

  16. CD2v Interacts with Adaptor Protein AP-1 during African Swine Fever Infection.

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    Daniel Pérez-Núñez

    Full Text Available African swine fever virus (ASFV CD2v protein is believed to be involved in virulence enhancement, viral hemadsorption, and pathogenesis, although the molecular mechanisms of the function of this viral protein are still not fully understood. Here we describe that CD2v localized around viral factories during ASFV infection, suggesting a role in the generation and/or dynamics of these viral structures and hence in disturbing cellular traffic. We show that CD2v targeted the regulatory trans-Golgi network (TGN protein complex AP-1, a key element in cellular traffic. This interaction was disrupted by brefeldin A even though the location of CD2v around the viral factory remained unchanged. CD2v-AP-1 binding was independent of CD2v glycosylation and occurred on the carboxy-terminal part of CD2v, where a canonical di-Leu motif previously reported to mediate AP-1 binding in eukaryotic cells, was identified. This motif was shown to be functionally interchangeable with the di-Leu motif present in HIV-Nef protein in an AP-1 binding assay. However, we demonstrated that it was not involved either in CD2v cellular distribution or in CD2v-AP-1 binding. Taken together, these findings shed light on CD2v function during ASFV infection by identifying AP-1 as a cellular factor targeted by CD2v and hence elucidate the cellular pathways used by the virus to enhance infectivity.

  17. Brain-derived neurotrophic factor modulation of Kv1.3 channel is disregulated by adaptor proteins Grb10 and nShc

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    Marks David R

    2009-01-01

    Full Text Available Abstract Background Neurotrophins are important regulators of growth and regeneration, and acutely, they can modulate the activity of voltage-gated ion channels. Previously we have shown that acute brain-derived neurotrophic factor (BDNF activation of neurotrophin receptor tyrosine kinase B (TrkB suppresses the Shaker voltage-gated potassium channel (Kv1.3 via phosphorylation of multiple tyrosine residues in the N and C terminal aspects of the channel protein. It is not known how adaptor proteins, which lack catalytic activity, but interact with members of the neurotrophic signaling pathway, might scaffold with ion channels or modulate channel activity. Results We report the co-localization of two adaptor proteins, neuronal Src homology and collagen (nShc and growth factor receptor-binding protein 10 (Grb10, with Kv1.3 channel as demonstrated through immunocytochemical approaches in the olfactory bulb (OB neural lamina. To further explore the specificity and functional ramification of adaptor/channel co-localization, we performed immunoprecipitation and Western analysis of channel, kinase, and adaptor transfected human embryonic kidney 293 cells (HEK 293. nShc formed a direct protein-protein interaction with Kv1.3 that was independent of BDNF-induced phosphorylation of Kv1.3, whereas Grb10 did not complex with Kv1.3 in HEK 293 cells. Both adaptors, however, co-immunoprecipitated with Kv1.3 in native OB. Grb10 was interestingly able to decrease the total expression of Kv1.3, particularly at the membrane surface, and subsequently eliminated the BDNF-induced phosphorylation of Kv1.3. To examine the possibility that the Src homology 2 (SH2 domains of Grb10 were directly binding to basally phosphorylated tyrosines in Kv1.3, we utilized point mutations to substitute multiple tyrosine residues with phenylalanine. Removal of the tyrosines 111–113 and 449 prevented Grb10 from decreasing Kv1.3 expression. In the absence of either adaptor protein

  18. TIRAP, an Adaptor Protein for TLR2/4, Transduces a Signal from RAGE Phosphorylated upon Ligand Binding

    Science.gov (United States)

    Sakaguchi, Masakiyo; Murata, Hitoshi; Yamamoto, Ken-ichi; Ono, Tomoyuki; Sakaguchi, Yoshihiko; Motoyama, Akira; Hibino, Toshihiko; Kataoka, Ken; Huh, Nam-ho

    2011-01-01

    The receptor for advanced glycation end products (RAGE) is thought to be involved in the pathogenesis of a broad range of inflammatory, degenerative and hyperproliferative diseases. It binds to diverse ligands and activates multiple intracellular signaling pathways. Despite these pivotal functions, molecular events just downstream of ligand-activated RAGE have been surprisingly unknown. Here we show that the cytoplasmic domain of RAGE is phosphorylated at Ser391 by PKCζ upon binding of ligands. TIRAP and MyD88, which are known to be adaptor proteins for Toll-like receptor-2 and -4 (TLR2/4), bound to the phosphorylated RAGE and transduced a signal to downstream molecules. Blocking of the function of TIRAP and MyD88 largely abrogated intracellular signaling from ligand-activated RAGE. Our findings indicate that functional interaction between RAGE and TLRs coordinately regulates inflammation, immune response and other cellular functions. PMID:21829704

  19. Transmembrane adaptor protein TRIM regulates T cell receptor (TCR) expression and TCR-mediated signaling via an association with the TCR zeta chain

    Czech Academy of Sciences Publication Activity Database

    Kirchgesser, H.; Dietrich, J.; Scherer, J.; Isomaki, P.; Kořínek, Vladimír; Hilgert, Ivan; Bruyns, E.; Leo, A.; Cope, A. P.; Schraven, B.

    2001-01-01

    Roč. 193, č. 11 (2001), s. 1269-1283 ISSN 0022-1007 R&D Projects: GA ČR GA204/99/0367 Institutional research plan: CEZ:AV0Z5052915 Keywords : receptor * adaptor protein * signaling Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 15.340, year: 2001

  20. LAT--an important raft-associated transmembrane adaptor protein. Delivered on 6 July 2009 at the 34th FEBS Congress in Prague, Czech Republic

    Czech Academy of Sciences Publication Activity Database

    Hořejší, Václav; Otáhal, Pavel; Brdička, Tomáš

    2010-01-01

    Roč. 277, č. 21 (2010), s. 4383-4397 ISSN 1742-464X R&D Projects: GA ČR GEMEM/09/E011; GA MŠk 1M0506 Institutional research plan: CEZ:AV0Z50520514 Keywords : LAT * transmembrane adaptor protein * membrane rafts Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 3.129, year: 2010

  1. Brucella TIR-like protein TcpB/Btp1 specifically targets the host adaptor protein MAL/TIRAP to promote infection.

    Science.gov (United States)

    Li, Wenna; Ke, Yuehua; Wang, Yufei; Yang, Mingjuan; Gao, Junguang; Zhan, Shaoxia; Xinying, Du; Huang, Liuyu; Li, Wenfeng; Chen, Zeliang; Li, Juan

    2016-08-26

    Brucella spp. are known to avoid host immune recognition and weaken the immune response to infection. Brucella like accomplish this by employing two clever strategies, called the stealth strategy and hijacking strategy. The TIR domain-containing protein (TcpB/Btp1) of Brucella melitensis is thought to be involved in inhibiting host NF-κB activation by binding to adaptors downstream of Toll-like receptors. However, of the five TIR domain-containing adaptors conserved in mammals, whether MyD88 or MAL, even other three adaptors, are specifically targeted by TcpB has not been identified. Here, we confirmed the effect of TcpB on B.melitensis virulence in mice and found that TcpB selectively targets MAL. By using siRNA against MAL, we found that TcpB from B.melitensis is involved in intracellular survival and that MAL affects intracellular replication of B.melitensis. Our results confirm that TcpB specifically targets MAL/TIRAP to disrupt downstream signaling pathways and promote intra-host survival of Brucella spp. Copyright © 2016 Elsevier Inc. All rights reserved.

  2. A dimer of the Toll-like receptor 4 cytoplasmic domain provides a specific scaffold for the recruitment of signalling adaptor proteins.

    Directory of Open Access Journals (Sweden)

    Ricardo Núñez Miguel

    2007-08-01

    Full Text Available The Toll-like receptor 4 (TLR4 is a class I transmembrane receptor expressed on the surface of immune system cells. TLR4 is activated by exposure to lipopolysaccharides derived from the outer membrane of Gram negative bacteria and forms part of the innate immune response in mammals. Like other class 1 receptors, TLR4 is activated by ligand induced dimerization, and recent studies suggest that this causes concerted conformational changes in the receptor leading to self association of the cytoplasmic Toll/Interleukin 1 receptor (TIR signalling domain. This homodimerization event is proposed to provide a new scaffold that is able to bind downstream signalling adaptor proteins. TLR4 uses two different sets of adaptors; TRAM and TRIF, and Mal and MyD88. These adaptor pairs couple two distinct signalling pathways leading to the activation of interferon response factor 3 (IRF-3 and nuclear factor kappaB (NFkappaB respectively. In this paper we have generated a structural model of the TLR4 TIR dimer and used molecular docking to probe for potential sites of interaction between the receptor homodimer and the adaptor molecules. Remarkably, both the Mal and TRAM adaptors are strongly predicted to bind at two symmetry-related sites at the homodimer interface. This model of TLR4 activation is supported by extensive functional studies involving site directed mutagenesis, inhibition by cell permeable peptides and stable protein phosphorylation of receptor and adaptor TIR domains. Our results also suggest a molecular mechanism for two recent findings, the caspase 1 dependence of Mal signalling and the protective effects conferred by the Mal polymorphism Ser180Leu.

  3. Adaptor Protein Complexes AP-1 and AP-3 Are Required by the HHV-7 Immunoevasin U21 for Rerouting of Class I MHC Molecules to the Lysosomal Compartment

    Science.gov (United States)

    Kimpler, Lisa A.; Glosson, Nicole L.; Downs, Deanna; Gonyo, Patrick; May, Nathan A.; Hudson, Amy W.

    2014-01-01

    The human herpesvirus-7 (HHV-7) U21 gene product binds to class I major histocompatibility complex (MHC) molecules and reroutes them to a lysosomal compartment. Trafficking of integral membrane proteins to lysosomes is mediated through cytoplasmic sorting signals that recruit heterotetrameric clathrin adaptor protein (AP) complexes, which in turn mediate protein sorting in post-Golgi vesicular transport. Since U21 can mediate rerouting of class I molecules to lysosomes even when lacking its cytoplasmic tail, we hypothesize the existence of a cellular protein that contains the lysosomal sorting information required to escort class I molecules to the lysosomal compartment. If such a protein exists, we expect that it might recruit clathrin adaptor protein complexes as a means of lysosomal sorting. Here we describe experiments demonstrating that the μ adaptins from AP-1 and AP-3 are involved in U21-mediated trafficking of class I molecules to lysosomes. These experiments support the idea that a cellular protein(s) is necessary for U21-mediated lysosomal sorting of class I molecules. We also examine the impact of transient versus chronic knockdown of these adaptor protein complexes, and show that the few remaining μ subunits in the cells are eventually able to reroute class I molecules to lysosomes. PMID:24901711

  4. The ubiquitin ligase RNF5 regulates antiviral responses by mediating degradation of the adaptor protein MITA.

    Science.gov (United States)

    Zhong, Bo; Zhang, Lu; Lei, Caoqi; Li, Ying; Mao, Ai-Ping; Yang, Yan; Wang, Yan-Yi; Zhang, Xiao-Lian; Shu, Hong-Bing

    2009-03-20

    Viral infection activates transcription factors NF-kappaB and IRF3, which collaborate to induce type I interferons (IFNs) and elicit innate antiviral response. MITA (also known as STING) has recently been identified as an adaptor that links virus-sensing receptors to IRF3 activation. Here, we showed that the E3 ubiquitin ligase RNF5 interacted with MITA in a viral-infection-dependent manner. Overexpression of RNF5 inhibited virus-triggered IRF3 activation, IFNB1 expression, and cellular antiviral response, whereas knockdown of RNF5 had opposite effects. RNF5 targeted MITA at Lys150 for ubiquitination and degradation after viral infection. Both MITA and RNF5 were located at the mitochondria and endoplasmic reticulum (ER) and viral infection caused their redistribution to the ER and mitochondria, respectively. We further found that virus-induced ubiquitination and degradation of MITA by RNF5 occurred at the mitochondria. These findings suggest that RNF5 negatively regulates virus-triggered signaling by targeting MITA for ubiquitination and degradation at the mitochondria.

  5. The adaptor protein alpha-syntrophin is reduced in human non-alcoholic steatohepatitis but is unchanged in hepatocellular carcinoma.

    Science.gov (United States)

    Rein-Fischboeck, Lisa; Pohl, Rebekka; Haberl, Elisabeth M; Weiss, Thomas S; Buechler, Christa

    2017-10-01

    The adaptor protein alpha-syntrophin (SNTA) is differentially expressed in varying types of cancer and affects triglyceride levels, inflammatory response and cell proliferation. However, little is known about the expression of SNTA in liver diseases. Non-alcoholic steatohepatitis (NASH) is characterized by hepatic steatosis, inflammation and eventually fibrosis, and may progress to hepatocellular carcinoma (HCC). Here, SNTA mRNA was analyzed in liver tissues from 71 non-alcoholic fatty liver disease patients and 32 controls to assess associations with disease characteristics. SNTA mRNA expression was reduced in NASH liver and negatively correlated with steatosis, inflammation, fibrosis and NASH scores. In the NASH patients, those with type 2 diabetes had a higher fibrosis score, reduced inflammation and increased hepatic SNTA mRNA levels demonstrating a strong association of SNTA mRNA levels with inflammation. Recently, we have shown diminished expression of the high-density lipoprotein scavenger receptor BI (SR-BI) in the liver of syntrophin-deficient mice. Indeed, hepatic SNTA and SR-BI mRNA were positively correlated. SNTA protein was further determined in tumor and non-tumorous tissues of 21 HCC patients. Protein expression was unchanged in the tumor and not related to staging and grading. Present study identified associations of hepatic SNTA mRNA levels with SR-BI and features of NASH assuming a function of this protein in chronic liver disease and cholesterol metabolism. Copyright © 2017 Elsevier Inc. All rights reserved.

  6. Matrilin-2, an extracellular adaptor protein, is needed for the regeneration of muscle, nerve and other tissues

    Directory of Open Access Journals (Sweden)

    Éva Korpos

    2015-01-01

    Full Text Available The extracellular matrix (ECM performs essential functions in the differentiation, maintenance and remodeling of tissues during development and regeneration, and it undergoes dynamic changes during remodeling concomitant to alterations in the cell-ECM interactions. Here we discuss recent data addressing the critical role of the widely expressed ECM protein, matrilin-2 (Matn2 in the timely onset of differentiation and regeneration processes in myogenic, neural and other tissues and in tumorigenesis. As a multiadhesion adaptor protein, it interacts with other ECM proteins and integrins. Matn2 promotes neurite outgrowth, Schwann cell migration, neuromuscular junction formation, skeletal muscle and liver regeneration and skin wound healing. Matn2 deposition by myoblasts is crucial for the timely induction of the global switch toward terminal myogenic differentiation during muscle regeneration by affecting transforming growth factor beta/bone morphogenetic protein 7/Smad and other signal transduction pathways. Depending on the type of tissue and the pathomechanism, Matn2 can also promote or suppress tumor growth.

  7. Role of adaptor proteins and clathrin in the trafficking of human kidney anion exchanger 1 (kAE1) to the cell surface.

    Science.gov (United States)

    Junking, Mutita; Sawasdee, Nunghathai; Duangtum, Natapol; Cheunsuchon, Boonyarit; Limjindaporn, Thawornchai; Yenchitsomanus, Pa-thai

    2014-07-01

    Kidney anion exchanger 1 (kAE1) plays an important role in acid-base homeostasis by mediating chloride/bicarbornate (Cl-/HCO3-) exchange at the basolateral membrane of α-intercalated cells in the distal nephron. Impaired intracellular trafficking of kAE1 caused by mutations of SLC4A1 encoding kAE1 results in kidney disease - distal renal tubular acidosis (dRTA). However, it is not known how the intracellular sorting and trafficking of kAE1 from trans-Golgi network (TGN) to the basolateral membrane occurs. Here, we studied the role of basolateral-related sorting proteins, including the mu1 subunit of adaptor protein (AP) complexes, clathrin and protein kinase D, on kAE1 trafficking in polarized and non-polarized kidney cells. By using RNA interference, co-immunoprecipitation, yellow fluorescent protein-based protein fragment complementation assays and immunofluorescence staining, we demonstrated that AP-1 mu1A, AP-3 mu1, AP-4 mu1 and clathrin (but not AP-1 mu1B, PKD1 or PKD2) play crucial roles in intracellular sorting and trafficking of kAE1. We also demonstrated colocalization of kAE1 and basolateral-related sorting proteins in human kidney tissues by double immunofluorescence staining. These findings indicate that AP-1 mu1A, AP-3 mu1, AP-4 mu1 and clathrin are required for kAE1 sorting and trafficking from TGN to the basolateral membrane of acid-secreting α-intercalated cells. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  8. Downregulation of the NHE3-binding PDZ-adaptor protein PDZK1 expression during cytokine-induced inflammation in interleukin-10-deficient mice.

    Directory of Open Access Journals (Sweden)

    Henrike Lenzen

    Full Text Available BACKGROUND: Impaired salt and water absorption is an important feature in the pathogenesis of diarrhea in inflammatory bowel disease (IBD. We analyzed the expression of proinflammatory cytokines in the infiltrating immune cells and the function and expression of the Na(+/H(+ exchanger isoform 3 (NHE3 and its regulatory PDZ-adaptor proteins NHERF1, NHERF2, and PDZK1 in the colon of interleukin-10-deficient (IL-10(-/- mice. METHODOLOGY/PRINCIPAL FINDINGS: Gene and protein expression were analyzed by real-time reverse transcription polymerase chain reaction (qRT-PCR, in situ RT-PCR, and immunohistochemistry. NHE3 activity was measured fluorometrically in apical enterocytes within isolated colonic crypts. Mice developed chronic colitis characterized by a typical immune cell infiltration composed of T-lymphocytes and macrophages, with high levels of gene and protein expression of the proinflammatory cytokines interleukin-1β and tumor necrosis factor-α. In parallel, inducible nitric oxide synthase expression was increased while procaspase 3 expression was unaffected. Interferon-γ expression remained low. Although acid-activated NHE3 activity was significantly decreased, the inflammatory process did not affect its gene and protein expression or its abundance and localization in the apical membrane. However, expression of the PDZ-adaptor proteins NHERF2 and PDZK1 was downregulated. NHERF1 expression was unchanged. In a comparative analysis we observed the PDZK1 downregulation also in the DSS (dextran sulphate sodium model of colitis. CONCLUSIONS/SIGNIFICANCE: The impairment of the absorptive function of the inflamed colon in the IL-10(-/- mouse, in spite of unaltered NHE3 expression and localization, is accompanied by the downregulation of the NHE3-regulatory PDZ adaptors NHERF2 and PDZK1. We propose that the downregulation of PDZ-adaptor proteins may be an important factor leading to NHE3 dysfunction and diarrhea in the course of the cytokine

  9. Regulation of protease-activated receptor 1 signaling by the adaptor protein complex 2 and R4 subfamily of regulator of G protein signaling proteins.

    Science.gov (United States)

    Chen, Buxin; Siderovski, David P; Neubig, Richard R; Lawson, Mark A; Trejo, Joann

    2014-01-17

    The G protein-coupled protease-activated receptor 1 (PAR1) is irreversibly proteolytically activated by thrombin. Hence, the precise regulation of PAR1 signaling is important for proper cellular responses. In addition to desensitization, internalization and lysosomal sorting of activated PAR1 are critical for the termination of signaling. Unlike most G protein-coupled receptors, PAR1 internalization is mediated by the clathrin adaptor protein complex 2 (AP-2) and epsin-1, rather than β-arrestins. However, the function of AP-2 and epsin-1 in the regulation of PAR1 signaling is not known. Here, we report that AP-2, and not epsin-1, regulates activated PAR1-stimulated phosphoinositide hydrolysis via two different mechanisms that involve, in part, a subset of R4 subfamily of "regulator of G protein signaling" (RGS) proteins. A significantly greater increase in activated PAR1 signaling was observed in cells depleted of AP-2 using siRNA or in cells expressing a PAR1 (420)AKKAA(424) mutant with defective AP-2 binding. This effect was attributed to AP-2 modulation of PAR1 surface expression and efficiency of G protein coupling. We further found that ectopic expression of R4 subfamily members RGS2, RGS3, RGS4, and RGS5 reduced activated PAR1 wild-type signaling, whereas signaling by the PAR1 AKKAA mutant was minimally affected. Intriguingly, siRNA-mediated depletion analysis revealed a function for RGS5 in the regulation of signaling by the PAR1 wild type but not the AKKAA mutant. Moreover, activation of the PAR1 wild type, and not the AKKAA mutant, induced Gαq association with RGS3 via an AP-2-dependent mechanism. Thus, AP-2 regulates activated PAR1 signaling by altering receptor surface expression and through recruitment of RGS proteins.

  10. Dual role of the Toxoplasma gondii clathrin adaptor AP1 in the sorting of rhoptry and microneme proteins and in parasite division.

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    Kannan Venugopal

    2017-04-01

    Full Text Available Toxoplasma gondii possesses a highly polarized secretory system, which efficiently assembles de novo micronemes and rhoptries during parasite replication. These apical secretory organelles release their contents into host cells promoting parasite invasion and survival. Using a CreLox-based inducible knock-out strategy and the ddFKBP over-expression system, we unraveled novel functions of the clathrin adaptor complex TgAP1. First, our data indicate that AP1 in T. gondii likely functions as a conserved heterotetrameric complex composed of the four subunits γ, β, μ1, σ1 and interacts with known regulators of clathrin-mediated vesicular budding such as the unique ENTH-domain containing protein, which we named Epsin-like protein (TgEpsL. Disruption of the μ1 subunit resulted in the mis-sorting of microneme proteins at the level of the Trans-Golgi-Network (TGN. Furthermore, we demonstrated that TgAP1 regulates rhoptry biogenesis by activating rhoptry protein exit from the TGN, but also participates in the post-Golgi maturation process of preROP compartments into apically anchored club-shaped mature organelles. For this latter activity, our data indicate a specific functional relationship between TgAP1 and the Rab5A-positive endosome-like compartment. In addition, we unraveled an original role for TgAP1 in the regulation of parasite division. APμ1-depleted parasites undergo normal daughter cell budding and basal complex assembly but fail to segregate at the end of cytokinesis.

  11. The Adaptor Protein SAP Directly Associates with CD3ζ Chain and Regulates T Cell Receptor Signaling

    Science.gov (United States)

    Proust, Richard; Bertoglio, Jacques; Gesbert, Franck

    2012-01-01

    Mutations altering the gene encoding the SLAM associated protein (SAP) are responsible for the X-linked lymphoproliferative disease or XLP1. Its absence is correlated with a defective NKT cells development, a decrease in B cell functions and a reduced T cells and NK cells cytotoxic activities, thus leading to an immunodeficiency syndrome. SAP is a small 128 amino-acid long protein that is almost exclusively composed of an SH2 domain. It has been shown to interact with the CD150/SLAM family of receptors, and in a non-canonical manner with SH3 containing proteins such as Fyn, βPIX, PKCθ and Nck1. It would thus play the role of a minimal adaptor protein. It has been shown that SAP plays an important function in the activation of T cells through its interaction with the SLAM family of receptors. Therefore SAP defective T cells display a reduced activation of signaling events downstream of the TCR-CD3 complex triggering. In the present work, we evidence that SAP is a direct interactor of the CD3ζ chain. This direct interaction occurs through the first ITAM of CD3ζ, proximal to the membrane. Additionally, we show that, in the context of the TCR-CD3 signaling, an Sh-RNA mediated silencing of SAP is responsible for a decrease of several canonical T cell signaling pathways including Erk, Akt and PLCγ1 and to a reduced induction of IL-2 and IL-4 mRNA. Altogether, we show that SAP plays a central function in the T cell activation processes through a direct association with the CD3 complex. PMID:22912825

  12. PRR7 Is a transmembrane adaptor protein expressed in activated T cells involved in regulation of T cell receptor signaling and apoptosis

    Czech Academy of Sciences Publication Activity Database

    Hrdinka, Matouš; Dráber, Peter; Štěpánek, Ondřej; Ormsby, Tereza; Otáhal, Pavel; Angelisová, Pavla; Brdička, Tomáš; Pačes, Jan; Hořejší, Václav; Drbal, Karel

    2011-01-01

    Roč. 286, č. 22 (2011), s. 19617-19629 ISSN 0021-9258 R&D Projects: GA MŠk 1M0506 Grant - others:GAČR(CZ) MEM/09/E011 Institutional research plan: CEZ:AV0Z50520514 Keywords : PRR7 * transmembrane adaptor protein * apoptosis Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 4.773, year: 2011

  13. Structure of a putative ClpS N-end rule adaptor protein from the malaria pathogen Plasmodium falciparum.

    Science.gov (United States)

    AhYoung, Andrew P; Koehl, Antoine; Vizcarra, Christina L; Cascio, Duilio; Egea, Pascal F

    2016-03-01

    The N-end rule pathway uses an evolutionarily conserved mechanism in bacteria and eukaryotes that marks proteins for degradation by ATP-dependent chaperones and proteases such as the Clp chaperones and proteases. Specific N-terminal amino acids (N-degrons) are sufficient to target substrates for degradation. In bacteria, the ClpS adaptor binds and delivers N-end rule substrates for their degradation upon association with the ClpA/P chaperone/protease. Here, we report the first crystal structure, solved at 2.7 Å resolution, of a eukaryotic homolog of bacterial ClpS from the malaria apicomplexan parasite Plasmodium falciparum (Pfal). Despite limited sequence identity, Plasmodium ClpS is very similar to bacterial ClpS. Akin to its bacterial orthologs, plasmodial ClpS harbors a preformed hydrophobic pocket whose geometry and chemical properties are compatible with the binding of N-degrons. However, while the N-degron binding pocket in bacterial ClpS structures is open and accessible, the corresponding pocket in Plasmodium ClpS is occluded by a conserved surface loop that acts as a latch. Despite the closed conformation observed in the crystal, we show that, in solution, Pfal-ClpS binds and discriminates peptides mimicking bona fide N-end rule substrates. The presence of an apicoplast targeting peptide suggests that Pfal-ClpS localizes to this plastid-like organelle characteristic of all Apicomplexa and hosting most of its Clp machinery. By analogy with the related ClpS1 from plant chloroplasts and cyanobacteria, Plasmodium ClpS likely functions in association with ClpC in the apicoplast. Our findings open new venues for the design of novel anti-malarial drugs aimed at disrupting parasite-specific protein quality control pathways. © 2016 The Protein Society.

  14. Impact of the adaptor protein GIPC1/Synectin on radioresistance and survival after irradiation of prostate cancer

    Energy Technology Data Exchange (ETDEWEB)

    Singer, A. [University Hospital Dresden (Germany). Dept. of Radiation Oncology; Deuse, Y.; Koch, U. [University Hospital Dresden (Germany). Dept. of Radiation Oncology; OncoRay National Center for Radiation Research in Oncology (Germany)] [and others

    2012-12-15

    Purpose: Studies have shown that GIPC1/Synectin is an essential adaptor protein of receptors that play an important role in cancer progression and therapy resistance. This is the first study to explore the role of GIPC1/Synectin in radioresistance of prostate cancer and as a possible predictive marker for outcome of primary radiation therapy. Materials and methods: The effect of RNA interference-mediated GIPC1/Synectin depletion on clonogenic cell survival after irradiation with 0, 2, 4, or 6 Gy was assayed in two different GIPC1/Synectin-expressing human prostate cancer cell lines. The clinical outcome data of 358 men who underwent radiotherapy of prostate cancer with a curative intention were analyzed retrospectively. Uni- and multivariate analysis was performed of prostate-specific antigen recurrence-free survival and overall survival in correlation with protein expression in pretreatment biopsy specimens. Protein expression was evaluated by standard immunohistochemistry methods. Results: In cell culture experiments, no change was detected in radiosensitivity after depletion of GIPC1/Synectin in GIPC1/Synectin-expressing prostate cancer cell lines. Furthermore, there was no correlation between GIPC1/Synectin expression in human pretreatment biopsy samples and overall or biochemical recurrence-free survival after radiotherapy in a retrospective analysis of the study cohort. Conclusion: Our results do not show a predictive or prognostic function of GIPC1/Synectin expression for the outcome of radiotherapy in prostate cancer. Furthermore, our in vitro results do not support a role of GIPC1 in the cellular radiation response. However, the role of GIPC1 in the progression of prostate cancer and its precursors should be subject to further research. (orig.)

  15. Role of Crk Adaptor Proteins in Cellular Migration and Invasion in Human Breast Cancer

    National Research Council Canada - National Science Library

    Fathers, Kelly E

    2008-01-01

    .... As migration and invasion are important components of the metastatic cascade, future work includes performing in vivo metastasis assays using cells with stably knocked down expression of Crk proteins...

  16. Pertussis toxin targets the innate immunity through DAP12, FcRγ, and MyD88 adaptor proteins.

    Science.gov (United States)

    Phongsisay, Vongsavanh; Iizasa, Ei'ichi; Hara, Hiromitsu; Yoshida, Hiroki

    2017-04-01

    Activation of the innate immunity by adjuvants, such as pertussis toxin (PTX), in the presence of autoreactive lymphocytes and antigen mimicry is sufficient to trigger autoimmunity. Toll-like, C-type lectin, and immunglobulin-like receptors play an important role in the innate immunity by sensing a variety of microbial products through several adaptor proteins, including MyD88, DAP12, and FcRγ. This study investigated the interaction between PTX and innate immune components. The direct interactions between coated PTX and receptor-fusion proteins were examined using ELISA-based binding assays. Functionally, PTX-binding receptors could be classified into two groups: inhibition (DAP12-coupled TREM2, ITIM-bearing SIRPα, SIGNR1/SIGNR3/DCSIGN) and activation (MyD88-associated TLR4, DAP12-coupled LMIR5/CD300b, FcRγ-coupled LMIR8/CD300c, CLEC9A, MGL-1). DAP12, MyD88, and FcRγ were selected for further investigation. A comprehensive analysis of gene transcription showed that PTX up-regulated the expression of various inflammatory mediators. DAP12 deficiency resulted in reduction or enhancement of inflammatory responses in a cytokine-specific manner. PTX was able to activate the TREM2-DAP12 signalling pathway. PTX induced lower expression of inflammatory mediators in the absence of FcRγ alone and substantially lost its inflammatory capacity in the absence of both FcRγ and MyD88. PTX was able to activate the MyD88-NF-κB signalling pathway in the presence of TLR2 or TLR4. The inflammatory activity of PTX was completely lost by heating. These results demonstrate that PTX targets the innate immunity through DAP12, FcRγ, and MyD88 providing new insights into the immunobiology of PTX. Copyright © 2016 Elsevier GmbH. All rights reserved.

  17. Characterization of the liver kinase B1-mouse protein-25 -Ste-20-related adaptor protein complex in adult mouse skeletal muscle.

    Science.gov (United States)

    Smith, Cody D; Compton, Richard A; Bowler, Joshua S; Kemp, Jonathan T; Sudweeks, Sterling N; Thomson, David M; Winder, William W

    2011-12-01

    In liver, the AMP-activated protein kinase kinase (AMPKK) complex was identified as the association of liver kinase B1 (LKB1), mouse protein 25 (MO25α/β), and Ste-20-related adaptor protein (STRADα/β); however, this complex has yet to be characterized in skeletal muscle. We demonstrate the expression of the LKB1-MO25-STRAD complex in skeletal muscle, confirm the absence of mRNA splice variants, and report the relative mRNA expression levels of these proteins in control and muscle-specific LKB1 knockout (LKB1(-/-)) mouse muscle. LKB1 detection in untreated control and LKB1(-/-) muscle lysates revealed two protein bands (50 and 60 kDa), although only the heavier band was diminished in LKB1(-/-) samples [55 ± 2.5 and 13 ± 1.5 arbitrary units (AU) in control and LKB1(-/-), respectively, P protein liquid chromatography. Mass spectrometry confirmed LKB1 protein detection in the 60-kDa protein band, while none was detected in the 50-kDa band. Coimmunoprecipitation assays demonstrated LKB1-MO25-STRAD complex formation. Quantitative PCR revealed significantly reduced LKB1, MO25α, and STRADβ mRNA in LKB1(-/-) muscle. These findings demonstrate that the LKB1-MO25-STRAD complex is the principal AMPKK in skeletal muscle.

  18. The adaptor protein alpha-syntrophin regulates adipocyte lipid droplet growth

    Energy Technology Data Exchange (ETDEWEB)

    Eisinger, Kristina; Rein-Fischboeck, Lisa; Pohl, Rebekka; Meier, Elisabeth M.; Krautbauer, Sabrina; Buechler, Christa, E-mail: christa.buechler@klinik.uni-regensburg.de

    2016-07-01

    The scaffold protein alpha-syntrophin (SNTA) regulates lipolysis indicating a role in lipid homeostasis. Adipocytes are the main lipid storage cells in the body, and here, the function of SNTA has been analyzed in 3T3-L1 cells. SNTA is expressed in preadipocytes and is induced early during adipogenesis. Knock-down of SNTA in preadipocytes increases their proliferation. Proteins which are induced during adipogenesis like adiponectin and caveolin-1, and the inflammatory cytokine IL-6 are at normal levels in the mature cells differentiated from preadipocytes with low SNTA. This suggests that SNTA does neither affect differentiation nor inflammation. Expression of proteins with a role in cholesterol and triglyceride homeostasis is unchanged. Consequently, basal and epinephrine induced lipolysis as well as insulin stimulated phosphorylation of Akt and ERK1/2 are normal. Importantly, adipocytes with low SNTA form smaller lipid droplets and store less triglycerides. Stearoyl-CoA reductase and MnSOD are reduced upon SNTA knock-down but do not contribute to lower lipid levels. Oleate uptake is even increased in cells with SNTA knock-down. In summary, current data show that SNTA is involved in the expansion of lipid droplets independent of adipogenesis. Enhanced preadipocyte proliferation and capacity to store surplus fatty acids may protect adipocytes with low SNTA from lipotoxicity in obesity. - Highlights: • Alpha-syntrophin (SNTA) is expressed in 3T3-L1adipocytes. • SNTA knock-down in preadipocytes has no effect on adipogenesis. • Mature 3T3-L1 differentiated from cells with low SNTA form small lipid droplets. • SCD1 and MnSOD are reduced in adipocytes with low SNTA. • SCD1 knock-down does not alter triglyceride levels.

  19. The Adaptor Protein SH2B3 (Lnk) Negatively Regulates Neurite Outgrowth of PC12 Cells and Cortical Neurons

    Science.gov (United States)

    Wang, Tien-Cheng; Chiu, Hsun; Chang, Yu-Jung; Hsu, Tai-Yu; Chiu, Ing-Ming; Chen, Linyi

    2011-01-01

    SH2B adaptor protein family members (SH2B1-3) regulate various physiological responses through affecting signaling, gene expression, and cell adhesion. SH2B1 and SH2B2 were reported to enhance nerve growth factor (NGF)-induced neuronal differentiation in PC12 cells, a well-established neuronal model system. In contrast, SH2B3 was reported to inhibit cell proliferation during the development of immune system. No study so far addresses the role of SH2B3 in the nervous system. In this study, we provide evidence suggesting that SH2B3 is expressed in the cortex of embryonic rat brain. Overexpression of SH2B3 not only inhibits NGF-induced differentiation of PC12 cells but also reduces neurite outgrowth of primary cortical neurons. SH2B3 does so by repressing NGF-induced activation of PLCγ, MEK-ERK1/2 and PI3K-AKT pathways and the expression of Egr-1. SH2B3 is capable of binding to phosphorylated NGF receptor, TrkA, as well as SH2B1β. Our data further demonstrate that overexpression of SH2B3 reduces the interaction between SH2B1β and TrkA. Consistent with this finding, overexpressing the SH2 domain of SH2B3 is sufficient to inhibit NGF-induced neurite outgrowth. Together, our data demonstrate that SH2B3, unlike the other two family members, inhibits neuronal differentiation of PC12 cells and primary cortical neurons. Its inhibitory mechanism is likely through the competition of TrkA binding with the positive-acting SH2B1 and SH2B2. PMID:22028877

  20. Multiple regulatory roles of the mouse transmembrane adaptor protein NTAL in gene transcription and mast cell physiology.

    Directory of Open Access Journals (Sweden)

    Iva Polakovicova

    Full Text Available Non-T cell activation linker (NTAL; also called LAB or LAT2 is a transmembrane adaptor protein that is expressed in a subset of hematopoietic cells, including mast cells. There are conflicting reports on the role of NTAL in the high affinity immunoglobulin E receptor (FcεRI signaling. Studies carried out on mast cells derived from mice with NTAL knock out (KO and wild type mice suggested that NTAL is a negative regulator of FcεRI signaling, while experiments with RNAi-mediated NTAL knockdown (KD in human mast cells and rat basophilic leukemia cells suggested its positive regulatory role. To determine whether different methodologies of NTAL ablation (KO vs KD have different physiological consequences, we compared under well defined conditions FcεRI-mediated signaling events in mouse bone marrow-derived mast cells (BMMCs with NTAL KO or KD. BMMCs with both NTAL KO and KD exhibited enhanced degranulation, calcium mobilization, chemotaxis, tyrosine phosphorylation of LAT and ERK, and depolymerization of filamentous actin. These data provide clear evidence that NTAL is a negative regulator of FcεRI activation events in murine BMMCs, independently of possible compensatory developmental alterations. To gain further insight into the role of NTAL in mast cells, we examined the transcriptome profiles of resting and antigen-activated NTAL KO, NTAL KD, and corresponding control BMMCs. Through this analysis we identified several genes that were differentially regulated in nonactivated and antigen-activated NTAL-deficient cells, when compared to the corresponding control cells. Some of the genes seem to be involved in regulation of cholesterol-dependent events in antigen-mediated chemotaxis. The combined data indicate multiple regulatory roles of NTAL in gene expression and mast cell physiology.

  1. The Shc family protein adaptor, Rai, negatively regulates T cell antigen receptor signaling by inhibiting ZAP-70 recruitment and activation.

    Directory of Open Access Journals (Sweden)

    Micol Ferro

    Full Text Available Rai/ShcC is a member of the Shc family of protein adaptors expressed with the highest abundance in the central nervous system, where it exerts a protective function by coupling neurotrophic receptors to the PI3K/Akt survival pathway. Rai is also expressed, albeit at lower levels, in other cell types, including T and B lymphocytes. We have previously reported that in these cells Rai attenuates antigen receptor signaling, thereby impairing not only cell proliferation but also, opposite to neurons, cell survival. Here we have addressed the mechanism underlying the inhibitory activity of Rai on TCR signaling. We show that Rai interferes with the TCR signaling cascade one of the earliest steps--recruitment of the initiating kinase ZAP-70 to the phosphorylated subunit of the TCR/CD3 complex, which results in a generalized dampening of the downstream signaling events. The inhibitory activity of Rai is associated to its inducible recruitment to phosphorylated CD3, which occurs in the physiological signaling context of the immune synapse. Rai is moreover found as a pre-assembled complex with ZAP-70 and also constitutively interacts with the regulatory p85 subunit of PI3K, similar to neuronal cells, notwithstanding the opposite biological outcome, i.e. impairment of PI-3K/Akt activation. The data highlight the ability of Rai to establish interactions with the TCR and key signaling mediators which, either directly (e.g. by inhibiting ZAP-70 recruitment to the TCR or sequestering ZAP-70/PI3K in the cytosol or indirectly (e.g. by promoting the recruitment of effectors responsible for signal extinction prevent full triggering of the TCR signaling cascade.

  2. The Shc family protein adaptor, Rai, negatively regulates T cell antigen receptor signaling by inhibiting ZAP-70 recruitment and activation.

    Science.gov (United States)

    Ferro, Micol; Savino, Maria Teresa; Ortensi, Barbara; Finetti, Francesca; Genovese, Luca; Masi, Giulia; Ulivieri, Cristina; Benati, Daniela; Pelicci, Giuliana; Baldari, Cosima T

    2011-01-01

    Rai/ShcC is a member of the Shc family of protein adaptors expressed with the highest abundance in the central nervous system, where it exerts a protective function by coupling neurotrophic receptors to the PI3K/Akt survival pathway. Rai is also expressed, albeit at lower levels, in other cell types, including T and B lymphocytes. We have previously reported that in these cells Rai attenuates antigen receptor signaling, thereby impairing not only cell proliferation but also, opposite to neurons, cell survival. Here we have addressed the mechanism underlying the inhibitory activity of Rai on TCR signaling. We show that Rai interferes with the TCR signaling cascade one of the earliest steps--recruitment of the initiating kinase ZAP-70 to the phosphorylated subunit of the TCR/CD3 complex, which results in a generalized dampening of the downstream signaling events. The inhibitory activity of Rai is associated to its inducible recruitment to phosphorylated CD3, which occurs in the physiological signaling context of the immune synapse. Rai is moreover found as a pre-assembled complex with ZAP-70 and also constitutively interacts with the regulatory p85 subunit of PI3K, similar to neuronal cells, notwithstanding the opposite biological outcome, i.e. impairment of PI-3K/Akt activation. The data highlight the ability of Rai to establish interactions with the TCR and key signaling mediators which, either directly (e.g. by inhibiting ZAP-70 recruitment to the TCR or sequestering ZAP-70/PI3K in the cytosol) or indirectly (e.g. by promoting the recruitment of effectors responsible for signal extinction) prevent full triggering of the TCR signaling cascade.

  3. The Shc Family Protein Adaptor, Rai, Negatively Regulates T Cell Antigen Receptor Signaling by Inhibiting ZAP-70 Recruitment and Activation

    Science.gov (United States)

    Ferro, Micol; Savino, Maria Teresa; Ortensi, Barbara; Finetti, Francesca; Genovese, Luca; Masi, Giulia; Ulivieri, Cristina; Benati, Daniela; Pelicci, Giuliana; Baldari, Cosima T.

    2011-01-01

    Rai/ShcC is a member of the Shc family of protein adaptors expressed with the highest abundance in the central nervous system, where it exerts a protective function by coupling neurotrophic receptors to the PI3K/Akt survival pathway. Rai is also expressed, albeit at lower levels, in other cell types, including T and B lymphocytes. We have previously reported that in these cells Rai attenuates antigen receptor signaling, thereby impairing not only cell proliferation but also, opposite to neurons, cell survival. Here we have addressed the mechanism underlying the inhibitory activity of Rai on TCR signaling. We show that Rai interferes with the TCR signaling cascade one of the earliest steps –recruitment of the initiating kinase ZAP-70 to the phosphorylated subunit of the TCR/CD3 complex, which results in a generalized dampening of the downstream signaling events. The inhibitory activity of Rai is associated to its inducible recruitment to phosphorylated CD3, which occurs in the physiological signaling context of the immune synapse. Rai is moreover found as a pre-assembled complex with ZAP-70 and also constitutively interacts with the regulatory p85 subunit of PI3K, similar to neuronal cells, notwithstanding the opposite biological outcome, i.e. impairment of PI-3K/Akt activation. The data highlight the ability of Rai to establish interactions with the TCR and key signaling mediators which, either directly (e.g. by inhibiting ZAP-70 recruitment to the TCR or sequestering ZAP-70/PI3K in the cytosol) or indirectly (e.g. by promoting the recruitment of effectors responsible for signal extinction) prevent full triggering of the TCR signaling cascade. PMID:22242145

  4. The interaction between the adaptor protein APS and Enigma is involved in actin organisation

    DEFF Research Database (Denmark)

    Barres, Romain; Gonzalez, Teresa; Le Marchand-Brustel, Yannick

    2005-01-01

    and APS were partially co-localised with F-actin in small ruffling structures. Insulin increased the complex formation between APS and Enigma and their co-localisation in large F-actin containing ruffles. While in NIH-3T3 and HeLa cells the co-expression of both Enigma and APS did not modify the actin...... cytoskeleton organisation, expression of Enigma alone led to the formation of F-actin clusters. Similar alteration in actin cytoskeleton organisation was observed in cells expressing both Enigma and APS with a mutation in the NPTY motif. These results identify Enigma as a novel APS-binding protein and suggest...... that the APS/Enigma complex plays a critical role in actin cytoskeleton organisation....

  5. Myelin protein zero/P0 phosphorylation and function require an adaptor protein linking it to RACK1 and PKC alpha.

    Science.gov (United States)

    Gaboreanu, Ana-Maria; Hrstka, Ronald; Xu, Wenbo; Shy, Michael; Kamholz, John; Lilien, Jack; Balsamo, Janne

    2007-05-21

    Point mutations in the cytoplasmic domain of myelin protein zero (P0; the major myelin protein in the peripheral nervous system) that alter a protein kinase Calpha (PKCalpha) substrate motif (198HRSTK201) or alter serines 199 and/or 204 eliminate P0-mediated adhesion. Mutation in the PKCalpha substrate motif (R198S) also causes a form of inherited peripheral neuropathy (Charcot Marie Tooth disease [CMT] 1B), indicating that PKCalpha-mediated phosphorylation of P0 is important for myelination. We have now identified a 65-kD adaptor protein that links P0 with the receptor for activated C kinase 1 (RACK1). The interaction of p65 with P0 maps to residues 179-197 within the cytoplasmic tail of P0. Mutations or deletions that abolish p65 binding reduce P0 phosphorylation and adhesion, which can be rescued by the substitution of serines 199 and 204 with glutamic acid. A mutation in the p65-binding sequence G184R occurs in two families with CMT, and mutation of this residue results in the loss of both p65 binding and adhesion function.

  6. Adaptor Protein Complex-2 (AP-2) and Epsin-1 Mediate Protease-activated Receptor-1 Internalization via Phosphorylation- and Ubiquitination-dependent Sorting Signals*

    Science.gov (United States)

    Chen, Buxin; Dores, Michael R.; Grimsey, Neil; Canto, Isabel; Barker, Breann L.; Trejo, JoAnn

    2011-01-01

    Signaling by protease-activated receptor-1 (PAR1), a G protein-coupled receptor (GPCR) for thrombin, is regulated by desensitization and internalization. PAR1 desensitization is mediated by β-arrestins, like most classic GPCRs. In contrast, internalization of PAR1 occurs through a clathrin- and dynamin-dependent pathway independent of β-arrestins. PAR1 displays two modes of internalization. Constitutive internalization of unactivated PAR1 is mediated by the clathrin adaptor protein complex-2 (AP-2), where the μ2-adaptin subunit binds directly to a tyrosine-based motif localized within the receptor C-tail domain. However, AP-2 depletion only partially inhibits agonist-induced internalization of PAR1, suggesting a function for other clathrin adaptors in this process. Here, we now report that AP-2 and epsin-1 are both critical mediators of agonist-stimulated PAR1 internalization. We show that ubiquitination of PAR1 and the ubiquitin-interacting motifs of epsin-1 are required for epsin-1-dependent internalization of activated PAR1. In addition, activation of PAR1 promotes epsin-1 de-ubiquitination, which may increase its endocytic adaptor activity to facilitate receptor internalization. AP-2 also regulates activated PAR1 internalization via recognition of distal C-tail phosphorylation sites rather than the canonical tyrosine-based motif. Thus, AP-2 and epsin-1 are both required to promote efficient internalization of activated PAR1 and recognize discrete receptor sorting signals. This study defines a new pathway for internalization of mammalian GPCRs. PMID:21965661

  7. MEX3C interacts with adaptor-related protein complex 2 and involves in miR-451a exosomal sorting.

    Directory of Open Access Journals (Sweden)

    Pin Lu

    Full Text Available Some RNA species, especially microRNAs, are non-randomly sorted into exosomes, but how selectivity of RNA exosomal sorting is achieved is unknown. We found that all three variants of RNA-binding ubiquitin E3 ligase (MEX3C-MEX3C-1, MEX3C-2, and MEX3C-3 -interact with adaptor-related protein complex 2 (AP-2, a cargo adaptor in clathrin-mediated endocytosis. MEX3C's C-terminal RING finger domain and the hnRNP K homology (KH domain shared by the three MEX3C variants are both necessary for MEX3C/AP-2 interaction. MEX3C associates with the endolysosomal compartment through an endocytosis-like process. siRNA-mediated inhibition of the MEX3C or AP-2 complex substantially decreased exosomal but not cellular microRNA miR-451a expression. Exosomal sorting is ceramide-dependent but not ESCRT-dependent in microRNA miR-451a. That RNA-binding protein associates with membrane trafficking machinery, and that its involvement in exosomal microRNA expression, suggest the existence of a mechanism for specific recruiting of RNA molecules to endosomes for subsequent exosomal sorting.

  8. WW domain-binding protein 2: an adaptor protein closely linked to the development of breast cancer.

    Science.gov (United States)

    Chen, Shuai; Wang, Han; Huang, Yu-Fan; Li, Ming-Li; Cheng, Jiang-Hong; Hu, Peng; Lu, Chuan-Hui; Zhang, Ya; Liu, Na; Tzeng, Chi-Meng; Zhang, Zhi-Ming

    2017-07-19

    The WW domain is composed of 38 to 40 semi-conserved amino acids shared with structural, regulatory, and signaling proteins. WW domain-binding protein 2 (WBP2), as a binding partner of WW domain protein, interacts with several WW-domain-containing proteins, such as Yes kinase-associated protein (Yap), paired box gene 8 (Pax8), WW-domain-containing transcription regulator protein 1 (TAZ), and WW-domain-containing oxidoreductase (WWOX) through its PPxY motifs within C-terminal region, and further triggers the downstream signaling pathway in vitro and in vivo. Studies have confirmed that phosphorylated form of WBP2 can move into nuclei and activate the transcription of estrogen receptor (ER) and progesterone receptor (PR), whose expression were the indicators of breast cancer development, indicating that WBP2 may participate in the progression of breast cancer. Both overexpression of WBP2 and activation of tyrosine phosphorylation upregulate the signal cascades in the cross-regulation of the Wnt and ER signaling pathways in breast cancer. Following the binding of WBP2 to the WW domain region of TAZ which can accelerate migration, invasion and is required for the transformed phenotypes of breast cancer cells, the transformation of epithelial to mesenchymal of MCF10A is activated, suggesting that WBP2 is a key player in regulating cell migration. When WBP2 binds with WWOX, a tumor suppressor, ER transactivation and tumor growth can be suppressed. Thus, WBP2 may serve as a molecular on/off switch that controls the crosstalk between E2, WWOX, Wnt, TAZ, and other oncogenic signaling pathways. This review interprets the relationship between WBP2 and breast cancer, and provides comprehensive views about the function of WBP2 in the regulation of the pathogenesis of breast cancer and endocrine therapy in breast cancer treatment.

  9. Shc adaptor proteins are key transducers of mitogenic signaling mediated by the G protein-coupled thrombin receptor

    DEFF Research Database (Denmark)

    Chen, Y; Grall, D; Salcini, A E

    1996-01-01

    of the thrombin receptor in growth-responsive CCL39 fibroblasts. Shc phosphorylation by thrombin or the thrombin receptor agonist peptide is maximal by 15 min and persists for > or = 2 h. Following thrombin stimulation, phosphorylated Shc is recruited to Grb2 complexes. One or more pertussis toxin......-insensitive proteins appear to mediate this effect, since (i) pertussis toxin pre-treatment of cells does not blunt the action of thrombin and (ii) Shc phosphorylation on tyrosine can be stimulated by the muscarinic m1 receptor. Shc phosphorylation does not appear to involve protein kinase C, since the addition of 4...

  10. The Adaptor Protein and Arf GTPase-activating Protein Cat-1/Git-1 Is Required for Cellular Transformation

    Science.gov (United States)

    Yoo, Sungsoo M.; Antonyak, Marc A.; Cerione, Richard A.

    2012-01-01

    Cat-1/Git-1 is a multifunctional protein that acts as a GTPase-activating protein (GAP) for Arf GTPases, as well as serves as a scaffold for a number of different signaling proteins. Cat-1 is best known for its role in regulating cell shape and promoting cell migration. However, whether Cat-1 might also contribute to cellular transformation is currently unknown. Here we show that ∼95% of cervical tumor samples examined overexpress Cat-1, suggesting that the up-regulation of Cat-1 expression is a frequent occurrence in this type of cancer. We demonstrate further that knocking down Cat-1 from NIH3T3 fibroblasts expressing an activated form of Cdc42 (Cdc42 F28L), or from the human cervical carcinoma (HeLa) cell line, inhibits the ability of these cells to form colonies in soft agar, an in vitro measure of tumorgenicity. The requirement for Cat-1 when assaying the anchorage-independent growth of transformed fibroblasts and HeLa cells is dependent on its ability to bind paxillin, while being negatively impacted by its Arf-GAP activity. Moreover, the co-expression of Cat-1 and an activated form of Arf6 in fibroblasts was sufficient to induce their transformation. These findings highlight novel roles for Cat-1 and its interactions with the Arf GTPases and paxillin in oncogenic transformation. PMID:22807447

  11. RECOMBINANT FLUORESCENT SENSOR OF HYDROGEN PEROXIDE HyPer FUSED WITH ADAPTOR PROTEIN Ruk/CIN85: DESIGNING OF EXPRESSION VECTOR AND ITS FUNCTIONAL CHARACTERIZATION

    Directory of Open Access Journals (Sweden)

    А. V. Bazalii

    2015-10-01

    Full Text Available The aim of this study was to design the expression vector encoding fluorescent sensor of hydrogen peroxide HyPer fused with adaptor protein Ruk/CIN85 as well as to check its subcellular distribution and ability to sense hydrogen peroxide. It was demonstrated that in transiently transfected HEK293 and MCF-7 cells Ruk/CIN85-HyPer is concentrated in dot-like vesicular structures of different size while HyPer is diffusely distributed throughout the cell. Using live cell fluorescence microscopy we observed gradual increase in hydrogen peroxide concentration in representative vesicular structures during the time of experiment. Thus, the developed genetic construction encoding the chimeric Ruk/CIN85-HyPer fluorescent protein represents a new tool to study localized H2O2 production in living cells.

  12. Expression of the neuronal adaptor protein X11alpha protects against memory dysfunction in a transgenic mouse model of Alzheimer's disease.

    LENUS (Irish Health Repository)

    Mitchell, Jacqueline C

    2010-01-01

    X11alpha is a neuronal-specific adaptor protein that binds to the amyloid-beta protein precursor (AbetaPP). Overexpression of X11alpha reduces Abeta production but whether X11alpha also protects against Abeta-related memory dysfunction is not known. To test this possibility, we crossed X11alpha transgenic mice with AbetaPP-Tg2576 mice. AbetaPP-Tg2576 mice produce high levels of brain Abeta and develop age-related defects in memory function that correlate with increasing Abeta load. Overexpression of X11alpha alone had no detectable adverse effect upon behavior. However, X11alpha reduced brain Abeta levels and corrected spatial reference memory defects in aged X11alpha\\/AbetaPP double transgenics. Thus, X11alpha may be a therapeutic target for Alzheimer\\'s disease.

  13. Seneca Valley Virus Suppresses Host Type I Interferon Production by Targeting Adaptor Proteins MAVS, TRIF, and TANK for Cleavage.

    Science.gov (United States)

    Qian, Suhong; Fan, Wenchun; Liu, Tingting; Wu, Mengge; Zhang, Huawei; Cui, Xiaofang; Zhou, Yun; Hu, Junjie; Wei, Shaozhong; Chen, Huanchun; Li, Xiangmin; Qian, Ping

    2017-08-15

    Seneca Valley virus (SVV) is an oncolytic RNA virus belonging to the Picornaviridae family. Its nucleotide sequence is highly similar to those of members of the Cardiovirus genus. SVV is also a neuroendocrine cancer-selective oncolytic picornavirus that can be used for anticancer therapy. However, the interaction between SVV and its host is yet to be fully characterized. In this study, SVV inhibited antiviral type I interferon (IFN) responses by targeting different host adaptors, including mitochondrial antiviral signaling (MAVS), Toll/interleukin 1 (IL-1) receptor domain-containing adaptor inducing IFN-β (TRIF), and TRAF family member-associated NF-κB activator (TANK), via viral 3C protease (3C pro ). SVV 3C pro mediated the cleavage of MAVS, TRIF, and TANK at specific sites, which required its protease activity. The cleaved MAVS, TRIF, and TANK lost the ability to regulate pattern recognition receptor (PRR)-mediated IFN production. The cleavage of TANK also facilitated TRAF6-induced NF-κB activation. SVV was also found to be sensitive to IFN-β. Therefore, SVV suppressed antiviral IFN production to escape host antiviral innate immune responses by cleaving host adaptor molecules. IMPORTANCE Host cells have developed various defenses against microbial pathogen infection. The production of IFN is the first line of defense against microbial infection. However, viruses have evolved many strategies to disrupt this host defense. SVV, a member of the Picornavirus genus, is an oncolytic virus that shows potential functions in anticancer therapy. It has been demonstrated that IFN can be used in anticancer therapy for certain tumors. However, the relationship between oncolytic virus and innate immune response in anticancer therapy is still not well known. In this study, we showed that SVV has evolved as an effective mechanism to inhibit host type I IFN production by using its 3C pro to cleave the molecules MAVS, TRIF, and TANK directly. These molecules are crucial for

  14. Skb5, an SH3 adaptor protein, regulates Pmk1 MAPK signaling by controlling the intracellular localization of the MAPKKK Mkh1.

    Science.gov (United States)

    Kanda, Yuki; Satoh, Ryosuke; Matsumoto, Saki; Ikeda, Chisato; Inutsuka, Natsumi; Hagihara, Kanako; Matzno, Sumio; Tsujimoto, Sho; Kita, Ayako; Sugiura, Reiko

    2016-08-15

    The mitogen-activated protein kinase (MAPK) cascade is a highly conserved signaling module composed of MAPK kinase kinases (MAPKKKs), MAPK kinases (MAPKK) and MAPKs. The MAPKKK Mkh1 is an initiating kinase in Pmk1 MAPK signaling, which regulates cell integrity in fission yeast (Schizosaccharomyces pombe). Our genetic screen for regulators of Pmk1 signaling identified Shk1 kinase binding protein 5 (Skb5), an SH3-domain-containing adaptor protein. Here, we show that Skb5 serves as an inhibitor of Pmk1 MAPK signaling activation by downregulating Mkh1 localization to cell tips through its interaction with the SH3 domain. Consistent with this, the Mkh1(3PA) mutant protein, with impaired Skb5 binding, remained in the cell tips, even when Skb5 was overproduced. Intriguingly, Skb5 needs Mkh1 to localize to the growing ends as Mkh1 deletion and disruption of Mkh1 binding impairs Skb5 localization. Deletion of Pck2, an upstream activator of Mkh1, impaired the cell tip localization of Mkh1 and Skb5 as well as the Mkh1-Skb5 interaction. Interestingly, both Pck2 and Mkh1 localized to the cell tips at the G1/S phase, which coincided with Pmk1 MAPK activation. Taken together, Mkh1 localization to cell tips is important for transmitting upstream signaling to Pmk1, and Skb5 spatially regulates this process. © 2016. Published by The Company of Biologists Ltd.

  15. Human kidney anion exchanger 1 interacts with adaptor-related protein complex 1 μ1A (AP-1 mu1A)

    International Nuclear Information System (INIS)

    Sawasdee, Nunghathai; Junking, Mutita; Ngaojanlar, Piengpaga; Sukomon, Nattakan; Ungsupravate, Duangporn; Limjindaporn, Thawornchai; Akkarapatumwong, Varaporn; Noisakran, Sansanee; Yenchitsomanus, Pa-thai

    2010-01-01

    Research highlights: → Trafficking defect of kAE1 is a cause of dRTA but trafficking pathway of kAE1 has not been clearly described. → Adaptor-related protein complex 1 μ1A (AP-1 mu1A) was firstly reported to interact with kAE1. → The interacting site for AP-1 mu1A on Ct-kAE1 was found to be Y904DEV907, a subset of YXXO motif. → AP-1 mu1A knockdown showed a marked reduction of kAE1 on the cell membrane and its accumulation in endoplasmic reticulum. → AP-1 mu1A has a critical role in kAE1 trafficking to the plasma membrane. -- Abstract: Kidney anion exchanger 1 (kAE1) mediates chloride (Cl - ) and bicarbonate (HCO 3 - ) exchange at the basolateral membrane of kidney α-intercalated cells. Impaired trafficking of kAE1 leads to defect of the Cl - /HCO 3 - exchange at the basolateral membrane and failure of proton (H + ) secretion at the apical membrane, causing a kidney disease - distal renal tubular acidosis (dRTA). To gain a better insight into kAE1 trafficking, we searched for proteins physically interacting with the C-terminal region of kAE1 (Ct-kAE1), which contains motifs crucial for intracellular trafficking, by a yeast two-hybrid (Y2H) system. An adaptor-related protein complex 1 μ1A (AP-1 mu1A) subunit was found to interact with Ct-kAE1. The interaction between either Ct-kAE1 or full-length kAE1 and AP-1 mu1A were confirmed in human embryonic kidney (HEK) 293T by co-immunoprecipitation, affinity co-purification, co-localization, yellow fluorescent protein (YFP)-based protein fragment complementation assay (PCA) and GST pull-down assay. The interacting site for AP-1 mu1A on Ct-kAE1 was found to be Y904DEV907, a subset of YXXO motif. Interestingly, suppression of endogenous AP-1 mu1A in HEK 293T by small interfering RNA (siRNA) decreased membrane localization of kAE1 and increased its intracellular accumulation, suggesting for the first time that AP-1 mu1A is involved in the kAE1 trafficking of kidney α-intercalated cells.

  16. Evidence against roles for phorbol binding protein Munc13-1, ADAM adaptor Eve-1, or vesicle trafficking phosphoproteins Munc18 or NSF as phospho-state-sensitive modulators of phorbol/PKC-activated Alzheimer APP ectodomain shedding

    Directory of Open Access Journals (Sweden)

    Lovestone Simon

    2007-12-01

    Full Text Available Abstract Background Shedding of the Alzheimer amyloid precursor protein (APP ectodomain can be accelerated by phorbol esters, compounds that act via protein kinase C (PKC or through unconventional phorbol-binding proteins such as Munc13-1. We have previously demonstrated that application of phorbol esters or purified PKC potentiates budding of APP-bearing secretory vesicles at the trans-Golgi network (TGN and toward the plasma membrane where APP becomes a substrate for enzymes responsible for shedding, known collectively as α-secretase(s. However, molecular identification of the presumptive "phospho-state-sensitive modulators of ectodomain shedding" (PMES responsible for regulated shedding has been challenging. Here, we examined the effects on APP ectodomain shedding of four phorbol-sensitive proteins involved in regulation of vesicular membrane trafficking of APP: Munc13-1, Munc18, NSF, and Eve-1. Results Overexpression of either phorbol-sensitive wildtype Munc13-1 or phorbol-insensitive Munc13-1 H567K resulted in increased basal APP ectodomain shedding. However, in contrast to the report of Roßner et al (2004, phorbol ester-dependent APP ectodomain shedding from cells overexpressing APP and Munc13-1 wildtype was indistinguishable from that observed following application of phorbol to cells overexpressing APP and Munc13-1 H567K mutant. This pattern of similar effects on basal and stimulated APP shedding was also observed for Munc18 and NSF. Eve-1, an ADAM adaptor protein reported to be essential for PKC-regulated shedding of pro-EGF, was found to play no obvious role in regulated shedding of sAPPα. Conclusion Our results indicate that, in the HEK293 system, Munc13-1, Munc18, NSF, and EVE-1 fail to meet essential criteria for identity as PMES for APP.

  17. Evidence against roles for phorbol binding protein Munc13-1, ADAM adaptor Eve-1, or vesicle trafficking phosphoproteins Munc18 or NSF as phospho-state-sensitive modulators of phorbol/PKC-activated Alzheimer APP ectodomain shedding.

    Science.gov (United States)

    Ikin, Annat F; Causevic, Mirsada; Pedrini, Steve; Benson, Lyndsey S; Buxbaum, Joseph D; Suzuki, Toshiharu; Lovestone, Simon; Higashiyama, Shigeki; Mustelin, Tomas; Burgoyne, Robert D; Gandy, Sam

    2007-12-09

    Shedding of the Alzheimer amyloid precursor protein (APP) ectodomain can be accelerated by phorbol esters, compounds that act via protein kinase C (PKC) or through unconventional phorbol-binding proteins such as Munc13-1. We have previously demonstrated that application of phorbol esters or purified PKC potentiates budding of APP-bearing secretory vesicles at the trans-Golgi network (TGN) and toward the plasma membrane where APP becomes a substrate for enzymes responsible for shedding, known collectively as alpha-secretase(s). However, molecular identification of the presumptive "phospho-state-sensitive modulators of ectodomain shedding" (PMES) responsible for regulated shedding has been challenging. Here, we examined the effects on APP ectodomain shedding of four phorbol-sensitive proteins involved in regulation of vesicular membrane trafficking of APP: Munc13-1, Munc18, NSF, and Eve-1. Overexpression of either phorbol-sensitive wildtype Munc13-1 or phorbol-insensitive Munc13-1 H567K resulted in increased basal APP ectodomain shedding. However, in contrast to the report of Rossner et al (2004), phorbol ester-dependent APP ectodomain shedding from cells overexpressing APP and Munc13-1 wildtype was indistinguishable from that observed following application of phorbol to cells overexpressing APP and Munc13-1 H567K mutant. This pattern of similar effects on basal and stimulated APP shedding was also observed for Munc18 and NSF. Eve-1, an ADAM adaptor protein reported to be essential for PKC-regulated shedding of pro-EGF, was found to play no obvious role in regulated shedding of sAPPalpha. Our results indicate that, in the HEK293 system, Munc13-1, Munc18, NSF, and EVE-1 fail to meet essential criteria for identity as PMES for APP.

  18. Signal-transducing adaptor protein-2 promotes generation of functional long-term memory CD8+ T cells by preventing terminal effector differentiation.

    Science.gov (United States)

    Muraoka, Daisuke; Seo, Naohiro; Hayashi, Tae; Hyuga-Amaike, Chisaki; Okamori, Kana; Tawara, Isao; Harada, Naozumi; Shiku, Hiroshi

    2017-05-09

    Long-surviving memory CD8+ T cells generated by stimulation with appropriate tumor-associated antigens are the most aggressive and persistent tumoricidal effectors. In this event of memory CD8+ T cell development, the signal transducer and activator of transcription (STAT) proteins function as the crucial intracellular signaling molecules, but the regulatory mechanism of STATs in CD8+ T cells is not fully understood. In this study, we report for the first time, by using murine vaccination models, that signal-transducing adaptor protein-2 (STAP2) maintains the cytotoxicity of long-lived memory CD8+ T cells by controlling a STAT3/suppressor of cytokine signaling 3 (SOCS3) cascade. Following T cell activation, STAP2 expression was transiently reduced but was subsequently recovered and augmented. Analysis using small-interfering RNA (siRNA) demonstrated that restored STAP2 expression was associated with the activation of STAT3/SOCS3 signals and maintenance of cytotoxic T lymphocytes (CTLs) secondary responses by preventing their differentiation into terminal effector cells. Notably, this STAP2-dependent memory differentiation was observed in the spleen, but not in the lymph nodes (LNs). These findings indicate an essential role for STAP2 in the generation of a high-quality memory CD8+ CTLs periphery, and suggest the therapeutic potential of STAP2 in cancer patients.

  19. The adaptor-like protein ROG-1 is required for activation of the Ras-MAP kinase pathway and meiotic cell cycle progression in Caenorhabditis elegans.

    Science.gov (United States)

    Matsubara, Yosuke; Kawasaki, Ichiro; Urushiyama, Seiichi; Yasuda, Tomoharu; Shirakata, Masaki; Iino, Yuichi; Shibuya, Hiroshi; Yamanashi, Yuji

    2007-03-01

    The Ras-MAP kinase pathway regulates varieties of fundamental cellular events. In Caenorhabditis elegans, this pathway is required for oocyte development; however, the nature of its up-stream regulators has remained elusive. Here, we identified a C. elegans gene, rog-1, which encodes the only protein having the IRS-type phosphotyrosine-binding (PTB) domain in the worms. ROG-1 has no obvious domain structure aside from the PTB domain, suggesting that it could serve as an adaptor down-stream of protein-tyrosine kinases (PTKs). RNA interference (RNAi)-mediated down-regulation of rog-1 mRNA significantly decreased brood size. rog-1(tm1031) truncation mutants showed a severe disruption in progression of developing oocytes from pachytene to diakinesis, as was seen in worms carrying a loss-of-function mutation in the let-60 Ras or mpk-1 MAP kinase gene. Furthermore, let-60 Ras-regulated activation of MPK-1 in the gonad is undetectable in rog-1(tm1031) mutants. Conversely, a gain-of-function mutation in the let-60 Ras gene rescues the brood size reduction and germ cell abnormality in rog-1(tm1031) worms. Consistently, rog-1 is preferentially expressed in the germ cells and its expression in the gonad is essential for oocyte development. Thus, ROG-1 is a key positive regulator of the Ras-MAP kinase pathway that permits germ cells to exit from pachytene.

  20. Disruption of the podosome adaptor protein TKS4 (SH3PXD2B) causes the skeletal dysplasia, eye, and cardiac abnormalities of Frank-Ter Haar Syndrome.

    Science.gov (United States)

    Iqbal, Zafar; Cejudo-Martin, Pilar; de Brouwer, Arjan; van der Zwaag, Bert; Ruiz-Lozano, Pilar; Scimia, M Cecilia; Lindsey, James D; Weinreb, Robert; Albrecht, Beate; Megarbane, Andre; Alanay, Yasemin; Ben-Neriah, Ziva; Amenduni, Mariangela; Artuso, Rosangela; Veltman, Joris A; van Beusekom, Ellen; Oudakker, Astrid; Millán, José Luis; Hennekam, Raoul; Hamel, Ben; Courtneidge, Sara A; van Bokhoven, Hans

    2010-02-12

    Frank-Ter Haar syndrome (FTHS), also known as Ter Haar syndrome, is an autosomal-recessive disorder characterized by skeletal, cardiovascular, and eye abnormalities, such as increased intraocular pressure, prominent eyes, and hypertelorism. We have conducted homozygosity mapping on patients representing 12 FTHS families. A locus on chromosome 5q35.1 was identified for which patients from nine families shared homozygosity. For one family, a homozygous deletion mapped exactly to the smallest region of overlapping homozygosity, which contains a single gene, SH3PXD2B. This gene encodes the TKS4 protein, a phox homology (PX) and Src homology 3 (SH3) domain-containing adaptor protein and Src substrate. This protein was recently shown to be involved in the formation of actin-rich membrane protrusions called podosomes or invadopodia, which coordinate pericellular proteolysis with cell migration. Mice lacking Tks4 also showed pronounced skeletal, eye, and cardiac abnormalities and phenocopied the majority of the defects associated with FTHS. These findings establish a role for TKS4 in FTHS and embryonic development. Mutation analysis revealed five different homozygous mutations in SH3PXD2B in seven FTHS families. No SH3PXD2B mutations were detected in six other FTHS families, demonstrating the genetic heterogeneity of this condition. Interestingly however, dermal fibroblasts from one of the individuals without an SH3PXD2B mutation nevertheless expressed lower levels of the TKS4 protein, suggesting a common mechanism underlying disease causation. Copyright (c) 2010 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

  1. Identification of Atg2 and ArfGAP1 as Candidate Genetic Modifiers of the Eye Pigmentation Phenotype of Adaptor Protein-3 (AP-3) Mutants in Drosophila melanogaster.

    Science.gov (United States)

    Rodriguez-Fernandez, Imilce A; Dell'Angelica, Esteban C

    2015-01-01

    The Adaptor Protein (AP)-3 complex is an evolutionary conserved, molecular sorting device that mediates the intracellular trafficking of proteins to lysosomes and related organelles. Genetic defects in AP-3 subunits lead to impaired biogenesis of lysosome-related organelles (LROs) such as mammalian melanosomes and insect eye pigment granules. In this work, we have performed a forward screening for genetic modifiers of AP-3 function in the fruit fly, Drosophila melanogaster. Specifically, we have tested collections of large multi-gene deletions--which together covered most of the autosomal chromosomes-to identify chromosomal regions that, when deleted in single copy, enhanced or ameliorated the eye pigmentation phenotype of two independent AP-3 subunit mutants. Fine-mapping led us to define two non-overlapping, relatively small critical regions within fly chromosome 3. The first critical region included the Atg2 gene, which encodes a conserved protein involved in autophagy. Loss of one functional copy of Atg2 ameliorated the pigmentation defects of mutants in AP-3 subunits as well as in two other genes previously implicated in LRO biogenesis, namely Blos1 and lightoid, and even increased the eye pigment content of wild-type flies. The second critical region included the ArfGAP1 gene, which encodes a conserved GTPase-activating protein with specificity towards GTPases of the Arf family. Loss of a single functional copy of the ArfGAP1 gene ameliorated the pigmentation phenotype of AP-3 mutants but did not to modify the eye pigmentation of wild-type flies or mutants in Blos1 or lightoid. Strikingly, loss of the second functional copy of the gene did not modify the phenotype of AP-3 mutants any further but elicited early lethality in males and abnormal eye morphology when combined with mutations in Blos1 and lightoid, respectively. These results provide genetic evidence for new functional links connecting the machinery for biogenesis of LROs with molecules implicated in

  2. The Adaptor Protein p62 Mediates Nuclear Factor κB Activation in Response to Inflammation and Facilitates the Formation of Prolabor Mediators in Human Myometrium.

    Science.gov (United States)

    Lappas, Martha

    2017-05-01

    Preventing spontaneous preterm birth is one of the most important issues facing perinatal medicine today. The pathophysiology of preterm labor, the single biggest cause of preterm birth, is poorly understood. Inflammation, however, plays a significant role in the terminal processes of human labor, which include myometrial contractions. Nuclear factor κB (NF-κB) drives the transcription of proinflammatory mediators involved in the terminal effector pathways of human labor and delivery. Recent studies in nongestational tissues have shown that the adaptor protein p62 interacts with NF-κB to induce inflammation. The aim of this study was to determine the role of p62 in the genesis of NF-κB-induced proinflammatory and prolabur mediators. Human spontaneous term labor was associated with increased p62 messenger RNA (mRNA) and protein expression in myometrium. Myometrial cells treated with proinflammatory cytokines interleukin 1β (IL-1β) and tumor necrosis factor alpha (TNF-α) also significantly increased p62 mRNA and protein expression. Functional studies using p62 small interfering RNA (siRNA) demonstrated a significant attenuation of TNF-α- and IL-1β-induced proinflammatory cytokines (IL-6) and chemokine (IL-8 and monocyte chemoattractant protein 1 [MCP-1]) mRNA expression and secretion, expression of cyclooxygenase 2, release of prostaglandin F 2α (PGF 2α ), and expression of the prostaglandin F receptor (FP). In addition, siRNA knockdown of p62 significantly suppressed IL-1β- and TNF-α-induced NF-κB activation. Collectively, these studies suggest that p62 is involved in the genesis of NF-κB-induced proinflammatory and prolabor mediators.

  3. The adaptor protein SAP directly associates with PECAM-1 and regulates PECAM-1-mediated-cell adhesion in T-like cell lines.

    Science.gov (United States)

    Proust, Richard; Crouin, Catherine; Gandji, Leslie Yewakon; Bertoglio, Jacques; Gesbert, Franck

    2014-04-01

    SAP is a small cytosolic adaptor protein expressed in hematopoietic lineages whose main function is to regulate intracellular signaling pathways induced by the triggering of members of the SLAM receptor family. In this paper, we have identified the adhesion molecule PECAM-1 as a new partner for SAP in a conditional yeast two-hybrid screen. PECAM-1 is an immunoglobulin-like molecule expressed by endothelial cells and leukocytes, which possesses both pro- and anti-inflammatory properties. However, little is known about PECAM-1 functions in T cells. We show that SAP directly and specifically interacts with the cytosolic tyrosine 686 of PECAM-1. We generated different T-like cell lines in which SAP or PECAM-1 are expressed or down modulated and we demonstrate that a diminished SAP expression correlates with a diminished PECAM-1-mediated adhesion. Although SAP has mainly been shown to associate with SLAM receptors, we evidence here that SAP is a new actor downstream of PECAM-1. Copyright © 2013 Elsevier Ltd. All rights reserved.

  4. Loss of the adaptor protein ShcA in endothelial cells protects against monocyte macrophage adhesion, LDL-oxydation, and atherosclerotic lesion formation.

    Science.gov (United States)

    Jaoude, Antoine Abou; Badiqué, Lise; Mlih, Mohamed; Awan, Sara; Guo, Sunning; Lemle, Alexandre; Abboud, Clauda; Foppolo, Sophie; Host, Lionel; Terrand, Jérôme; Justiniano, Hélène; Herz, Joachim; Matz, Rachel L; Boucher, Philippe

    2018-03-14

    ShcA is an adaptor protein that binds to the cytoplasmic tail of receptor tyrosine kinases and of the Low Density Lipoprotein-related receptor 1 (LRP1), a trans-membrane receptor that protects against atherosclerosis. Here, we examined the role of endothelial ShcA in atherosclerotic lesion formation. We found that atherosclerosis progression was markedly attenuated in mice deleted for ShcA in endothelial cells, that macrophage content was reduced at the sites of lesions, and that adhesion molecules such as the intercellular adhesion molecule-1 (ICAM-1) were severely reduced. Our data indicate that transcriptional regulation of ShcA by the zinc-finger E-box-binding homeobox 1 (ZEB1) and the Hippo pathway effector YAP, promotes ICAM-1 expression independently of p-NF-κB, the primary driver of adhesion molecules expressions. In addition, ShcA suppresses endothelial Akt and nitric oxide synthase (eNOS) expressions. Thus, through down regulation of eNOS and ZEB1-mediated ICAM-1 up regulation, endothelial ShcA promotes monocyte-macrophage adhesion and atherosclerotic lesion formation. Reducing ShcA expression in endothelial cells may represent an obvious therapeutic approach to prevent atherosclerosis.

  5. A role for cargo in Arf-dependent adaptor recruitment.

    Science.gov (United States)

    Caster, Amanda H; Sztul, Elizabeth; Kahn, Richard A

    2013-05-24

    Membrane traffic requires the specific concentration of protein cargos and exclusion of other proteins into nascent carriers. Critical components of this selectivity are the protein adaptors that bind to short, linear motifs in the cytoplasmic tails of transmembrane protein cargos and sequester them into nascent carriers. The recruitment of the adaptors is mediated by activated Arf GTPases, and the Arf-adaptor complexes mark sites of carrier formation. However, the nature of the signal(s) that initiates carrier biogenesis remains unknown. We examined the specificity and initial sites of recruitment of Arf-dependent adaptors (AP-1 and GGAs) in response to the Golgi or endosomal localization of specific cargo proteins (furin, mannose-6-phosphate receptor (M6PR), and M6PR lacking a C-terminal domain M6PRΔC). We find that cargo promotes the recruitment of specific adaptors, suggesting that it is part of an upstream signaling event. Cargos do not promote adaptor recruitment to all compartments in which they reside, and thus additional factors regulate the cargo's ability to promote Arf activation and adaptor recruitment. We document that within a given compartment different cargos recruit different adaptors, suggesting that there is little or no free, activated Arf at the membrane and that Arf activation is spatially and temporally coupled to the cargo and the adaptor. Using temperature block, brefeldin A, and recovery from each, we found that the cytoplasmic tail of M6PR causes the recruitment of AP-1 and GGAs to recycling endosomes and not at the Golgi, as predicted by steady state staining profiles. These results are discussed with respect to the generation of novel models for cargo-dependent regulation of membrane traffic.

  6. A Role for Cargo in Arf-dependent Adaptor Recruitment*

    Science.gov (United States)

    Caster, Amanda H.; Sztul, Elizabeth; Kahn, Richard A.

    2013-01-01

    Membrane traffic requires the specific concentration of protein cargos and exclusion of other proteins into nascent carriers. Critical components of this selectivity are the protein adaptors that bind to short, linear motifs in the cytoplasmic tails of transmembrane protein cargos and sequester them into nascent carriers. The recruitment of the adaptors is mediated by activated Arf GTPases, and the Arf-adaptor complexes mark sites of carrier formation. However, the nature of the signal(s) that initiates carrier biogenesis remains unknown. We examined the specificity and initial sites of recruitment of Arf-dependent adaptors (AP-1 and GGAs) in response to the Golgi or endosomal localization of specific cargo proteins (furin, mannose-6-phosphate receptor (M6PR), and M6PR lacking a C-terminal domain M6PRΔC). We find that cargo promotes the recruitment of specific adaptors, suggesting that it is part of an upstream signaling event. Cargos do not promote adaptor recruitment to all compartments in which they reside, and thus additional factors regulate the cargo's ability to promote Arf activation and adaptor recruitment. We document that within a given compartment different cargos recruit different adaptors, suggesting that there is little or no free, activated Arf at the membrane and that Arf activation is spatially and temporally coupled to the cargo and the adaptor. Using temperature block, brefeldin A, and recovery from each, we found that the cytoplasmic tail of M6PR causes the recruitment of AP-1 and GGAs to recycling endosomes and not at the Golgi, as predicted by steady state staining profiles. These results are discussed with respect to the generation of novel models for cargo-dependent regulation of membrane traffic. PMID:23572528

  7. Interplays between Sumoylation, SUMO-Targeted Ubiquitin Ligases, and the Ubiquitin-Adaptor Protein Ufd1 in Fission Yeast

    DEFF Research Database (Denmark)

    Køhler, Julie Bonne

    their conformation or interactions with other macromolecules. Though, whereas the downstream consequence of ubiquitin conjugation is often protein degradation, the functional outcomes of sumoylation are less unifiable. A class of ubiquitin E3 ligases able to target sumoylated proteins for degradation by the 26S...... proteasome mediates direct cross-talk between the two modification systems. By contributing to the dynamic turnover of SUMO conjugated species these SUMO-targeted ubiquitin ligases (STUbLs) fulfills essential roles in both yeast and man. However, the specific sumoylated proteins affected by STUbL activity...... and the specific molecular interactions and sequence of events linking sumoylation, ubiquitylation and substrate degradation, has been largely uncovered. Using the fission yeast model organism I here present evidence for a role of the Ufd1 (ubiquitinfusion degradation 1) protein, and by extension of the Cdc48-Ufd1...

  8. A screen for E3 ubiquitination ligases that genetically interact with the adaptor protein Cindr during Drosophila eye patterning.

    Science.gov (United States)

    Ketosugbo, Kwami F; Bushnell, Henry L; Johnson, Ruth I

    2017-01-01

    Ubiquitination is a crucial post-translational modification that can target proteins for degradation. The E3 ubiquitin ligases are responsible for recognizing substrate proteins for ubiquitination, hence providing specificity to the process of protein degradation. Here, we describe a genetic modifier screen that identified E3 ligases that modified the rough-eye phenotype generated by expression of cindrRNAi transgenes during Drosophila eye development. In total, we identified 36 E3 ligases, as well as 4 Cullins, that modified the mild cindrRNA mis-patterning phenotype. This indicates possible roles for these E3s/Cullins in processes that require Cindr function, including cytoskeletal regulation, cell adhesion, cell signaling and cell survival. Three E3 ligases identified in our screen had previously been linked to regulating JNK signaling.

  9. The Pseudomonas aeruginosa lectin LecA triggers host cell signalling by glycosphingolipid-dependent phosphorylation of the adaptor protein CrkII.

    Science.gov (United States)

    Zheng, Shuangshuang; Eierhoff, Thorsten; Aigal, Sahaja; Brandel, Annette; Thuenauer, Roland; de Bentzmann, Sophie; Imberty, Anne; Römer, Winfried

    2017-07-01

    The human pathogen Pseudomonas aeruginosa induces phosphorylation of the adaptor protein CrkII by activating the non-receptor tyrosine kinase Abl to promote its uptake into host cells. So far, specific factors of P. aeruginosa, which induce Abl/CrkII signalling, are entirely unknown. In this research, we employed human lung epithelial cells H1299, Chinese hamster ovary cells and P. aeruginosa wild type strain PAO1 to study the invasion process of P. aeruginosa into host cells by using microbiological, biochemical and cell biological approaches such as Western Blot, immunofluorescence microscopy and flow cytometry. Here, we demonstrate that the host glycosphingolipid globotriaosylceramide, also termed Gb3, represents a signalling receptor for the P. aeruginosa lectin LecA to induce CrkII phosphorylation at tyrosine 221. Alterations in Gb3 expression and LecA function correlate with CrkII phosphorylation. Interestingly, phosphorylation of CrkII Y221 occurs independently of Abl kinase. We further show that Src family kinases transduce the signal induced by LecA binding to Gb3, leading to Crk Y221 phosphorylation. In summary, we identified LecA as a bacterial factor, which utilizes a so far unrecognized mechanism for phospho-CrkII Y221 induction by binding to the host glycosphingolipid receptor Gb3. The LecA/Gb3 interaction highlights the potential of glycolipids to mediate signalling processes across the plasma membrane and should be further elucidated to gain deeper insights into this non-canonical mechanism of activating host cell processes. Copyright © 2017 Elsevier B.V. All rights reserved.

  10. Identification of Atg2 and ArfGAP1 as Candidate Genetic Modifiers of the Eye Pigmentation Phenotype of Adaptor Protein-3 (AP-3 Mutants in Drosophila melanogaster.

    Directory of Open Access Journals (Sweden)

    Imilce A Rodriguez-Fernandez

    Full Text Available The Adaptor Protein (AP-3 complex is an evolutionary conserved, molecular sorting device that mediates the intracellular trafficking of proteins to lysosomes and related organelles. Genetic defects in AP-3 subunits lead to impaired biogenesis of lysosome-related organelles (LROs such as mammalian melanosomes and insect eye pigment granules. In this work, we have performed a forward screening for genetic modifiers of AP-3 function in the fruit fly, Drosophila melanogaster. Specifically, we have tested collections of large multi-gene deletions--which together covered most of the autosomal chromosomes-to identify chromosomal regions that, when deleted in single copy, enhanced or ameliorated the eye pigmentation phenotype of two independent AP-3 subunit mutants. Fine-mapping led us to define two non-overlapping, relatively small critical regions within fly chromosome 3. The first critical region included the Atg2 gene, which encodes a conserved protein involved in autophagy. Loss of one functional copy of Atg2 ameliorated the pigmentation defects of mutants in AP-3 subunits as well as in two other genes previously implicated in LRO biogenesis, namely Blos1 and lightoid, and even increased the eye pigment content of wild-type flies. The second critical region included the ArfGAP1 gene, which encodes a conserved GTPase-activating protein with specificity towards GTPases of the Arf family. Loss of a single functional copy of the ArfGAP1 gene ameliorated the pigmentation phenotype of AP-3 mutants but did not to modify the eye pigmentation of wild-type flies or mutants in Blos1 or lightoid. Strikingly, loss of the second functional copy of the gene did not modify the phenotype of AP-3 mutants any further but elicited early lethality in males and abnormal eye morphology when combined with mutations in Blos1 and lightoid, respectively. These results provide genetic evidence for new functional links connecting the machinery for biogenesis of LROs with

  11. The adaptor protein SAP regulates type II NKT-cell development, cytokine production, and cytotoxicity against lymphoma.

    Science.gov (United States)

    Weng, Xiufang; Liao, Chia-Min; Bagchi, Sreya; Cardell, Susanna L; Stein, Paul L; Wang, Chyung-Ru

    2014-12-01

    CD1d-restricted NKT cells represent a unique lineage of immunoregulatory T cells that are divided into two groups, type I and type II, based on their TCR usage. Because there are no specific tools to identify type II NKT cells, little is known about their developmental requirements and functional regulation. In our previous study, we showed that signaling lymphocytic activation molecule associated protein (SAP) is essential for the development of type II NKT cells. Here, using a type II NKT-cell TCR transgenic mouse model, we demonstrated that CD1d-expressing hematopoietic cells, but not thymic epithelial cells, meditate efficient selection of type II NKT cells. Furthermore, we showed that SAP regulates type II NKT-cell development by controlling early growth response 2 protein and promyelocytic leukemia zinc finger expression. SAP-deficient 24αβ transgenic T cells (24αβ T cells) exhibited an immature phenotype with reduced Th2 cytokine-producing capacity and diminished cytotoxicity to CD1d-expressing lymphoma cells. The impaired IL-4 production by SAP-deficient 24αβ T cells was associated with reduced IFN regulatory factor 4 and GATA-3 induction following TCR stimulation. Collectively, these data suggest that SAP is critical for regulating type II NKT cell responses. Aberrant responses of these T cells may contribute to the immune dysregulation observed in X-linked lymphoproliferative disease caused by mutations in SAP. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  12. Spectral affinity in protein networks.

    Science.gov (United States)

    Voevodski, Konstantin; Teng, Shang-Hua; Xia, Yu

    2009-11-29

    Protein-protein interaction (PPI) networks enable us to better understand the functional organization of the proteome. We can learn a lot about a particular protein by querying its neighborhood in a PPI network to find proteins with similar function. A spectral approach that considers random walks between nodes of interest is particularly useful in evaluating closeness in PPI networks. Spectral measures of closeness are more robust to noise in the data and are more precise than simpler methods based on edge density and shortest path length. We develop a novel affinity measure for pairs of proteins in PPI networks, which uses personalized PageRank, a random walk based method used in context-sensitive search on the Web. Our measure of closeness, which we call PageRank Affinity, is proportional to the number of times the smaller-degree protein is visited in a random walk that restarts at the larger-degree protein. PageRank considers paths of all lengths in a network, therefore PageRank Affinity is a precise measure that is robust to noise in the data. PageRank Affinity is also provably related to cluster co-membership, making it a meaningful measure. In our experiments on protein networks we find that our measure is better at predicting co-complex membership and finding functionally related proteins than other commonly used measures of closeness. Moreover, our experiments indicate that PageRank Affinity is very resilient to noise in the network. In addition, based on our method we build a tool that quickly finds nodes closest to a queried protein in any protein network, and easily scales to much larger biological networks. We define a meaningful way to assess the closeness of two proteins in a PPI network, and show that our closeness measure is more biologically significant than other commonly used methods. We also develop a tool, accessible at http://xialab.bu.edu/resources/pnns, that allows the user to quickly find nodes closest to a queried vertex in any protein

  13. Spectral affinity in protein networks

    Directory of Open Access Journals (Sweden)

    Teng Shang-Hua

    2009-11-01

    Full Text Available Abstract Background Protein-protein interaction (PPI networks enable us to better understand the functional organization of the proteome. We can learn a lot about a particular protein by querying its neighborhood in a PPI network to find proteins with similar function. A spectral approach that considers random walks between nodes of interest is particularly useful in evaluating closeness in PPI networks. Spectral measures of closeness are more robust to noise in the data and are more precise than simpler methods based on edge density and shortest path length. Results We develop a novel affinity measure for pairs of proteins in PPI networks, which uses personalized PageRank, a random walk based method used in context-sensitive search on the Web. Our measure of closeness, which we call PageRank Affinity, is proportional to the number of times the smaller-degree protein is visited in a random walk that restarts at the larger-degree protein. PageRank considers paths of all lengths in a network, therefore PageRank Affinity is a precise measure that is robust to noise in the data. PageRank Affinity is also provably related to cluster co-membership, making it a meaningful measure. In our experiments on protein networks we find that our measure is better at predicting co-complex membership and finding functionally related proteins than other commonly used measures of closeness. Moreover, our experiments indicate that PageRank Affinity is very resilient to noise in the network. In addition, based on our method we build a tool that quickly finds nodes closest to a queried protein in any protein network, and easily scales to much larger biological networks. Conclusion We define a meaningful way to assess the closeness of two proteins in a PPI network, and show that our closeness measure is more biologically significant than other commonly used methods. We also develop a tool, accessible at http://xialab.bu.edu/resources/pnns, that allows the user to

  14. The Adaptor Protein SAP Regulates Type II NKT Cell Development, Cytokine Production and Cytotoxicity Against Lymphoma1

    Science.gov (United States)

    Weng, Xiufang; Liao, Chia-Min; Bagchi, Sreya; Cardell, Susanna L.; Stein, Paul L.; Wang, Chyung-Ru

    2014-01-01

    CD1d-restricted NKT cells represent a unique lineage of immunoregulatory T cells that are divided into two groups, type I and type II, based on their TCR usage. Because there are no specific tools to identify type II NKT cells, little is known about their developmental requirements and functional regulation. In our previous study, we showed that signaling lymphocytic activation molecule-associated protein (SAP) is essential for the development of type II NKT cells. Here, using a type II NKT cell TCR transgenic mouse model (24αβTg), we demonstrated that CD1d-expressing hematopoietic cells but not thymic epithelial cells meditate efficient selection of type II NKT cells. Further, we showed that SAP regulates type II NKT cell development by controlling Egr2 and PLZF expression. SAP-deficient 24αβ transgenic T cells (24αβ T cells) exhibited an immature phenotype with reduced Th2 cytokine-producing capacity and diminished cytotoxicity to CD1d-expressing lymphoma cells. The impaired IL-4 production by SAP-deficient 24αβ T cells was associated with reduced IRF4 and GATA-3 induction following TCR stimulation. Collectively, these data suggest that SAP is critical for regulating type II NKT cell responses. Aberrant responses of these T cells may contribute to the immune dysregulation observed in X-linked lymphoproliferative disease caused by mutations in SAP. PMID:25236978

  15. MyD88 Adaptor Protein Is Required for Appropriate Hepcidin Induction in Response to Dietary Iron Overload in Mice

    Directory of Open Access Journals (Sweden)

    Antonio Layoun

    2018-03-01

    Full Text Available Iron homeostasis is tightly regulated to provide virtually all cells in the body, particularly red blood cells, with this essential element while defending against its toxicity. The peptide hormone hepcidin is central to the control of the amount of iron absorbed from the diet and iron recycling from macrophages. Previously, we have shown that hepcidin induction in macrophages following Toll-like receptor (TLR stimulation depends on the presence of myeloid differentiation primary response gene 88 (MyD88. In this study, we analyzed the regulation of iron metabolism in MyD88−/− mice to further investigate MyD88 involvement in iron sensing and hepcidin induction. We show that mice lacking MyD88 accumulate significantly more iron in their livers than wild-type counterparts in response to dietary iron loading as they are unable to appropriately control hepcidin levels. The defect was associated with inappropriately low levels of Smad4 protein and Smad1/5/8 phosphorylation in liver samples found in the MyD88−/− mice compared to wild-type mice. In conclusion, our results reveal a previously unknown link between MyD88 and iron homeostasis, and provide new insights into the regulation of hepcidin through the iron-sensing pathway.

  16. The Arabidopsis adaptor protein AP-3µ interacts with the G-protein β subunit AGB1 and is involved in abscisic acid regulation of germination and post-germination development

    Science.gov (United States)

    Tsugama, Daisuke; Takano, Tetsuo

    2013-01-01

    Heterotrimeric G-proteins (G-proteins) have been implicated in ubiquitous signalling mechanisms in eukaryotes. In plants, G-proteins modulate hormonal and stress responses and regulate diverse developmental processes. However, the molecular mechanisms of their functions are largely unknown. A yeast two-hybrid screen was performed to identify interacting partners of the Arabidopsis G-protein β subunit AGB1. One of the identified AGB1-interacting proteins is the Arabidopsis adaptor protein AP-3µ. The interaction between AGB1 and AP-3µ was confirmed by an in vitro pull-down assay and bimolecular fluorescence complementation assay. Two ap-3µ T-DNA insertional mutants were found to be hyposensitive to abscisic acid (ABA) during germination and post-germination growth, whereas agb1 mutants were hypersensitive to ABA. During seed germination, agb1/ap-3µ double mutants were more sensitive to ABA than the wild type but less sensitive than agb1 mutants. However, in post-germination growth, the double mutants were as sensitive to ABA as agb1 mutants. These data suggest that AP-3µ positively regulates the ABA responses independently of AGB1 in seed germination, while AP-3µ does require AGB1 to regulate ABA responses during post-germination growth. PMID:24098050

  17. Structural analysis of intermolecular interactions in the kinesin adaptor complex fasciculation and elongation protein zeta 1/ short coiled-coil protein (FEZ1/SCOCO.

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    Marcos Rodrigo Alborghetti

    Full Text Available Cytoskeleton and protein trafficking processes, including vesicle transport to synapses, are key processes in neuronal differentiation and axon outgrowth. The human protein FEZ1 (fasciculation and elongation protein zeta 1 / UNC-76, in C. elegans, SCOCO (short coiled-coil protein / UNC-69 and kinesins (e.g. kinesin heavy chain / UNC116 are involved in these processes. Exploiting the feature of FEZ1 protein as a bivalent adapter of transport mediated by kinesins and FEZ1 protein interaction with SCOCO (proteins involved in the same path of axonal growth, we investigated the structural aspects of intermolecular interactions involved in this complex formation by NMR (Nuclear Magnetic Resonance, cross-linking coupled with mass spectrometry (MS, SAXS (Small Angle X-ray Scattering and molecular modelling. The topology of homodimerization was accessed through NMR (Nuclear Magnetic Resonance studies of the region involved in this process, corresponding to FEZ1 (92-194. Through studies involving the protein in its monomeric configuration (reduced and dimeric state, we propose that homodimerization occurs with FEZ1 chains oriented in an anti-parallel topology. We demonstrate that the interaction interface of FEZ1 and SCOCO defined by MS and computational modelling is in accordance with that previously demonstrated for UNC-76 and UNC-69. SAXS and literature data support a heterotetrameric complex model. These data provide details about the interaction interfaces probably involved in the transport machinery assembly and open perspectives to understand and interfere in this assembly and its involvement in neuronal differentiation and axon outgrowth.

  18. Oligomeric protein structure networks: insights into protein-protein interactions

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    Brinda KV

    2005-12-01

    Full Text Available Abstract Background Protein-protein association is essential for a variety of cellular processes and hence a large number of investigations are being carried out to understand the principles of protein-protein interactions. In this study, oligomeric protein structures are viewed from a network perspective to obtain new insights into protein association. Structure graphs of proteins have been constructed from a non-redundant set of protein oligomer crystal structures by considering amino acid residues as nodes and the edges are based on the strength of the non-covalent interactions between the residues. The analysis of such networks has been carried out in terms of amino acid clusters and hubs (highly connected residues with special emphasis to protein interfaces. Results A variety of interactions such as hydrogen bond, salt bridges, aromatic and hydrophobic interactions, which occur at the interfaces are identified in a consolidated manner as amino acid clusters at the interface, from this study. Moreover, the characterization of the highly connected hub-forming residues at the interfaces and their comparison with the hubs from the non-interface regions and the non-hubs in the interface regions show that there is a predominance of charged interactions at the interfaces. Further, strong and weak interfaces are identified on the basis of the interaction strength between amino acid residues and the sizes of the interface clusters, which also show that many protein interfaces are stronger than their monomeric protein cores. The interface strengths evaluated based on the interface clusters and hubs also correlate well with experimentally determined dissociation constants for known complexes. Finally, the interface hubs identified using the present method correlate very well with experimentally determined hotspots in the interfaces of protein complexes obtained from the Alanine Scanning Energetics database (ASEdb. A few predictions of interface hot

  19. Vaccinia virus protein C6 is a virulence factor that binds TBK-1 adaptor proteins and inhibits activation of IRF3 and IRF7.

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    Leonie Unterholzner

    2011-09-01

    Full Text Available Recognition of viruses by pattern recognition receptors (PRRs causes interferon-β (IFN-β induction, a key event in the anti-viral innate immune response, and also a target of viral immune evasion. Here the vaccinia virus (VACV protein C6 is identified as an inhibitor of PRR-induced IFN-β expression by a functional screen of select VACV open reading frames expressed individually in mammalian cells. C6 is a member of a family of Bcl-2-like poxvirus proteins, many of which have been shown to inhibit innate immune signalling pathways. PRRs activate both NF-κB and IFN regulatory factors (IRFs to activate the IFN-β promoter induction. Data presented here show that C6 inhibits IRF3 activation and translocation into the nucleus, but does not inhibit NF-κB activation. C6 inhibits IRF3 and IRF7 activation downstream of the kinases TANK binding kinase 1 (TBK1 and IκB kinase-ε (IKKε, which phosphorylate and activate these IRFs. However, C6 does not inhibit TBK1- and IKKε-independent IRF7 activation or the induction of promoters by constitutively active forms of IRF3 or IRF7, indicating that C6 acts at the level of the TBK1/IKKε complex. Consistent with this notion, C6 immunoprecipitated with the TBK1 complex scaffold proteins TANK, SINTBAD and NAP1. C6 is expressed early during infection and is present in both nucleus and cytoplasm. Mutant viruses in which the C6L gene is deleted, or mutated so that the C6 protein is not expressed, replicated normally in cell culture but were attenuated in two in vivo models of infection compared to wild type and revertant controls. Thus C6 contributes to VACV virulence and might do so via the inhibition of PRR-induced activation of IRF3 and IRF7.

  20. Molecular cloning and characterization of GhAPm, a gene encoding the μ subunit of the clathrin-associated adaptor protein complex that is associated with cotton (Gossypium hirsutum) fiber development.

    Science.gov (United States)

    Zhou, Tao; Zhang, Rui; Yang, Dawei; Guo, Sandui

    2011-06-01

    The clathrin-associated adaptor protein (AP) complexes are the primary clathrin adaptors that contribute to the formation of clathrin-coated vesicles (CCVs). The GhAPm gene (GenBank accession number: GU359054), which encodes the medium subunit of the AP complexes, was cloned from cotton by rapid amplification of cDNA ends-polymerase chain reaction (RACE-PCR). The full-length cDNA was 1590 bp in size and encoded an open reading frame (ORF) of 416 amino acids with a molecular weight of 46 kDa. The GhAPm protein shared 81-85% identity at the amino acid level with the AP complex μ subunits isolated from Vitis vinifera, Glycine max, Populus trichocarpa, Ricinus communis and Arabidopsis thaliana, respectively. The corresponding genomic DNA, containing eight exons and seven introns, was isolated and analyzed. Also, a 5'-flanking region was analyzed, and a group of putative cis-acting elements were identified. DNA gel blot analysis showed that there is only one GhAPm gene in the cotton genome. Real-time RT-PCR analysis revealed that GhAPm is expressed in the root, stem, leaf, petal, ovule, and fiber. However, the interesting finding is that GhAPm expression level was shown to increase steadily as the cotton fiber develops. In 30 DPA fibers, expression increases sharply and arrives at a peak then the expression levels decrease rapidly. Based on these data, we propose that GhAPm has a critical role in cotton membrane trafficking and fiber development.

  1. Domain distribution and intrinsic disorder in hubs in the human protein-protein interaction network.

    Science.gov (United States)

    Patil, Ashwini; Kinoshita, Kengo; Nakamura, Haruki

    2010-08-01

    Intrinsic disorder and distributed surface charge have been previously identified as some of the characteristics that differentiate hubs (proteins with a large number of interactions) from non-hubs in protein-protein interaction networks. In this study, we investigated the differences in the quantity, diversity, and functional nature of Pfam domains, and their relationship with intrinsic disorder, in hubs and non-hubs. We found that proteins with a more diverse domain composition were over-represented in hubs when compared with non-hubs, with the number of interactions in hubs increasing with domain diversity. Conversely, the fraction of intrinsic disorder in hubs decreased with increasing number of ordered domains. The difference in the levels of disorder was more prominent in hubs and non-hubs with fewer domains. Functional analysis showed that hubs were enriched in kinase and adaptor domains acting primarily in signal transduction and transcription regulation, whereas non-hubs had more DNA-binding domains and were involved in catalytic activity. Consistent with the differences in the functional nature of their domains, hubs with two or more domains were more likely to connect distinct functional modules in the interaction network when compared with single domain hubs. We conclude that the availability of greater number and diversity of ordered domains, in addition to the tendency to have promiscuous domains, differentiates hubs from non-hubs and provides an additional means of achieving interaction promiscuity. Further, hubs with fewer domains use greater levels of intrinsic disorder to facilitate interaction promiscuity with the prevalence of disorder decreasing with increasing number of ordered domains.

  2. Protein Networks in Alzheimer’s Disease

    DEFF Research Database (Denmark)

    Carlsen, Eva Maria Meier; Rasmussen, Rune

    2017-01-01

    Overlap of RNA and protein networks reveals glia cells as key players for the development of symptomatic Alzheimer’s disease in humans......Overlap of RNA and protein networks reveals glia cells as key players for the development of symptomatic Alzheimer’s disease in humans...

  3. Ontology integration to identify protein complex in protein interaction networks

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    Yang Zhihao

    2011-10-01

    Full Text Available Abstract Background Protein complexes can be identified from the protein interaction networks derived from experimental data sets. However, these analyses are challenging because of the presence of unreliable interactions and the complex connectivity of the network. The integration of protein-protein interactions with the data from other sources can be leveraged for improving the effectiveness of protein complexes detection algorithms. Methods We have developed novel semantic similarity method, which use Gene Ontology (GO annotations to measure the reliability of protein-protein interactions. The protein interaction networks can be converted into a weighted graph representation by assigning the reliability values to each interaction as a weight. Following the approach of that of the previously proposed clustering algorithm IPCA which expands clusters starting from seeded vertices, we present a clustering algorithm OIIP based on the new weighted Protein-Protein interaction networks for identifying protein complexes. Results The algorithm OIIP is applied to the protein interaction network of Sacchromyces cerevisiae and identifies many well known complexes. Experimental results show that the algorithm OIIP has higher F-measure and accuracy compared to other competing approaches.

  4. 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.

  5. Unraveling protein networks with power graph analysis.

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    Loïc Royer

    Full Text Available Networks play a crucial role in computational biology, yet their analysis and representation is still an open problem. Power Graph Analysis is a lossless transformation of biological networks into a compact, less redundant representation, exploiting the abundance of cliques and bicliques as elementary topological motifs. We demonstrate with five examples the advantages of Power Graph Analysis. Investigating protein-protein interaction networks, we show how the catalytic subunits of the casein kinase II complex are distinguishable from the regulatory subunits, how interaction profiles and sequence phylogeny of SH3 domains correlate, and how false positive interactions among high-throughput interactions are spotted. Additionally, we demonstrate the generality of Power Graph Analysis by applying it to two other types of networks. We show how power graphs induce a clustering of both transcription factors and target genes in bipartite transcription networks, and how the erosion of a phosphatase domain in type 22 non-receptor tyrosine phosphatases is detected. We apply Power Graph Analysis to high-throughput protein interaction networks and show that up to 85% (56% on average of the information is redundant. Experimental networks are more compressible than rewired ones of same degree distribution, indicating that experimental networks are rich in cliques and bicliques. Power Graphs are a novel representation of networks, which reduces network complexity by explicitly representing re-occurring network motifs. Power Graphs compress up to 85% of the edges in protein interaction networks and are applicable to all types of networks such as protein interactions, regulatory networks, or homology networks.

  6. Protein complexes predictions within protein interaction networks using genetic algorithms.

    Science.gov (United States)

    Ramadan, Emad; Naef, Ahmed; Ahmed, Moataz

    2016-07-25

    Protein-protein interaction networks are receiving increased attention due to their importance in understanding life at the cellular level. A major challenge in systems biology is to understand the modular structure of such biological networks. Although clustering techniques have been proposed for clustering protein-protein interaction networks, those techniques suffer from some drawbacks. The application of earlier clustering techniques to protein-protein interaction networks in order to predict protein complexes within the networks does not yield good results due to the small-world and power-law properties of these networks. In this paper, we construct a new clustering algorithm for predicting protein complexes through the use of genetic algorithms. We design an objective function for exclusive clustering and overlapping clustering. We assess the quality of our proposed clustering algorithm using two gold-standard data sets. Our algorithm can identify protein complexes that are significantly enriched in the gold-standard data sets. Furthermore, our method surpasses three competing methods: MCL, ClusterOne, and MCODE in terms of the quality of the predicted complexes. The source code and accompanying examples are freely available at http://faculty.kfupm.edu.sa/ics/eramadan/GACluster.zip .

  7. Characterization of Toll-like receptors in primary lung epithelial cells: strong impact of the TLR3 ligand poly(I:C on the regulation of Toll-like receptors, adaptor proteins and inflammatory response

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    Weith Andreas

    2005-11-01

    Full Text Available Abstract Background Bacterial and viral exacerbations play a crucial role in a variety of lung diseases including COPD or asthma. Since the lung epithelium is a major source of various inflammatory mediators that affect the immune response, we analyzed the inflammatory reaction of primary lung epithelial cells to different microbial molecules that are recognized by Toll-like receptors (TLR. Methods The effects of TLR ligands on primary small airway epithelial cells were analyzed in detail with respect to cytokine, chemokine and matrix metalloproteinase secretion. In addition, the regulation of the expression of TLRs and their adaptor proteins in small airway epithelial cells was investigated. Results Our data demonstrate that poly(I:C, a synthetic analog of viral dsRNA, mediated the strongest proinflammatory effects among the tested ligands, including an increased secretion of IL-6, IL-8, TNF-α, GM-CSF, GRO-α, TARC, MCP-1, MIP-3α, RANTES, IFN-β, IP-10 and ITAC as well as an increased release of MMP-1, MMP-8, MMP-9, MMP-10 and MMP-13. Furthermore, our data show that poly(I:C as well as type-1 and type-2 cytokines have a pronounced effect on the expression of TLRs and molecules involved in TLR signaling in small airway epithelial cells. Poly(I:C induced an elevated expression of TLR1, TLR2 and TLR3 and increased the gene expression of the general TLR adaptor MyD88 and IRAK-2. Simultaneously, poly(I:C decreased the expression of TLR5, TLR6 and TOLLIP. Conclusion Poly(I:C, an analog of viral dsRNA and a TLR3 ligand, triggers a strong inflammatory response in small airway epithelial cells that is likely to contribute to viral exacerbations of pulmonary diseases like asthma or COPD. The pronounced effects of poly(I:C on the expression of Toll-like receptors and molecules involved in TLR signaling is assumed to influence the immune response of the lung epithelium to viral and bacterial infections. Likewise, the regulation of TLR expression by type

  8. Identifying hubs in protein interaction networks.

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    Ravishankar R Vallabhajosyula

    Full Text Available In spite of the scale-free degree distribution that characterizes most protein interaction networks (PINs, it is common to define an ad hoc degree scale that defines "hub" proteins having special topological and functional significance. This raises the concern that some conclusions on the functional significance of proteins based on network properties may not be robust.In this paper we present three objective methods to define hub proteins in PINs: one is a purely topological method and two others are based on gene expression and function. By applying these methods to four distinct PINs, we examine the extent of agreement among these methods and implications of these results on network construction.We find that the methods agree well for networks that contain a balance between error-free and unbiased interactions, indicating that the hub concept is meaningful for such networks.

  9. The microRNA mir-71 inhibits calcium signaling by targeting the TIR-1/Sarm1 adaptor protein to control stochastic L/R neuronal asymmetry in C. elegans.

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    Yi-Wen Hsieh

    Full Text Available The Caenorhabditis elegans left and right AWC olfactory neurons communicate to establish stochastic asymmetric identities, AWC(ON and AWC(OFF, by inhibiting a calcium-mediated signaling pathway in the future AWC(ON cell. NSY-4/claudin-like protein and NSY-5/innexin gap junction protein are the two parallel signals that antagonize the calcium signaling pathway to induce the AWC(ON fate. However, it is not known how the calcium signaling pathway is downregulated by nsy-4 and nsy-5 in the AWC(ON cell. Here we identify a microRNA, mir-71, that represses the TIR-1/Sarm1 adaptor protein in the calcium signaling pathway to promote the AWC(ON identity. Similar to tir-1 loss-of-function mutants, overexpression of mir-71 generates two AWC(ON neurons. tir-1 expression is downregulated through its 3' UTR in AWC(ON, in which mir-71 is expressed at a higher level than in AWC(OFF. In addition, mir-71 is sufficient to inhibit tir-1 expression in AWC through the mir-71 complementary site in the tir-1 3' UTR. Our genetic studies suggest that mir-71 acts downstream of nsy-4 and nsy-5 to promote the AWC(ON identity in a cell autonomous manner. Furthermore, the stability of mature mir-71 is dependent on nsy-4 and nsy-5. Together, these results provide insight into the mechanism by which nsy-4 and nsy-5 inhibit calcium signaling to establish stochastic asymmetric AWC differentiation.

  10. Absence of the Adaptor Protein PEA-15 Is Associated with Altered Pattern of Th Cytokines Production by Activated CD4+ T Lymphocytes In Vitro, and Defective Red Blood Cell Alloimmune Response In Vivo.

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    Stéphane Kerbrat

    Full Text Available TCR-dependent and costimulation signaling, cell division, and cytokine environment are major factors driving cytokines expression induced by CD4(+ T cell activation. PEA-15 15 (Protein Enriched in Astrocyte / 15 kDa is an adaptor protein that regulates death receptor-induced apoptosis and proliferation signaling by binding to FADD and relocating ERK1/2 to the cytosol, respectively. By using PEA-15-deficient mice, we examined the role of PEA-15 in TCR-dependent cytokine production in CD4(+ T cells. TCR-stimulated PEA-15-deficient CD4(+ T cells exhibited defective progression through the cell cycle associated with impaired expression of cyclin E and phosphoRb, two ERK1/2-dependent proteins of the cell cycle. Accordingly, expression of the division cycle-dependent cytokines IL-2 and IFNγ, a Th1 cytokine, was reduced in stimulated PEA-15-deficient CD4(+ T cells. This was associated with abnormal subcellular compartmentalization of activated ERK1/2 in PEA-15-deficient T cells. Furthermore, in vitro TCR-dependent differentiation of naive CD4(+ CD62L(+ PEA-15-deficient T cells was associated with a lower production of the Th2 cytokine, IL-4, whereas expression of the Th17-associated molecule IL4I1 was enhanced. Finally, a defective humoral response was shown in PEA-15-deficient mice in a model of red blood cell alloimmunization performed with Poly IC, a classical adjuvant of Th1 response in vivo. Collectively, our data suggest that PEA-15 contributes to the specification of the cytokine pattern of activated Th cells, thus highlighting a potential new target to interfere with T cell functional polarization and subsequent immune response.

  11. Absence of the Adaptor Protein PEA-15 Is Associated with Altered Pattern of Th Cytokines Production by Activated CD4+ T Lymphocytes In Vitro, and Defective Red Blood Cell Alloimmune Response In Vivo.

    Science.gov (United States)

    Kerbrat, Stéphane; Vingert, Benoit; Junier, Marie-Pierre; Castellano, Flavia; Renault-Mihara, François; Dos Reis Tavares, Silvina; Surenaud, Mathieu; Noizat-Pirenne, France; Boczkowski, Jorge; Guellaën, Georges; Chneiweiss, Hervé; Le Gouvello, Sabine

    2015-01-01

    TCR-dependent and costimulation signaling, cell division, and cytokine environment are major factors driving cytokines expression induced by CD4(+) T cell activation. PEA-15 15 (Protein Enriched in Astrocyte / 15 kDa) is an adaptor protein that regulates death receptor-induced apoptosis and proliferation signaling by binding to FADD and relocating ERK1/2 to the cytosol, respectively. By using PEA-15-deficient mice, we examined the role of PEA-15 in TCR-dependent cytokine production in CD4(+) T cells. TCR-stimulated PEA-15-deficient CD4(+) T cells exhibited defective progression through the cell cycle associated with impaired expression of cyclin E and phosphoRb, two ERK1/2-dependent proteins of the cell cycle. Accordingly, expression of the division cycle-dependent cytokines IL-2 and IFNγ, a Th1 cytokine, was reduced in stimulated PEA-15-deficient CD4(+) T cells. This was associated with abnormal subcellular compartmentalization of activated ERK1/2 in PEA-15-deficient T cells. Furthermore, in vitro TCR-dependent differentiation of naive CD4(+) CD62L(+) PEA-15-deficient T cells was associated with a lower production of the Th2 cytokine, IL-4, whereas expression of the Th17-associated molecule IL4I1 was enhanced. Finally, a defective humoral response was shown in PEA-15-deficient mice in a model of red blood cell alloimmunization performed with Poly IC, a classical adjuvant of Th1 response in vivo. Collectively, our data suggest that PEA-15 contributes to the specification of the cytokine pattern of activated Th cells, thus highlighting a potential new target to interfere with T cell functional polarization and subsequent immune response.

  12. Prediction of Protein-Protein Interactions Related to Protein Complexes Based on Protein Interaction Networks

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    Peng Liu

    2015-01-01

    Full Text Available A method for predicting protein-protein interactions based on detected protein complexes is proposed to repair deficient interactions derived from high-throughput biological experiments. Protein complexes are pruned and decomposed into small parts based on the adaptive k-cores method to predict protein-protein interactions associated with the complexes. The proposed method is adaptive to protein complexes with different structure, number, and size of nodes in a protein-protein interaction network. Based on different complex sets detected by various algorithms, we can obtain different prediction sets of protein-protein interactions. The reliability of the predicted interaction sets is proved by using estimations with statistical tests and direct confirmation of the biological data. In comparison with the approaches which predict the interactions based on the cliques, the overlap of the predictions is small. Similarly, the overlaps among the predicted sets of interactions derived from various complex sets are also small. Thus, every predicted set of interactions may complement and improve the quality of the original network data. Meanwhile, the predictions from the proposed method replenish protein-protein interactions associated with protein complexes using only the network topology.

  13. Human cancer protein-protein interaction network: a structural perspective.

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    Gozde Kar

    2009-12-01

    Full Text Available Protein-protein interaction networks provide a global picture of cellular function and biological processes. Some proteins act as hub proteins, highly connected to others, whereas some others have few interactions. The dysfunction of some interactions causes many diseases, including cancer. Proteins interact through their interfaces. Therefore, studying the interface properties of cancer-related proteins will help explain their role in the interaction networks. Similar or overlapping binding sites should be used repeatedly in single interface hub proteins, making them promiscuous. Alternatively, multi-interface hub proteins make use of several distinct binding sites to bind to different partners. We propose a methodology to integrate protein interfaces into cancer interaction networks (ciSPIN, cancer structural protein interface network. The interactions in the human protein interaction network are replaced by interfaces, coming from either known or predicted complexes. We provide a detailed analysis of cancer related human protein-protein interfaces and the topological properties of the cancer network. The results reveal that cancer-related proteins have smaller, more planar, more charged and less hydrophobic binding sites than non-cancer proteins, which may indicate low affinity and high specificity of the cancer-related interactions. We also classified the genes in ciSPIN according to phenotypes. Within phenotypes, for breast cancer, colorectal cancer and leukemia, interface properties were found to be discriminating from non-cancer interfaces with an accuracy of 71%, 67%, 61%, respectively. In addition, cancer-related proteins tend to interact with their partners through distinct interfaces, corresponding mostly to multi-interface hubs, which comprise 56% of cancer-related proteins, and constituting the nodes with higher essentiality in the network (76%. We illustrate the interface related affinity properties of two cancer-related hub

  14. NAPS: Network Analysis of Protein Structures

    Science.gov (United States)

    Chakrabarty, Broto; Parekh, Nita

    2016-01-01

    Traditionally, protein structures have been analysed by the secondary structure architecture and fold arrangement. An alternative approach that has shown promise is modelling proteins as a network of non-covalent interactions between amino acid residues. The network representation of proteins provide a systems approach to topological analysis of complex three-dimensional structures irrespective of secondary structure and fold type and provide insights into structure-function relationship. We have developed a web server for network based analysis of protein structures, NAPS, that facilitates quantitative and qualitative (visual) analysis of residue–residue interactions in: single chains, protein complex, modelled protein structures and trajectories (e.g. from molecular dynamics simulations). The user can specify atom type for network construction, distance range (in Å) and minimal amino acid separation along the sequence. NAPS provides users selection of node(s) and its neighbourhood based on centrality measures, physicochemical properties of amino acids or cluster of well-connected residues (k-cliques) for further analysis. Visual analysis of interacting domains and protein chains, and shortest path lengths between pair of residues are additional features that aid in functional analysis. NAPS support various analyses and visualization views for identifying functional residues, provide insight into mechanisms of protein folding, domain-domain and protein–protein interactions for understanding communication within and between proteins. URL:http://bioinf.iiit.ac.in/NAPS/. PMID:27151201

  15. DNAX-activating Protein 10 (DAP10) Membrane Adaptor Associates with Receptor for Advanced Glycation End Products (RAGE) and Modulates the RAGE-triggered Signaling Pathway in Human Keratinocytes*

    Science.gov (United States)

    Sakaguchi, Masakiyo; Murata, Hitoshi; Aoyama, Yumi; Hibino, Toshihiko; Putranto, Endy Widya; Ruma, I. Made Winarsa; Inoue, Yusuke; Sakaguchi, Yoshihiko; Yamamoto, Ken-ichi; Kinoshita, Rie; Futami, Junichiro; Kataoka, Ken; Iwatsuki, Keiji; Huh, Nam-ho

    2014-01-01

    The receptor for advanced glycation end products (RAGE) is involved in the pathogenesis of many inflammatory, degenerative, and hyperproliferative diseases, including cancer. Previously, we revealed mechanisms of downstream signaling from ligand-activated RAGE, which recruits TIRAP/MyD88. Here, we showed that DNAX-activating protein 10 (DAP10), a transmembrane adaptor protein, also binds to RAGE. By artificial oligomerization of RAGE alone or RAGE-DAP10, we found that RAGE-DAP10 heterodimer formation resulted in a marked enhancement of Akt activation, whereas homomultimeric interaction of RAGE led to activation of caspase 8. Normal human epidermal keratinocytes exposed to S100A8/A9, a ligand for RAGE, at a nanomolar concentration mimicked the pro-survival response of RAGE-DAP10 interaction, although at a micromolar concentration, the cells mimicked the pro-apoptotic response of RAGE-RAGE. In transformed epithelial cell lines, A431 and HaCaT, in which endogenous DAP10 was overexpressed, and S100A8/A9, even at a micromolar concentration, led to cell growth and survival due to RAGE-DAP10 interaction. Functional blocking of DAP10 in the cell lines abrogated the Akt phosphorylation from S100A8/A9-activated RAGE, eventually leading to an increase in apoptosis. Finally, S100A8/A9, RAGE, and DAP10 were overexpressed in the psoriatic epidermis. Our findings indicate that the functional interaction between RAGE and DAP10 coordinately regulates S100A8/A9-mediated survival and/or apoptotic response of keratinocytes. PMID:25002577

  16. The adaptor molecule signaling lymphocytic activation molecule (SLAM)-associated protein (SAP) is essential in mechanisms involving the Fyn tyrosine kinase for induction and progression of collagen-induced arthritis.

    Science.gov (United States)

    Zhong, Ming-Chao; Veillette, André

    2013-11-01

    Signaling lymphocytic activation molecule-associated protein (SAP) is an Src homology 2 domain-only adaptor involved in multiple immune cell functions. It has also been linked to immunodeficiencies and autoimmune diseases, such as systemic lupus erythematosus. Here, we examined the role and mechanism of action of SAP in autoimmunity using a mouse model of autoimmune arthritis, collagen-induced arthritis (CIA). We found that SAP was essential for development of CIA in response to collagen immunization. It was also required for production of collagen-specific antibodies, which play a key role in disease pathogenesis. These effects required SAP expression in T cells, not in B cells. In mice immunized with a high dose of collagen, the activity of SAP was nearly independent of its ability to bind the protein tyrosine kinase Fyn and correlated with the capacity of SAP to promote full differentiation of follicular T helper (TFH) cells. However, with a lower dose of collagen, the role of SAP was more dependent on Fyn binding, suggesting that additional mechanisms other than TFH cell differentiation were involved. Further studies suggested that this might be due to a role of the SAP-Fyn interaction in natural killer T cell development through the ability of SAP-Fyn to promote Vav-1 activation. We also found that removal of SAP expression during progression of CIA attenuated disease severity. However, it had no effect on disease when CIA was clinically established. Together, these results indicate that SAP plays an essential role in CIA because of Fyn-independent and Fyn-dependent effects on TFH cells and, possibly, other T cell types.

  17. Evolution of protein-protein interaction networks in yeast.

    Directory of Open Access Journals (Sweden)

    Andrew Schoenrock

    Full Text Available Interest in the evolution of protein-protein and genetic interaction networks has been rising in recent years, but the lack of large-scale high quality comparative datasets has acted as a barrier. Here, we carried out a comparative analysis of computationally predicted protein-protein interaction (PPI networks from five closely related yeast species. We used the Protein-protein Interaction Prediction Engine (PIPE, which uses a database of known interactions to make sequence-based PPI predictions, to generate high quality predicted interactomes. Simulated proteomes and corresponding PPI networks were used to provide null expectations for the extent and nature of PPI network evolution. We found strong evidence for conservation of PPIs, with lower than expected levels of change in PPIs for about a quarter of the proteome. Furthermore, we found that changes in predicted PPI networks are poorly predicted by sequence divergence. Our analyses identified a number of functional classes experiencing fewer PPI changes than expected, suggestive of purifying selection on PPIs. Our results demonstrate the added benefit of considering predicted PPI networks when studying the evolution of closely related organisms.

  18. Association between receptor protein-tyrosine phosphatase RPTPalpha and the Grb2 adaptor. Dual Src homology (SH) 2/SH3 domain requirement and functional consequences

    DEFF Research Database (Denmark)

    Su, J; Yang, L T; Sap, J

    1996-01-01

    binding site in RPTPalpha was studied further by expression of wild type or mutant RPTPalpha proteins in PC12 cells. In these cells, wild type RPTPalpha interferes with acidic fibroblast growth factor-induced neurite outgrowth; this effect requires both the catalytic activity and the Grb2 binding Tyr798...

  19. Neural Networks for protein Structure Prediction

    DEFF Research Database (Denmark)

    Bohr, Henrik

    1998-01-01

    This is a review about neural network applications in bioinformatics. Especially the applications to protein structure prediction, e.g. prediction of secondary structures, prediction of surface structure, fold class recognition and prediction of the 3-dimensional structure of protein backbones...

  20. Geometric de-noising of protein-protein interaction networks.

    Directory of Open Access Journals (Sweden)

    Oleksii Kuchaiev

    2009-08-01

    Full Text Available Understanding complex networks of protein-protein interactions (PPIs is one of the foremost challenges of the post-genomic era. Due to the recent advances in experimental bio-technology, including yeast-2-hybrid (Y2H, tandem affinity purification (TAP and other high-throughput methods for protein-protein interaction (PPI detection, huge amounts of PPI network data are becoming available. Of major concern, however, are the levels of noise and incompleteness. For example, for Y2H screens, it is thought that the false positive rate could be as high as 64%, and the false negative rate may range from 43% to 71%. TAP experiments are believed to have comparable levels of noise.We present a novel technique to assess the confidence levels of interactions in PPI networks obtained from experimental studies. We use it for predicting new interactions and thus for guiding future biological experiments. This technique is the first to utilize currently the best fitting network model for PPI networks, geometric graphs. Our approach achieves specificity of 85% and sensitivity of 90%. We use it to assign confidence scores to physical protein-protein interactions in the human PPI network downloaded from BioGRID. Using our approach, we predict 251 interactions in the human PPI network, a statistically significant fraction of which correspond to protein pairs sharing common GO terms. Moreover, we validate a statistically significant portion of our predicted interactions in the HPRD database and the newer release of BioGRID. The data and Matlab code implementing the methods are freely available from the web site: http://www.kuchaev.com/Denoising.

  1. Abelson interactor-1 (ABI-1) interacts with MRL adaptor protein MIG-10 and is required in guided cell migrations and process outgrowth in C.elegans

    Science.gov (United States)

    McShea, Molly A.; Schmidt, Kristopher L.; Dubuke, Michelle L.; Baldiga, Christina E.; Sullender, Meagan E.; Reis, Andrea L.; Zhang, Subaiou; O'Toole, Sean M.; Jeffers, Mary C.; Warden, Rachel M.; Kenney, Allison H.; Gosselin, Jennifer; Kuhlwein, Mark; Hashmi, Sana K.; Stringham, Eve G.; Ryder, Elizabeth F.

    2012-01-01

    Directed cell migration and process outgrowth are vital to proper development of many metazoan tissues. These processes are dependent on reorganization of the actin cytoskeleton in response to external guidance cues. During development of the nervous system, the MIG-10/RIAM/Lamellipodin (MRL) signaling proteins are thought to transmit positional information from surface guidance cues to the actin polymerization machinery, and thus to promote polarized outgrowth of axons. In C. elegans, mutations in the MRL family member gene mig-10 result in animals that have defects in axon guidance, neuronal migration, and the outgrowth of the processes or ‘canals’ of the excretory cell, which is required for osmoregulation in the worm. In addition, mig-10 mutant animals have recently been shown to have defects in clustering of vesicles at the synapse. To determine additional molecular partners of MIG-10, we conducted a yeast two hybrid screen using isoform MIG-10A as bait and isolated Abelson-interactor protein-1 (ABI-1). ABI-1, a downstream target of Abl non-receptor tyrosine kinase, is a member of the WAVE regulatory complex (WRC) involved in the initiation of actin polymerization. Further analysis using a co-mmunoprecipitation system confirmed the interaction of MIG-10 and ABI-1 and showed that it requires the SH3 domain of ABI-1. Single mutants for mig-10 and abi-1 displayed similar phenotypes of incomplete migration of the ALM neurons and truncated outgrowth of the excretory cell canals, suggesting that the ABI-1/MIG-10 interaction is relevant in vivo. Cell autonomous expression of MIG-10 isoforms rescued both the neuronal migration and the canal outgrowth defects, showing that MIG-10 functions autonomously in the ALM neurons and the excretory cell. These results suggest that MIG-10 and ABI-1 interact physically to promote cell migration and process outgrowth in vivo. In the excretory canal, ABI-1 is thought to act downstream of UNC-53/NAV2, linking this large

  2. Influence of degree correlations on network structure and stability in protein-protein interaction networks

    Directory of Open Access Journals (Sweden)

    Zimmer Ralf

    2007-08-01

    Full Text Available Abstract Background The existence of negative correlations between degrees of interacting proteins is being discussed since such negative degree correlations were found for the large-scale yeast protein-protein interaction (PPI network of Ito et al. More recent studies observed no such negative correlations for high-confidence interaction sets. In this article, we analyzed a range of experimentally derived interaction networks to understand the role and prevalence of degree correlations in PPI networks. We investigated how degree correlations influence the structure of networks and their tolerance against perturbations such as the targeted deletion of hubs. Results For each PPI network, we simulated uncorrelated, positively and negatively correlated reference networks. Here, a simple model was developed which can create different types of degree correlations in a network without changing the degree distribution. Differences in static properties associated with degree correlations were compared by analyzing the network characteristics of the original PPI and reference networks. Dynamics were compared by simulating the effect of a selective deletion of hubs in all networks. Conclusion Considerable differences between the network types were found for the number of components in the original networks. Negatively correlated networks are fragmented into significantly less components than observed for positively correlated networks. On the other hand, the selective deletion of hubs showed an increased structural tolerance to these deletions for the positively correlated networks. This results in a lower rate of interaction loss in these networks compared to the negatively correlated networks and a decreased disintegration rate. Interestingly, real PPI networks are most similar to the randomly correlated references with respect to all properties analyzed. Thus, although structural properties of networks can be modified considerably by degree

  3. Network compression as a quality measure for protein interaction networks.

    Directory of Open Access Journals (Sweden)

    Loic Royer

    Full Text Available With the advent of large-scale protein interaction studies, there is much debate about data quality. Can different noise levels in the measurements be assessed by analyzing network structure? Because proteomic regulation is inherently co-operative, modular and redundant, it is inherently compressible when represented as a network. Here we propose that network compression can be used to compare false positive and false negative noise levels in protein interaction networks. We validate this hypothesis by first confirming the detrimental effect of false positives and false negatives. Second, we show that gold standard networks are more compressible. Third, we show that compressibility correlates with co-expression, co-localization, and shared function. Fourth, we also observe correlation with better protein tagging methods, physiological expression in contrast to over-expression of tagged proteins, and smart pooling approaches for yeast two-hybrid screens. Overall, this new measure is a proxy for both sensitivity and specificity and gives complementary information to standard measures such as average degree and clustering coefficients.

  4. Detection of protein complex from protein-protein interaction network using Markov clustering

    International Nuclear Information System (INIS)

    Ochieng, P J; Kusuma, W A; Haryanto, T

    2017-01-01

    Detection of complexes, or groups of functionally related proteins, is an important challenge while analysing biological networks. However, existing algorithms to identify protein complexes are insufficient when applied to dense networks of experimentally derived interaction data. Therefore, we introduced a graph clustering method based on Markov clustering algorithm to identify protein complex within highly interconnected protein-protein interaction networks. Protein-protein interaction network was first constructed to develop geometrical network, the network was then partitioned using Markov clustering to detect protein complexes. The interest of the proposed method was illustrated by its application to Human Proteins associated to type II diabetes mellitus. Flow simulation of MCL algorithm was initially performed and topological properties of the resultant network were analysed for detection of the protein complex. The results indicated the proposed method successfully detect an overall of 34 complexes with 11 complexes consisting of overlapping modules and 20 non-overlapping modules. The major complex consisted of 102 proteins and 521 interactions with cluster modularity and density of 0.745 and 0.101 respectively. The comparison analysis revealed MCL out perform AP, MCODE and SCPS algorithms with high clustering coefficient (0.751) network density and modularity index (0.630). This demonstrated MCL was the most reliable and efficient graph clustering algorithm for detection of protein complexes from PPI networks. (paper)

  5. 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

  6. Finding local communities in protein networks.

    Science.gov (United States)

    Voevodski, Konstantin; Teng, Shang-Hua; Xia, Yu

    2009-09-18

    Protein-protein interactions (PPIs) play fundamental roles in nearly all biological processes, and provide major insights into the inner workings of cells. A vast amount of PPI data for various organisms is available from BioGRID and other sources. The identification of communities in PPI networks is of great interest because they often reveal previously unknown functional ties between proteins. A large number of global clustering algorithms have been applied to protein networks, where the entire network is partitioned into clusters. Here we take a different approach by looking for local communities in PPI networks. We develop a tool, named Local Protein Community Finder, which quickly finds a community close to a queried protein in any network available from BioGRID or specified by the user. Our tool uses two new local clustering algorithms Nibble and PageRank-Nibble, which look for a good cluster among the most popular destinations of a short random walk from the queried vertex. The quality of a cluster is determined by proportion of outgoing edges, known as conductance, which is a relative measure particularly useful in undersampled networks. We show that the two local clustering algorithms find communities that not only form excellent clusters, but are also likely to be biologically relevant functional components. We compare the performance of Nibble and PageRank-Nibble to other popular and effective graph partitioning algorithms, and show that they find better clusters in the graph. Moreover, Nibble and PageRank-Nibble find communities that are more functionally coherent. The Local Protein Community Finder, accessible at http://xialab.bu.edu/resources/lpcf, allows the user to quickly find a high-quality community close to a queried protein in any network available from BioGRID or specified by the user. We show that the communities found by our tool form good clusters and are functionally coherent, making our application useful for biologists who wish to

  7. Finding local communities in protein networks

    Directory of Open Access Journals (Sweden)

    Teng Shang-Hua

    2009-09-01

    Full Text Available Abstract Background Protein-protein interactions (PPIs play fundamental roles in nearly all biological processes, and provide major insights into the inner workings of cells. A vast amount of PPI data for various organisms is available from BioGRID and other sources. The identification of communities in PPI networks is of great interest because they often reveal previously unknown functional ties between proteins. A large number of global clustering algorithms have been applied to protein networks, where the entire network is partitioned into clusters. Here we take a different approach by looking for local communities in PPI networks. Results We develop a tool, named Local Protein Community Finder, which quickly finds a community close to a queried protein in any network available from BioGRID or specified by the user. Our tool uses two new local clustering algorithms Nibble and PageRank-Nibble, which look for a good cluster among the most popular destinations of a short random walk from the queried vertex. The quality of a cluster is determined by proportion of outgoing edges, known as conductance, which is a relative measure particularly useful in undersampled networks. We show that the two local clustering algorithms find communities that not only form excellent clusters, but are also likely to be biologically relevant functional components. We compare the performance of Nibble and PageRank-Nibble to other popular and effective graph partitioning algorithms, and show that they find better clusters in the graph. Moreover, Nibble and PageRank-Nibble find communities that are more functionally coherent. Conclusion The Local Protein Community Finder, accessible at http://xialab.bu.edu/resources/lpcf, allows the user to quickly find a high-quality community close to a queried protein in any network available from BioGRID or specified by the user. We show that the communities found by our tool form good clusters and are functionally coherent

  8. DETECTION OF TOPOLOGICAL PATTERNS IN PROTEIN NETWORKS.

    Energy Technology Data Exchange (ETDEWEB)

    MASLOV,S.SNEPPEN,K.

    2003-11-17

    Complex networks appear in biology on many different levels: (1) All biochemical reactions taking place in a single cell constitute its metabolic network, where nodes are individual metabolites, and edges are metabolic reactions converting them to each other. (2) Virtually every one of these reactions is catalyzed by an enzyme and the specificity of this catalytic function is ensured by the key and lock principle of its physical interaction with the substrate. Often the functional enzyme is formed by several mutually interacting proteins. Thus the structure of the metabolic network is shaped by the network of physical interactions of cell's proteins with their substrates and each other. (3) The abundance and the level of activity of each of the proteins in the physical interaction network in turn is controlled by the regulatory network of the cell. Such regulatory network includes all of the multiple mechanisms in which proteins in the cell control each other including transcriptional and translational regulation, regulation of mRNA editing and its transport out of the nucleus, specific targeting of individual proteins for degradation, modification of their activity e.g. by phosphorylation/dephosphorylation or allosteric regulation, etc. To get some idea about the complexity and interconnectedness of protein-protein regulations in baker's yeast Saccharomyces Cerevisiae in Fig. 1 we show a part of the regulatory network corresponding to positive or negative regulations that regulatory proteins exert on each other. (4) On yet higher level individual cells of a multicellular organism exchange signals with each other. This gives rise to several new networks such as e.g. nervous, hormonal, and immune systems of animals. The intercellular signaling network stages the development of a multicellular organism from the fertilized egg. (5) Finally, on the grandest scale, the interactions between individual species in ecosystems determine their food webs. An

  9. A conserved mammalian protein interaction network.

    Directory of Open Access Journals (Sweden)

    Åsa Pérez-Bercoff

    Full Text Available Physical interactions between proteins mediate a variety of biological functions, including signal transduction, physical structuring of the cell and regulation. While extensive catalogs of such interactions are known from model organisms, their evolutionary histories are difficult to study given the lack of interaction data from phylogenetic outgroups. Using phylogenomic approaches, we infer a upper bound on the time of origin for a large set of human protein-protein interactions, showing that most such interactions appear relatively ancient, dating no later than the radiation of placental mammals. By analyzing paired alignments of orthologous and putatively interacting protein-coding genes from eight mammals, we find evidence for weak but significant co-evolution, as measured by relative selective constraint, between pairs of genes with interacting proteins. However, we find no strong evidence for shared instances of directional selection within an interacting pair. Finally, we use a network approach to show that the distribution of selective constraint across the protein interaction network is non-random, with a clear tendency for interacting proteins to share similar selective constraints. Collectively, the results suggest that, on the whole, protein interactions in mammals are under selective constraint, presumably due to their functional roles.

  10. Inferring protein function by domain context similarities in protein-protein interaction networks

    Directory of Open Access Journals (Sweden)

    Sun Zhirong

    2009-12-01

    Full Text Available Abstract Background Genome sequencing projects generate massive amounts of sequence data but there are still many proteins whose functions remain unknown. The availability of large scale protein-protein interaction data sets makes it possible to develop new function prediction methods based on protein-protein interaction (PPI networks. Although several existing methods combine multiple information resources, there is no study that integrates protein domain information and PPI networks to predict protein functions. Results The domain context similarity can be a useful index to predict protein function similarity. The prediction accuracy of our method in yeast is between 63%-67%, which outperforms the other methods in terms of ROC curves. Conclusion This paper presents a novel protein function prediction method that combines protein domain composition information and PPI networks. Performance evaluations show that this method outperforms existing methods.

  11. Hubs with network motifs organize modularity dynamically in the protein-protein interaction network of yeast.

    Science.gov (United States)

    Jin, Guangxu; Zhang, Shihua; Zhang, Xiang-Sun; Chen, Luonan

    2007-11-21

    It has been recognized that modular organization pervades biological complexity. Based on network analysis, 'party hubs' and 'date hubs' were proposed to understand the basic principle of module organization of biomolecular networks. However, recent study on hubs has suggested that there is no clear evidence for coexistence of 'party hubs' and 'date hubs'. Thus, an open question has been raised as to whether or not 'party hubs' and 'date hubs' truly exist in yeast interactome. In contrast to previous studies focusing on the partners of a hub or the individual proteins around the hub, our work aims to study the network motifs of a hub or interactions among individual proteins including the hub and its neighbors. Depending on the relationship between a hub's network motifs and protein complexes, we define two new types of hubs, 'motif party hubs' and 'motif date hubs', which have the same characteristics as the original 'party hubs' and 'date hubs' respectively. The network motifs of these two types of hubs display significantly different features in spatial distribution (or cellular localizations), co-expression in microarray data, controlling topological structure of network, and organizing modularity. By virtue of network motifs, we basically solved the open question about 'party hubs' and 'date hubs' which was raised by previous studies. Specifically, at the level of network motifs instead of individual proteins, we found two types of hubs, motif party hubs (mPHs) and motif date hubs (mDHs), whose network motifs display distinct characteristics on biological functions. In addition, in this paper we studied network motifs from a different viewpoint. That is, we show that a network motif should not be merely considered as an interaction pattern but be considered as an essential function unit in organizing modules of networks.

  12. Topology-function conservation in protein-protein interaction networks.

    Science.gov (United States)

    Davis, Darren; Yaveroğlu, Ömer Nebil; Malod-Dognin, Noël; Stojmirovic, Aleksandar; Pržulj, Nataša

    2015-05-15

    Proteins underlay the functioning of a cell and the wiring of proteins in protein-protein interaction network (PIN) relates to their biological functions. Proteins with similar wiring in the PIN (topology around them) have been shown to have similar functions. This property has been successfully exploited for predicting protein functions. Topological similarity is also used to guide network alignment algorithms that find similarly wired proteins between PINs of different species; these similarities are used to transfer annotation across PINs, e.g. from model organisms to human. To refine these functional predictions and annotation transfers, we need to gain insight into the variability of the topology-function relationships. For example, a function may be significantly associated with specific topologies, while another function may be weakly associated with several different topologies. Also, the topology-function relationships may differ between different species. To improve our understanding of topology-function relationships and of their conservation among species, we develop a statistical framework that is built upon canonical correlation analysis. Using the graphlet degrees to represent the wiring around proteins in PINs and gene ontology (GO) annotations to describe their functions, our framework: (i) characterizes statistically significant topology-function relationships in a given species, and (ii) uncovers the functions that have conserved topology in PINs of different species, which we term topologically orthologous functions. We apply our framework to PINs of yeast and human, identifying seven biological process and two cellular component GO terms to be topologically orthologous for the two organisms. © The Author 2015. Published by Oxford University Press.

  13. Essential Protein Detection by Random Walk on Weighted Protein-Protein Interaction Networks.

    Science.gov (United States)

    Xu, Bin; Guan, Jihong; Wang, Yang; Wang, Zewei

    2017-05-12

    Essential proteins are critical to the development and survival of cells. Identification of essential proteins is helpful for understanding the minimal set of required genes in a living cell and for designing new drugs. To detect essential proteins, various computational methods have been proposed based on protein-protein interaction (PPI) networks. However, protein interaction data obtained by highthroughput experiments usually contain high false positives, which negatively impacts the accuracy of essential protein detection. Moreover, most existing studies focused on the local information of proteins in PPI networks, while ignoring the influence of indirect protein interactions on essentiality. In this paper, we propose a novel method, called Essentiality Ranking (EssRank in short), to boost the accuracy of essential protein detection. To deal with the inaccuracy of PPI data, confidence scores of interactions are evaluated by integrating various biological information. Weighted edge clustering coefficient (WECC), considering both interaction confidence scores and network topology, is proposed to calculate edge weights in PPI networks. The weight of each node is evaluated by the sum of WECC values of its linking edges. A random walk method, making use of both direct and indirect protein interactions, is then employed to calculate protein essentiality iteratively. Experimental results on the yeast PPI network show that EssRank outperforms most existing methods, including the most commonly-used centrality measures (SC, DC, BC, CC, IC, EC), topology based methods (DMNC and NC) and the data integrating method IEW.

  14. Styles of Creativity: Adaptors and Innovators in a Singapore Context

    Science.gov (United States)

    Ee, Jessie; Seng, Tan Oon; Kwang, Ng Aik

    2007-01-01

    Kirton (1976) described two creative styles, namely adaptors and innovators. Adaptors prefer to "do things better" whilst, innovators prefer to "do things differently". This study explored the relationship between two creative styles (adaptor and innovator) and the Big Five personality traits (extraversion, agreeableness, conscientiousness,…

  15. 21 CFR 870.3620 - Pacemaker lead adaptor.

    Science.gov (United States)

    2010-04-01

    ... 21 Food and Drugs 8 2010-04-01 2010-04-01 false Pacemaker lead adaptor. 870.3620 Section 870.3620...) MEDICAL DEVICES CARDIOVASCULAR DEVICES Cardiovascular Prosthetic Devices § 870.3620 Pacemaker lead adaptor. (a) Identification. A pacemaker lead adaptor is a device used to adapt a pacemaker lead so that it...

  16. Comparative Study of Elastic Network Model and Protein Contact Network for Protein Complexes: The Hemoglobin Case

    Directory of Open Access Journals (Sweden)

    Guang Hu

    2017-01-01

    Full Text Available The overall topology and interfacial interactions play key roles in understanding structural and functional principles of protein complexes. Elastic Network Model (ENM and Protein Contact Network (PCN are two widely used methods for high throughput investigation of structures and interactions within protein complexes. In this work, the comparative analysis of ENM and PCN relative to hemoglobin (Hb was taken as case study. We examine four types of structural and dynamical paradigms, namely, conformational change between different states of Hbs, modular analysis, allosteric mechanisms studies, and interface characterization of an Hb. The comparative study shows that ENM has an advantage in studying dynamical properties and protein-protein interfaces, while PCN is better for describing protein structures quantitatively both from local and from global levels. We suggest that the integration of ENM and PCN would give a potential but powerful tool in structural systems biology.

  17. HKC: An Algorithm to Predict Protein Complexes in Protein-Protein Interaction Networks

    Directory of Open Access Journals (Sweden)

    Xiaomin Wang

    2011-01-01

    Full Text Available With the availability of more and more genome-scale protein-protein interaction (PPI networks, research interests gradually shift to Systematic Analysis on these large data sets. A key topic is to predict protein complexes in PPI networks by identifying clusters that are densely connected within themselves but sparsely connected with the rest of the network. In this paper, we present a new topology-based algorithm, HKC, to detect protein complexes in genome-scale PPI networks. HKC mainly uses the concepts of highest k-core and cohesion to predict protein complexes by identifying overlapping clusters. The experiments on two data sets and two benchmarks show that our algorithm has relatively high F-measure and exhibits better performance compared with some other methods.

  18. Domain distribution and intrinsic disorder in hubs in the human protein–protein interaction network

    Science.gov (United States)

    Patil, Ashwini; Kinoshita, Kengo; Nakamura, Haruki

    2010-01-01

    Intrinsic disorder and distributed surface charge have been previously identified as some of the characteristics that differentiate hubs (proteins with a large number of interactions) from non-hubs in protein–protein interaction networks. In this study, we investigated the differences in the quantity, diversity, and functional nature of Pfam domains, and their relationship with intrinsic disorder, in hubs and non-hubs. We found that proteins with a more diverse domain composition were over-represented in hubs when compared with non-hubs, with the number of interactions in hubs increasing with domain diversity. Conversely, the fraction of intrinsic disorder in hubs decreased with increasing number of ordered domains. The difference in the levels of disorder was more prominent in hubs and non-hubs with fewer domains. Functional analysis showed that hubs were enriched in kinase and adaptor domains acting primarily in signal transduction and transcription regulation, whereas non-hubs had more DNA-binding domains and were involved in catalytic activity. Consistent with the differences in the functional nature of their domains, hubs with two or more domains were more likely to connect distinct functional modules in the interaction network when compared with single domain hubs. We conclude that the availability of greater number and diversity of ordered domains, in addition to the tendency to have promiscuous domains, differentiates hubs from non-hubs and provides an additional means of achieving interaction promiscuity. Further, hubs with fewer domains use greater levels of intrinsic disorder to facilitate interaction promiscuity with the prevalence of disorder decreasing with increasing number of ordered domains. PMID:20509167

  19. Discriminating lysosomal membrane protein types using dynamic neural network.

    Science.gov (United States)

    Tripathi, Vijay; Gupta, Dwijendra Kumar

    2014-01-01

    This work presents a dynamic artificial neural network methodology, which classifies the proteins into their classes from their sequences alone: the lysosomal membrane protein classes and the various other membranes protein classes. In this paper, neural networks-based lysosomal-associated membrane protein type prediction system is proposed. Different protein sequence representations are fused to extract the features of a protein sequence, which includes seven feature sets; amino acid (AA) composition, sequence length, hydrophobic group, electronic group, sum of hydrophobicity, R-group, and dipeptide composition. To reduce the dimensionality of the large feature vector, we applied the principal component analysis. The probabilistic neural network, generalized regression neural network, and Elman regression neural network (RNN) are used as classifiers and compared with layer recurrent network (LRN), a dynamic network. The dynamic networks have memory, i.e. its output depends not only on the input but the previous outputs also. Thus, the accuracy of LRN classifier among all other artificial neural networks comes out to be the highest. The overall accuracy of jackknife cross-validation is 93.2% for the data-set. These predicted results suggest that the method can be effectively applied to discriminate lysosomal associated membrane proteins from other membrane proteins (Type-I, Outer membrane proteins, GPI-Anchored) and Globular proteins, and it also indicates that the protein sequence representation can better reflect the core feature of membrane proteins than the classical AA composition.

  20. Analysis of core–periphery organization in protein contact networks ...

    Indian Academy of Sciences (India)

    2015-09-29

    Sep 29, 2015 ... The representation of proteins as networks of interacting amino acids, referred to as protein contact networks (PCN), and their subsequent analyses using graph theoretic tools, can provide novel insights into the key functional roles of specific groups of residues. We have characterized the networks ...

  1. Analysis of core–periphery organization in protein contact networks ...

    Indian Academy of Sciences (India)

    The representation of proteins as networks of interacting amino acids, referred to as protein contact networks (PCN), and their subsequent analyses using graph theoretic tools, can provide novel insights into the key functional roles of specific groups of residues. We have characterized the networks corresponding to the ...

  2. Protein function prediction using neighbor relativity in protein-protein interaction network.

    Science.gov (United States)

    Moosavi, Sobhan; Rahgozar, Masoud; Rahimi, Amir

    2013-04-01

    There is a large gap between the number of discovered proteins and the number of functionally annotated ones. Due to the high cost of determining protein function by wet-lab research, function prediction has become a major task for computational biology and bioinformatics. Some researches utilize the proteins interaction information to predict function for un-annotated proteins. In this paper, we propose a novel approach called "Neighbor Relativity Coefficient" (NRC) based on interaction network topology which estimates the functional similarity between two proteins. NRC is calculated for each pair of proteins based on their graph-based features including distance, common neighbors and the number of paths between them. In order to ascribe function to an un-annotated protein, NRC estimates a weight for each neighbor to transfer its annotation to the unknown protein. Finally, the unknown protein will be annotated by the top score transferred functions. We also investigate the effect of using different coefficients for various types of functions. The proposed method has been evaluated on Saccharomyces cerevisiae and Homo sapiens interaction networks. The performance analysis demonstrates that NRC yields better results in comparison with previous protein function prediction approaches that utilize interaction network. Copyright © 2012 Elsevier Ltd. All rights reserved.

  3. The Role of the Clathrin Adaptor AP-1: Polarized Sorting and Beyond

    Directory of Open Access Journals (Sweden)

    Fubito Nakatsu

    2014-11-01

    Full Text Available The selective transport of proteins or lipids by vesicular transport is a fundamental process supporting cellular physiology. The budding process involves cargo sorting and vesicle formation at the donor membrane and constitutes an important process in vesicular transport. This process is particularly important for the polarized sorting in epithelial cells, in which the cargo molecules need to be selectively sorted and transported to two distinct destinations, the apical or basolateral plasma membrane. Adaptor protein (AP-1, a member of the AP complex family, which includes the ubiquitously expressed AP-1A and the epithelium-specific AP-1B, regulates polarized sorting at the trans-Golgi network and/or at the recycling endosomes. A growing body of evidence, especially from studies using model organisms and animals, demonstrates that the AP-1-mediated polarized sorting supports the development and physiology of multi-cellular units as functional organs and tissues (e.g., cell fate determination, inflammation and gut immune homeostasis. Furthermore, a possible involvement of AP-1B in the pathogenesis of human diseases, such as Crohn’s disease and cancer, is now becoming evident. These data highlight the significant contribution of AP-1 complexes to the physiology of multicellular organisms, as master regulators of polarized sorting in epithelial cells.

  4. Modeling protein network evolution under genome duplication and domain shuffling

    Directory of Open Access Journals (Sweden)

    Isambert Hervé

    2007-11-01

    Full Text Available Abstract Background Successive whole genome duplications have recently been firmly established in all major eukaryote kingdoms. Such exponential evolutionary processes must have largely contributed to shape the topology of protein-protein interaction (PPI networks by outweighing, in particular, all time-linear network growths modeled so far. Results We propose and solve a mathematical model of PPI network evolution under successive genome duplications. This demonstrates, from first principles, that evolutionary conservation and scale-free topology are intrinsically linked properties of PPI networks and emerge from i prevailing exponential network dynamics under duplication and ii asymmetric divergence of gene duplicates. While required, we argue that this asymmetric divergence arises, in fact, spontaneously at the level of protein-binding sites. This supports a refined model of PPI network evolution in terms of protein domains under exponential and asymmetric duplication/divergence dynamics, with multidomain proteins underlying the combinatorial formation of protein complexes. Genome duplication then provides a powerful source of PPI network innovation by promoting local rearrangements of multidomain proteins on a genome wide scale. Yet, we show that the overall conservation and topology of PPI networks are robust to extensive domain shuffling of multidomain proteins as well as to finer details of protein interaction and evolution. Finally, large scale features of direct and indirect PPI networks of S. cerevisiae are well reproduced numerically with only two adjusted parameters of clear biological significance (i.e. network effective growth rate and average number of protein-binding domains per protein. Conclusion This study demonstrates the statistical consequences of genome duplication and domain shuffling on the conservation and topology of PPI networks over a broad evolutionary scale across eukaryote kingdoms. In particular, scale

  5. 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.

  6. Analysis of protein-protein interaction networks by means of annotated graph mining algorithms

    NARCIS (Netherlands)

    Rahmani, Hossein

    2012-01-01

    This thesis discusses solutions to several open problems in Protein-Protein Interaction (PPI) networks with the aid of Knowledge Discovery. PPI networks are usually represented as undirected graphs, with nodes corresponding to proteins and edges representing interactions among protein pairs. A large

  7. Building protein-protein interaction networks for Leishmania species through protein structural information.

    Science.gov (United States)

    Dos Santos Vasconcelos, Crhisllane Rafaele; de Lima Campos, Túlio; Rezende, Antonio Mauro

    2018-03-06

    Systematic analysis of a parasite interactome is a key approach to understand different biological processes. It makes possible to elucidate disease mechanisms, to predict protein functions and to select promising targets for drug development. Currently, several approaches for protein interaction prediction for non-model species incorporate only small fractions of the entire proteomes and their interactions. Based on this perspective, this study presents an integration of computational methodologies, protein network predictions and comparative analysis of the protozoan species Leishmania braziliensis and Leishmania infantum. These parasites cause Leishmaniasis, a worldwide distributed and neglected disease, with limited treatment options using currently available drugs. The predicted interactions were obtained from a meta-approach, applying rigid body docking tests and template-based docking on protein structures predicted by different comparative modeling techniques. In addition, we trained a machine-learning algorithm (Gradient Boosting) using docking information performed on a curated set of positive and negative protein interaction data. Our final model obtained an AUC = 0.88, with recall = 0.69, specificity = 0.88 and precision = 0.83. Using this approach, it was possible to confidently predict 681 protein structures and 6198 protein interactions for L. braziliensis, and 708 protein structures and 7391 protein interactions for L. infantum. The predicted networks were integrated to protein interaction data already available, analyzed using several topological features and used to classify proteins as essential for network stability. The present study allowed to demonstrate the importance of integrating different methodologies of interaction prediction to increase the coverage of the protein interaction of the studied protocols, besides it made available protein structures and interactions not previously reported.

  8. Detecting overlapping protein complexes by rough-fuzzy clustering in protein-protein interaction networks.

    Science.gov (United States)

    Wu, Hao; Gao, Lin; Dong, Jihua; Yang, Xiaofei

    2014-01-01

    In this paper, we present a novel rough-fuzzy clustering (RFC) method to detect overlapping protein complexes in protein-protein interaction (PPI) networks. RFC focuses on fuzzy relation model rather than graph model by integrating fuzzy sets and rough sets, employs the upper and lower approximations of rough sets to deal with overlapping complexes, and calculates the number of complexes automatically. Fuzzy relation between proteins is established and then transformed into fuzzy equivalence relation. Non-overlapping complexes correspond to equivalence classes satisfying certain equivalence relation. To obtain overlapping complexes, we calculate the similarity between one protein and each complex, and then determine whether the protein belongs to one or multiple complexes by computing the ratio of each similarity to maximum similarity. To validate RFC quantitatively, we test it in Gavin, Collins, Krogan and BioGRID datasets. Experiment results show that there is a good correspondence to reference complexes in MIPS and SGD databases. Then we compare RFC with several previous methods, including ClusterONE, CMC, MCL, GCE, OSLOM and CFinder. Results show the precision, sensitivity and separation are 32.4%, 42.9% and 81.9% higher than mean of the five methods in four weighted networks, and are 0.5%, 11.2% and 66.1% higher than mean of the six methods in five unweighted networks. Our method RFC works well for protein complexes detection and provides a new insight of network division, and it can also be applied to identify overlapping community structure in social networks and LFR benchmark networks.

  9. RAIN: RNA-protein Association and Interaction Networks

    DEFF Research Database (Denmark)

    Junge, Alexander; Refsgaard, Jan Christian; Garde, Christian

    2017-01-01

    Protein association networks can be inferred from a range of resources including experimental data, literature mining and computational predictions. These types of evidence are emerging for non-coding RNAs (ncRNAs) as well. However, integration of ncRNAs into protein association networks...

  10. The architectural design of networks of protein domain architectures.

    Science.gov (United States)

    Hsu, Chia-Hsin; Chen, Chien-Kuo; Hwang, Ming-Jing

    2013-08-23

    Protein domain architectures (PDAs), in which single domains are linked to form multiple-domain proteins, are a major molecular form used by evolution for the diversification of protein functions. However, the design principles of PDAs remain largely uninvestigated. In this study, we constructed networks to connect domain architectures that had grown out from the same single domain for every single domain in the Pfam-A database and found that there are three main distinctive types of these networks, which suggests that evolution can exploit PDAs in three different ways. Further analysis showed that these three different types of PDA networks are each adopted by different types of protein domains, although many networks exhibit the characteristics of more than one of the three types. Our results shed light on nature's blueprint for protein architecture and provide a framework for understanding architectural design from a network perspective.

  11. Small world network strategies for studying protein structures and binding.

    Science.gov (United States)

    Taylor, Neil R

    2013-01-01

    Small world network concepts provide many new opportunities to investigate the complex three dimensional structures of protein molecules. This mini-review explores the published literature on using small-world network approaches to study protein structure, with emphasis on the different combinations of descriptors that have been tested, on studies involving ligand binding in protein-ligand complexes, and on protein-protein complexes. The benefits and success of small world network approaches, which change the focus from specific interactions to the local environment, even to non-local phenomenon, are described. The purpose is to show the different ways that small world network concepts have been used for building new computational models for studying protein structure and function, and for extending and improving existing modelling approaches.

  12. TRAM is involved in IL-18 signaling and functions as a sorting adaptor for MyD88.

    Directory of Open Access Journals (Sweden)

    Hidenori Ohnishi

    Full Text Available MyD88, a Toll/interleukin-1 receptor homology (TIR domain-containing adaptor protein, mediates signals from the Toll-like receptors (TLR or IL-1/IL-18 receptors to downstream kinases. In MyD88-dependent TLR4 signaling, the function of MyD88 is enhanced by another TIR domain-containing adaptor, Mal/TIRAP, which brings MyD88 to the plasma membrane and promotes its interaction with the cytosolic region of TLR4. Hence, Mal is recognized as the "sorting adaptor" for MyD88. In this study, a direct interaction between MyD88-TIR and another membrane-sorting adaptor, TRAM/TICAM-2, was demonstrated in vitro. Cell-based assays including RNA interference experiments and TRAM deficient mice revealed that the interplay between MyD88 and TRAM in cells is important in mediating IL-18 signal transduction. Live cell imaging further demonstrated the co-localized accumulation of MyD88 and TRAM in the membrane regions in HEK293 cells. These findings suggest that TRAM serves as the sorting adaptor for MyD88 in IL-18 signaling, which then facilitates the signal transduction. The binding sites for TRAM are located in the TIR domain of MyD88 and actually overlap with the binding sites for Mal. MyD88, the multifunctional signaling adaptor that works together with most of the TLR members and with the IL-1/IL-18 receptors, can interact with two distinct sorting adaptors, TRAM and Mal, in a conserved manner in a distinct context.

  13. Evidence of probabilistic behaviour in protein interaction networks.

    Science.gov (United States)

    Ivanic, Joseph; Wallqvist, Anders; Reifman, Jaques

    2008-01-31

    Data from high-throughput experiments of protein-protein interactions are commonly used to probe the nature of biological organization and extract functional relationships between sets of proteins. What has not been appreciated is that the underlying mechanisms involved in assembling these networks may exhibit considerable probabilistic behaviour. We find that the probability of an interaction between two proteins is generally proportional to the numerical product of their individual interacting partners, or degrees. The degree-weighted behaviour is manifested throughout the protein-protein interaction networks studied here, except for the high-degree, or hub, interaction areas. However, we find that the probabilities of interaction between the hubs are still high. Further evidence is provided by path length analyses, which show that these hubs are separated by very few links. The results suggest that protein-protein interaction networks incorporate probabilistic elements that lead to scale-rich hierarchical architectures. These observations seem to be at odds with a biologically-guided organization. One interpretation of the findings is that we are witnessing the ability of proteins to indiscriminately bind rather than the protein-protein interactions that are actually utilized by the cell in biological processes. Therefore, the topological study of a degree-weighted network requires a more refined methodology to extract biological information about pathways, modules, or other inferred relationships among proteins.

  14. Evidence of probabilistic behaviour in protein interaction networks

    Directory of Open Access Journals (Sweden)

    Reifman Jaques

    2008-01-01

    Full Text Available Abstract Background Data from high-throughput experiments of protein-protein interactions are commonly used to probe the nature of biological organization and extract functional relationships between sets of proteins. What has not been appreciated is that the underlying mechanisms involved in assembling these networks may exhibit considerable probabilistic behaviour. Results We find that the probability of an interaction between two proteins is generally proportional to the numerical product of their individual interacting partners, or degrees. The degree-weighted behaviour is manifested throughout the protein-protein interaction networks studied here, except for the high-degree, or hub, interaction areas. However, we find that the probabilities of interaction between the hubs are still high. Further evidence is provided by path length analyses, which show that these hubs are separated by very few links. Conclusion The results suggest that protein-protein interaction networks incorporate probabilistic elements that lead to scale-rich hierarchical architectures. These observations seem to be at odds with a biologically-guided organization. One interpretation of the findings is that we are witnessing the ability of proteins to indiscriminately bind rather than the protein-protein interactions that are actually utilized by the cell in biological processes. Therefore, the topological study of a degree-weighted network requires a more refined methodology to extract biological information about pathways, modules, or other inferred relationships among proteins.

  15. A potential role for the clathrin adaptor GGA in Drosophila spermatogenesis

    Directory of Open Access Journals (Sweden)

    Carmichael Jenny

    2011-05-01

    Full Text Available Abstract Background GGAs (Golgi-localised, γ-ear containing, ADP ribosylation factor-binding are a family of clathrin adaptors that sort a number of biologically important transmembrane proteins into clathrin-coated vesicles. Knockout and knockdown studies to determine GGA function are confounded by the fact that there are 3 GGA genes in mammalian cells. Thus Drosophila melanogaster is a useful model system to study tissue expression profiles and knockdown phenotypes as there is a single GGA ortholog. Results Here we have quantified protein expression in Drosophila and show that there is >3-fold higher expression of GGA in male flies relative to female flies. In female flies the majority of GGA expression is in the head. In male flies GGA is not only expressed at high levels in the head but there is a gender specific increased expression which is due to the abundant expression of GGA in the testes. Using a highly specific antibody we have localised endogenous GGA protein in testes squashes, and visualised it in somatic and germ line cells. We show that GGA is expressed during multiple stages of sperm development, and co-stains with a marker of the trans-Golgi Network. This is most striking at the acroblast of early spermatids. In spite of the high expression of GGA in testes, knocking down its expression by >95% using transgenic RNAi fly lines did not affect male fertility. Therefore spermatogenesis in the male flies appears to progress normally with Conclusion In Drosophila we have uncovered a potential role for GGA in the testes of male flies. The gender specific higher expression of GGA, its specific enrichment in testes and its localisation to developing spermatocytes and at the acroblast of spermatids supports a role for GGA function in Drosophila spermatogenesis, even though spermatogenesis still occurs when GGA expression is depleted to

  16. Probing the extent of randomness in protein interaction networks.

    Directory of Open Access Journals (Sweden)

    Joseph Ivanic

    Full Text Available Protein-protein interaction (PPI networks are commonly explored for the identification of distinctive biological traits, such as pathways, modules, and functional motifs. In this respect, understanding the underlying network structure is vital to assess the significance of any discovered features. We recently demonstrated that PPI networks show degree-weighted behavior, whereby the probability of interaction between two proteins is generally proportional to the product of their numbers of interacting partners or degrees. It was surmised that degree-weighted behavior is a characteristic of randomness. We expand upon these findings by developing a random, degree-weighted, network model and show that eight PPI networks determined from single high-throughput (HT experiments have global and local properties that are consistent with this model. The apparent random connectivity in HT PPI networks is counter-intuitive with respect to their observed degree distributions; however, we resolve this discrepancy by introducing a non-network-based model for the evolution of protein degrees or "binding affinities." This mechanism is based on duplication and random mutation, for which the degree distribution converges to a steady state that is identical to one obtained by averaging over the eight HT PPI networks. The results imply that the degrees and connectivities incorporated in HT PPI networks are characteristic of unbiased interactions between proteins that have varying individual binding affinities. These findings corroborate the observation that curated and high-confidence PPI networks are distinct from HT PPI networks and not consistent with a random connectivity. These results provide an avenue to discern indiscriminate organizations in biological networks and suggest caution in the analysis of curated and high-confidence networks.

  17. Probing the extent of randomness in protein interaction networks.

    Science.gov (United States)

    Ivanic, Joseph; Wallqvist, Anders; Reifman, Jaques

    2008-07-11

    Protein-protein interaction (PPI) networks are commonly explored for the identification of distinctive biological traits, such as pathways, modules, and functional motifs. In this respect, understanding the underlying network structure is vital to assess the significance of any discovered features. We recently demonstrated that PPI networks show degree-weighted behavior, whereby the probability of interaction between two proteins is generally proportional to the product of their numbers of interacting partners or degrees. It was surmised that degree-weighted behavior is a characteristic of randomness. We expand upon these findings by developing a random, degree-weighted, network model and show that eight PPI networks determined from single high-throughput (HT) experiments have global and local properties that are consistent with this model. The apparent random connectivity in HT PPI networks is counter-intuitive with respect to their observed degree distributions; however, we resolve this discrepancy by introducing a non-network-based model for the evolution of protein degrees or "binding affinities." This mechanism is based on duplication and random mutation, for which the degree distribution converges to a steady state that is identical to one obtained by averaging over the eight HT PPI networks. The results imply that the degrees and connectivities incorporated in HT PPI networks are characteristic of unbiased interactions between proteins that have varying individual binding affinities. These findings corroborate the observation that curated and high-confidence PPI networks are distinct from HT PPI networks and not consistent with a random connectivity. These results provide an avenue to discern indiscriminate organizations in biological networks and suggest caution in the analysis of curated and high-confidence networks.

  18. Role of the epithelial cell-specific clathrin adaptor complex AP-1B in cell polarity

    Science.gov (United States)

    Fölsch, Heike

    2015-01-01

    Epithelial cells are important for organ development and function. To this end, they polarize their plasma membrane into biochemically and physically distinct membrane domains. The apical membrane faces the luminal site of an organ and the basolateral domain is in contact with the basement membrane and neighboring cells. To establish and maintain this polarity it is important that newly synthesized and endocytic cargos are correctly sorted according to their final destinations at either membrane. Sorting takes place at one of 2 major sorting stations in the cells, the trans-Golgi network (TGN) and recycling endosomes (REs). Polarized sorting may involve epithelial cell-specific sorting adaptors like the AP-1B clathrin adaptor complex. AP-1B facilitates basolateral sorting from REs. This review will discuss various aspects of basolateral sorting in epithelial cells with a special emphasis on AP-1B. PMID:27057418

  19. Convolutional LSTM Networks for Subcellular Localization of Proteins

    DEFF Research Database (Denmark)

    Sønderby, Søren Kaae; Sønderby, Casper Kaae; Nielsen, Henrik

    2015-01-01

    Machine learning is widely used to analyze biological sequence data. Non-sequential models such as SVMs or feed-forward neural networks are often used although they have no natural way of handling sequences of varying length. Recurrent neural networks such as the long short term memory (LSTM) model...... on the other hand are designed to handle sequences. In this study we demonstrate that LSTM networks predict the subcellular location of proteins given only the protein sequence with high accuracy (0.902) outperforming current state of the art algorithms. We further improve the performance by introducing...... the LSTM networks....

  20. Combining neural networks for protein secondary structure prediction

    DEFF Research Database (Denmark)

    Riis, Søren Kamaric

    1995-01-01

    In this paper structured neural networks are applied to the problem of predicting the secondary structure of proteins. A hierarchical approach is used where specialized neural networks are designed for each structural class and then combined using another neural network. The submodels are designed...... by using a priori knowledge of the mapping between protein building blocks and the secondary structure and by using weight sharing. Since none of the individual networks have more than 600 adjustable weights over-fitting is avoided. When ensembles of specialized experts are combined the performance...... is better than most secondary structure prediction methods based on single sequences even though this model contains much fewer parameters...

  1. Evolution of a protein domain interaction network

    International Nuclear Information System (INIS)

    Li-Feng, Gao; Jian-Jun, Shi; Shan, Guan

    2010-01-01

    In this paper, we attempt to understand complex network evolution from the underlying evolutionary relationship between biological organisms. Firstly, we construct a Pfam domain interaction network for each of the 470 completely sequenced organisms, and therefore each organism is correlated with a specific Pfam domain interaction network; secondly, we infer the evolutionary relationship of these organisms with the nearest neighbour joining method; thirdly, we use the evolutionary relationship between organisms constructed in the second step as the evolutionary course of the Pfam domain interaction network constructed in the first step. This analysis of the evolutionary course shows: (i) there is a conserved sub-network structure in network evolution; in this sub-network, nodes with lower degree prefer to maintain their connectivity invariant, and hubs tend to maintain their role as a hub is attached preferentially to new added nodes; (ii) few nodes are conserved as hubs; most of the other nodes are conserved as one with very low degree; (iii) in the course of network evolution, new nodes are added to the network either individually in most cases or as clusters with relative high clustering coefficients in a very few cases. (general)

  2. Analysis of protein folds using protein contact networks

    Indian Academy of Sciences (India)

    Proteins are important biomolecules, which perform diverse structural and functional roles in living systems. Starting from a .... even be extended up to the level of protein secondary structural elements, as seen in protein topology cartoons [13]. Even though ... chemical interactions [8]. This distance map is a 2D symmetric, ...

  3. CNNcon: improved protein contact maps prediction using cascaded neural networks.

    Directory of Open Access Journals (Sweden)

    Wang Ding

    Full Text Available BACKGROUNDS: Despite continuing progress in X-ray crystallography and high-field NMR spectroscopy for determination of three-dimensional protein structures, the number of unsolved and newly discovered sequences grows much faster than that of determined structures. Protein modeling methods can possibly bridge this huge sequence-structure gap with the development of computational science. A grand challenging problem is to predict three-dimensional protein structure from its primary structure (residues sequence alone. However, predicting residue contact maps is a crucial and promising intermediate step towards final three-dimensional structure prediction. Better predictions of local and non-local contacts between residues can transform protein sequence alignment to structure alignment, which can finally improve template based three-dimensional protein structure predictors greatly. METHODS: CNNcon, an improved multiple neural networks based contact map predictor using six sub-networks and one final cascade-network, was developed in this paper. Both the sub-networks and the final cascade-network were trained and tested with their corresponding data sets. While for testing, the target protein was first coded and then input to its corresponding sub-networks for prediction. After that, the intermediate results were input to the cascade-network to finish the final prediction. RESULTS: The CNNcon can accurately predict 58.86% in average of contacts at a distance cutoff of 8 Å for proteins with lengths ranging from 51 to 450. The comparison results show that the present method performs better than the compared state-of-the-art predictors. Particularly, the prediction accuracy keeps steady with the increase of protein sequence length. It indicates that the CNNcon overcomes the thin density problem, with which other current predictors have trouble. This advantage makes the method valuable to the prediction of long length proteins. As a result, the effective

  4. Fluctuations in Mass-Action Equilibrium of Protein Binding Networks

    Science.gov (United States)

    Yan, Koon-Kiu; Walker, Dylan; Maslov, Sergei

    2008-12-01

    We consider two types of fluctuations in the mass-action equilibrium in protein binding networks. The first type is driven by slow changes in total concentrations of interacting proteins. The second type (spontaneous) is caused by quickly decaying thermodynamic deviations away from equilibrium. We investigate the effects of network connectivity on fluctuations by comparing them to scenarios in which the interacting pair is isolated from the network and analytically derives bounds on fluctuations. Collective effects are shown to sometimes lead to large amplification of spontaneous fluctuations. The strength of both types of fluctuations is positively correlated with the complex connectivity and negatively correlated with complex concentration. Our general findings are illustrated using a curated network of protein interactions and multiprotein complexes in baker’s yeast, with empirical protein concentrations.

  5. NatalieQ: A web server for protein-protein interaction network querying

    NARCIS (Netherlands)

    El-Kebir, M.; Brandt, B.W.; Heringa, J.; Klau, G.W.

    2014-01-01

    Background Molecular interactions need to be taken into account to adequately model the complex behavior of biological systems. These interactions are captured by various types of biological networks, such as metabolic, gene-regulatory, signal transduction and protein-protein interaction networks.

  6. NatalieQ: a web server for protein-protein interaction network querying

    NARCIS (Netherlands)

    El-Kebir, M.; Brandt, B.W.; Heringa, J.; Klau, G.W.

    2014-01-01

    Background: Molecular interactions need to be taken into account to adequately model the complex behavior of biological systems. These interactions are captured by various types of biological networks, such as metabolic, gene-regulatory, signal transduction and protein-protein interaction networks.

  7. Rapid Sampling of Hydrogen Bond Networks for Computational Protein Design.

    Science.gov (United States)

    Maguire, Jack B; Boyken, Scott E; Baker, David; Kuhlman, Brian

    2018-04-20

    Hydrogen bond networks play a critical role in determining the stability and specificity of biomolecular complexes, and the ability to design such networks is important for engineering novel structures, interactions, and enzymes. One key feature of hydrogen bond networks that makes them difficult to rationally engineer is that they are highly cooperative and are not energetically favorable until the hydrogen bonding potential has been satisfied for all buried polar groups in the network. Existing computational methods for protein design are ill-equipped for creating these highly cooperative networks because they rely on energy functions and sampling strategies that are focused on pairwise interactions. To enable the design of complex hydrogen bond networks, we have developed a new sampling protocol in the molecular modeling program Rosetta that explicitly searches for sets of amino acid mutations that can form self-contained hydrogen bond networks. For a given set of designable residues, the protocol often identifies many alternative sets of mutations/networks, and we show that it can readily be applied to large sets of residues at protein-protein interfaces or in the interior of proteins. The protocol builds on a recently developed method in Rosetta for designing hydrogen bond networks that has been experimentally validated for small symmetric systems but was not extensible to many larger protein structures and complexes. The sampling protocol we describe here not only recapitulates previously validated designs with performance improvements but also yields viable hydrogen bond networks for cases where the previous method fails, such as the design of large, asymmetric interfaces relevant to engineering protein-based therapeutics.

  8. Topological properties of complex networks in protein structures

    Science.gov (United States)

    Kim, Kyungsik; Jung, Jae-Won; Min, Seungsik

    2014-03-01

    We study topological properties of networks in structural classification of proteins. We model the native-state protein structure as a network made of its constituent amino-acids and their interactions. We treat four structural classes of proteins composed predominantly of α helices and β sheets and consider several proteins from each of these classes whose sizes range from amino acids of the Protein Data Bank. Particularly, we simulate and analyze the network metrics such as the mean degree, the probability distribution of degree, the clustering coefficient, the characteristic path length, the local efficiency, and the cost. This work was supported by the KMAR and DP under Grant WISE project (153-3100-3133-302-350).

  9. NETAL: a new graph-based method for global alignment of protein-protein interaction networks.

    Science.gov (United States)

    Neyshabur, Behnam; Khadem, Ahmadreza; Hashemifar, Somaye; Arab, Seyed Shahriar

    2013-07-01

    The interactions among proteins and the resulting networks of such interactions have a central role in cell biology. Aligning these networks gives us important information, such as conserved complexes and evolutionary relationships. Although there have been several publications on the global alignment of protein networks; however, none of proposed methods are able to produce a highly conserved and meaningful alignment. Moreover, time complexity of current algorithms makes them impossible to use for multiple alignment of several large networks together. We present a novel algorithm for the global alignment of protein-protein interaction networks. It uses a greedy method, based on the alignment scoring matrix, which is derived from both biological and topological information of input networks to find the best global network alignment. NETAL outperforms other global alignment methods in terms of several measurements, such as Edge Correctness, Largest Common Connected Subgraphs and the number of common Gene Ontology terms between aligned proteins. As the running time of NETAL is much less than other available methods, NETAL can be easily expanded to multiple alignment algorithm. Furthermore, NETAL overpowers all other existing algorithms in term of performance so that the short running time of NETAL allowed us to implement it as the first server for global alignment of protein-protein interaction networks. Binaries supported on linux are freely available for download at http://www.bioinf.cs.ipm.ir/software/netal. Supplementary data are available at Bioinformatics online.

  10. Analysis of protein folds using protein contact networks

    Indian Academy of Sciences (India)

    Proteins are important biomolecules, which perform diverse structural and functional roles in living systems. Starting from a linear chain of amino acids, proteins fold to different secondary structures, which then fold through short- and long-range interactions to give rise to the final three-dimensional shapes useful to carry out ...

  11. Predicting and validating protein interactions using network structure.

    Directory of Open Access Journals (Sweden)

    Pao-Yang Chen

    2008-07-01

    Full Text Available Protein interactions play a vital part in the function of a cell. As experimental techniques for detection and validation of protein interactions are time consuming, there is a need for computational methods for this task. Protein interactions appear to form a network with a relatively high degree of local clustering. In this paper we exploit this clustering by suggesting a score based on triplets of observed protein interactions. The score utilises both protein characteristics and network properties. Our score based on triplets is shown to complement existing techniques for predicting protein interactions, outperforming them on data sets which display a high degree of clustering. The predicted interactions score highly against test measures for accuracy. Compared to a similar score derived from pairwise interactions only, the triplet score displays higher sensitivity and specificity. By looking at specific examples, we show how an experimental set of interactions can be enriched and validated. As part of this work we also examine the effect of different prior databases upon the accuracy of prediction and find that the interactions from the same kingdom give better results than from across kingdoms, suggesting that there may be fundamental differences between the networks. These results all emphasize that network structure is important and helps in the accurate prediction of protein interactions. The protein interaction data set and the program used in our analysis, and a list of predictions and validations, are available at http://www.stats.ox.ac.uk/bioinfo/resources/PredictingInteractions.

  12. Advanced path sampling of the kinetic network of small proteins

    NARCIS (Netherlands)

    Du, W.

    2014-01-01

    This thesis is focused on developing advanced path sampling simulation methods to study protein folding and unfolding, and to build kinetic equilibrium networks describing these processes. In Chapter 1 the basic knowledge of protein structure and folding theories were introduced and a brief overview

  13. Dynamic rheology of food protein networks

    Science.gov (United States)

    Small amplitude oscillatory shear analyses of samples containing protein are useful for determining the nature of the protein matrix without damaging it. Elastic modulus, viscous modulus, and loss tangent (the ratio of viscous modulus to elastic modulus) give information on the strength of the netw...

  14. Computational Modeling of Complex Protein Activity Networks

    NARCIS (Netherlands)

    Schivo, Stefano; Leijten, Jeroen; Karperien, Marcel; Post, Janine N.; Prignet, Claude

    2017-01-01

    Because of the numerous entities interacting, the complexity of the networks that regulate cell fate makes it impossible to analyze and understand them using the human brain alone. Computational modeling is a powerful method to unravel complex systems. We recently described the development of a

  15. Protein diffusion in photopolymerized poly(ethylene glycol) hydrogel networks

    Energy Technology Data Exchange (ETDEWEB)

    Engberg, Kristin; Frank, Curtis W, E-mail: curt.frank@stanford.edu [Department of Chemical Engineering, Stanford University, 381 North-South Mall, Stauffer III, Stanford, CA 94305 (United States)

    2011-10-15

    In this study, protein diffusion through swollen hydrogel networks prepared from end-linked poly(ethylene glycol)-diacrylate (PEG-DA) was investigated. Hydrogels were prepared via photopolymerization from PEG-DA macromonomer solutions of two molecular weights, 4600 Da and 8000 Da, with three initial solid contents: 20, 33 and 50 wt/wt% PEG. Diffusion coefficients for myoglobin traveling across the hydrogel membrane were determined for all PEG network compositions. The diffusion coefficient depended on PEG molecular weight and initial solid content, with the slowest diffusion occurring through lower molecular weight, high-solid-content networks (D{sub gel} = 0.16 {+-} 0.02 x 10{sup -8} cm{sup 2} s{sup -1}) and the fastest diffusion occurring through higher molecular weight, low-solid-content networks (D{sub gel} = 11.05 {+-} 0.43 x 10{sup -8} cm{sup 2} s{sup -1}). Myoglobin diffusion coefficients increased linearly with the increase of water content within the hydrogels. The permeability of three larger model proteins (horseradish peroxidase, bovine serum albumin and immunoglobulin G) through PEG(8000) hydrogel membranes was also examined, with the observation that globular molecules as large as 10.7 nm in hydrodynamic diameter can diffuse through the PEG network. Protein diffusion coefficients within the PEG hydrogels ranged from one to two orders of magnitude lower than the diffusion coefficients in free water. Network defects were determined to be a significant contributing factor to the observed protein diffusion.

  16. Protein diffusion in photopolymerized poly(ethylene glycol) hydrogel networks

    International Nuclear Information System (INIS)

    Engberg, Kristin; Frank, Curtis W

    2011-01-01

    In this study, protein diffusion through swollen hydrogel networks prepared from end-linked poly(ethylene glycol)-diacrylate (PEG-DA) was investigated. Hydrogels were prepared via photopolymerization from PEG-DA macromonomer solutions of two molecular weights, 4600 Da and 8000 Da, with three initial solid contents: 20, 33 and 50 wt/wt% PEG. Diffusion coefficients for myoglobin traveling across the hydrogel membrane were determined for all PEG network compositions. The diffusion coefficient depended on PEG molecular weight and initial solid content, with the slowest diffusion occurring through lower molecular weight, high-solid-content networks (D gel = 0.16 ± 0.02 x 10 -8 cm 2 s -1 ) and the fastest diffusion occurring through higher molecular weight, low-solid-content networks (D gel = 11.05 ± 0.43 x 10 -8 cm 2 s -1 ). Myoglobin diffusion coefficients increased linearly with the increase of water content within the hydrogels. The permeability of three larger model proteins (horseradish peroxidase, bovine serum albumin and immunoglobulin G) through PEG(8000) hydrogel membranes was also examined, with the observation that globular molecules as large as 10.7 nm in hydrodynamic diameter can diffuse through the PEG network. Protein diffusion coefficients within the PEG hydrogels ranged from one to two orders of magnitude lower than the diffusion coefficients in free water. Network defects were determined to be a significant contributing factor to the observed protein diffusion.

  17. Using the clustered circular layout as an informative method for visualizing protein-protein interaction networks.

    Science.gov (United States)

    Fung, David C Y; Wilkins, Marc R; Hart, David; Hong, Seok-Hee

    2010-07-01

    The force-directed layout is commonly used in computer-generated visualizations of protein-protein interaction networks. While it is good for providing a visual outline of the protein complexes and their interactions, it has two limitations when used as a visual analysis method. The first is poor reproducibility. Repeated running of the algorithm does not necessarily generate the same layout, therefore, demanding cognitive readaptation on the investigator's part. The second limitation is that it does not explicitly display complementary biological information, e.g. Gene Ontology, other than the protein names or gene symbols. Here, we present an alternative layout called the clustered circular layout. Using the human DNA replication protein-protein interaction network as a case study, we compared the two network layouts for their merits and limitations in supporting visual analysis.

  18. Emergence of modularity and disassortativity in protein-protein interaction networks.

    Science.gov (United States)

    Wan, Xi; Cai, Shuiming; Zhou, Jin; Liu, Zengrong

    2010-12-01

    In this paper, we present a simple evolution model of protein-protein interaction networks by introducing a rule of small-preference duplication of a node, meaning that the probability of a node chosen to duplicate is inversely proportional to its degree, and subsequent divergence plus nonuniform heterodimerization based on some plausible mechanisms in biology. We show that our model cannot only reproduce scale-free connectivity and small-world pattern, but also exhibit hierarchical modularity and disassortativity. After comparing the features of our model with those of real protein-protein interaction networks, we believe that our model can provide relevant insights into the mechanism underlying the evolution of protein-protein interaction networks. © 2010 American Institute of Physics.

  19. Distinctive Behaviors of Druggable Proteins in Cellular Networks.

    Directory of Open Access Journals (Sweden)

    Costas Mitsopoulos

    2015-12-01

    Full Text Available The interaction environment of a protein in a cellular network is important in defining the role that the protein plays in the system as a whole, and thus its potential suitability as a drug target. Despite the importance of the network environment, it is neglected during target selection for drug discovery. Here, we present the first systematic, comprehensive computational analysis of topological, community and graphical network parameters of the human interactome and identify discriminatory network patterns that strongly distinguish drug targets from the interactome as a whole. Importantly, we identify striking differences in the network behavior of targets of cancer drugs versus targets from other therapeutic areas and explore how they may relate to successful drug combinations to overcome acquired resistance to cancer drugs. We develop, computationally validate and provide the first public domain predictive algorithm for identifying druggable neighborhoods based on network parameters. We also make available full predictions for 13,345 proteins to aid target selection for drug discovery. All target predictions are available through canSAR.icr.ac.uk. Underlying data and tools are available at https://cansar.icr.ac.uk/cansar/publications/druggable_network_neighbourhoods/.

  20. Distinctive Behaviors of Druggable Proteins in Cellular Networks.

    Science.gov (United States)

    Mitsopoulos, Costas; Schierz, Amanda C; Workman, Paul; Al-Lazikani, Bissan

    2015-12-01

    The interaction environment of a protein in a cellular network is important in defining the role that the protein plays in the system as a whole, and thus its potential suitability as a drug target. Despite the importance of the network environment, it is neglected during target selection for drug discovery. Here, we present the first systematic, comprehensive computational analysis of topological, community and graphical network parameters of the human interactome and identify discriminatory network patterns that strongly distinguish drug targets from the interactome as a whole. Importantly, we identify striking differences in the network behavior of targets of cancer drugs versus targets from other therapeutic areas and explore how they may relate to successful drug combinations to overcome acquired resistance to cancer drugs. We develop, computationally validate and provide the first public domain predictive algorithm for identifying druggable neighborhoods based on network parameters. We also make available full predictions for 13,345 proteins to aid target selection for drug discovery. All target predictions are available through canSAR.icr.ac.uk. Underlying data and tools are available at https://cansar.icr.ac.uk/cansar/publications/druggable_network_neighbourhoods/.

  1. Analysis of protein folds using protein contact networks

    Indian Academy of Sciences (India)

    range in- teractions to give rise to the final three-dimensional ... data. As defined by SCOP, there exist several hierarchies. The principal levels are family, superfamily, fold and class. According to SCOP, proteins clustered together into families are ...

  2. Response of the mosquito protein interaction network to dengue infection

    Directory of Open Access Journals (Sweden)

    Pike Andrew D

    2010-06-01

    Full Text Available Abstract Background Two fifths of the world's population is at risk from dengue. The absence of effective drugs and vaccines leaves vector control as the primary intervention tool. Understanding dengue virus (DENV host interactions is essential for the development of novel control strategies. The availability of genome sequences for both human and mosquito host greatly facilitates genome-wide studies of DENV-host interactions. Results We developed the first draft of the mosquito protein interaction network using a computational approach. The weighted network includes 4,214 Aedes aegypti proteins with 10,209 interactions, among which 3,500 proteins are connected into an interconnected scale-free network. We demonstrated the application of this network for the further annotation of mosquito proteins and dissection of pathway crosstalk. Using three datasets based on physical interaction assays, genome-wide RNA interference (RNAi screens and microarray assays, we identified 714 putative DENV-associated mosquito proteins. An integrated analysis of these proteins in the network highlighted four regions consisting of highly interconnected proteins with closely related functions in each of replication/transcription/translation (RTT, immunity, transport and metabolism. Putative DENV-associated proteins were further selected for validation by RNAi-mediated gene silencing, and dengue viral titer in mosquito midguts was significantly reduced for five out of ten (50.0% randomly selected genes. Conclusions Our results indicate the presence of common host requirements for DENV in mosquitoes and humans. We discuss the significance of our findings for pharmacological intervention and genetic modification of mosquitoes for blocking dengue transmission.

  3. A scored human protein-protein interaction network to catalyze genomic interpretation

    DEFF Research Database (Denmark)

    Li, Taibo; Wernersson, Rasmus; Hansen, Rasmus B

    2017-01-01

    Genome-scale human protein-protein interaction networks are critical to understanding cell biology and interpreting genomic data, but challenging to produce experimentally. Through data integration and quality control, we provide a scored human protein-protein interaction network (InWeb_InBioMap,......Web_InBioMap, or InWeb_IM) with severalfold more interactions (>500,000) and better functional biological relevance than comparable resources. We illustrate that InWeb_InBioMap enables functional interpretation of >4,700 cancer genomes and genes involved in autism....

  4. 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.

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

    Science.gov (United States)

    Chakraborty, Sandip; Alvarez-Ponce, David

    2016-01-01

    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.

  6. Droplet networks with incorporated protein diodes show collective properties

    Science.gov (United States)

    Maglia, Giovanni; Heron, Andrew J.; Hwang, William L.; Holden, Matthew A.; Mikhailova, Ellina; Li, Qiuhong; Cheley, Stephen; Bayley, Hagan

    2009-07-01

    Recently, we demonstrated that submicrolitre aqueous droplets submerged in an apolar liquid containing lipid can be tightly connected by means of lipid bilayers to form networks. Droplet interface bilayers have been used for rapid screening of membrane proteins and to form asymmetric bilayers with which to examine the fundamental properties of channels and pores. Networks, meanwhile, have been used to form microscale batteries and to detect light. Here, we develop an engineered protein pore with diode-like properties that can be incorporated into droplet interface bilayers in droplet networks to form devices with electrical properties including those of a current limiter, a half-wave rectifier and a full-wave rectifier. The droplet approach, which uses unsophisticated components (oil, lipid, salt water and a simple pore), can therefore be used to create multidroplet networks with collective properties that cannot be produced by droplet pairs.

  7. 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.

  8. Functional module identification in protein interaction networks by interaction patterns

    Science.gov (United States)

    Wang, Yijie; Qian, Xiaoning

    2014-01-01

    Motivation: Identifying functional modules in protein–protein interaction (PPI) networks may shed light on cellular functional organization and thereafter underlying cellular mechanisms. Many existing module identification algorithms aim to detect densely connected groups of proteins as potential modules. However, based on this simple topological criterion of ‘higher than expected connectivity’, those algorithms may miss biologically meaningful modules of functional significance, in which proteins have similar interaction patterns to other proteins in networks but may not be densely connected to each other. A few blockmodel module identification algorithms have been proposed to address the problem but the lack of global optimum guarantee and the prohibitive computational complexity have been the bottleneck of their applications in real-world large-scale PPI networks. Results: In this article, we propose a novel optimization formulation LCP2 (low two-hop conductance sets) using the concept of Markov random walk on graphs, which enables simultaneous identification of both dense and sparse modules based on protein interaction patterns in given networks through searching for LCP2 by random walk. A spectral approximate algorithm SLCP2 is derived to identify non-overlapping functional modules. Based on a bottom-up greedy strategy, we further extend LCP2 to a new algorithm (greedy algorithm for LCP2) GLCP2 to identify overlapping functional modules. We compare SLCP2 and GLCP2 with a range of state-of-the-art algorithms on synthetic networks and real-world PPI networks. The performance evaluation based on several criteria with respect to protein complex prediction, high level Gene Ontology term prediction and especially sparse module detection, has demonstrated that our algorithms based on searching for LCP2 outperform all other compared algorithms. Availability and implementation: All data and code are available at http://www.cse.usf.edu/∼xqian/fmi/slcp2hop

  9. Network approaches to the functional analysis of microbial proteins.

    Science.gov (United States)

    Hallinan, J S; James, K; Wipat, A

    2011-01-01

    Large amounts of detailed biological data have been generated over the past few decades. Much of these data is freely available in over 1000 online databases; an enticing, but frustrating resource for microbiologists interested in a systems-level view of the structure and function of microbial cells. The frustration engendered by the need to trawl manually through hundreds of databases in order to accumulate information about a gene, protein, pathway, or organism of interest can be alleviated by the use of computational data integration to generated network views of the system of interest. Biological networks can be constructed from a single type of data, such as protein-protein binding information, or from data generated by multiple experimental approaches. In an integrated network, nodes usually represent genes or gene products, while edges represent some form of interaction between the nodes. Edges between nodes may be weighted to represent the probability that the edge exists in vivo. Networks may also be enriched with ontological annotations, facilitating both visual browsing and computational analysis via web service interfaces. In this review, we describe the construction, analysis of both single-data source and integrated networks, and their application to the inference of protein function in microbes. Copyright © 2011 Elsevier Ltd. All rights reserved.

  10. Context-specific protein network miner - an online system for exploring context-specific protein interaction networks from the literature

    KAUST Repository

    Chowdhary, Rajesh

    2012-04-06

    Background: Protein interaction networks (PINs) specific within a particular context contain crucial information regarding many cellular biological processes. For example, PINs may include information on the type and directionality of interaction (e.g. phosphorylation), location of interaction (i.e. tissues, cells), and related diseases. Currently, very few tools are capable of deriving context-specific PINs for conducting exploratory analysis. Results: We developed a literature-based online system, Context-specific Protein Network Miner (CPNM), which derives context-specific PINs in real-time from the PubMed database based on a set of user-input keywords and enhanced PubMed query system. CPNM reports enriched information on protein interactions (with type and directionality), their network topology with summary statistics (e.g. most densely connected proteins in the network; most densely connected protein-pairs; and proteins connected by most inbound/outbound links) that can be explored via a user-friendly interface. Some of the novel features of the CPNM system include PIN generation, ontology-based PubMed query enhancement, real-time, user-queried, up-to-date PubMed document processing, and prediction of PIN directionality. Conclusions: CPNM provides a tool for biologists to explore PINs. It is freely accessible at http://www.biotextminer.com/CPNM/. © 2012 Chowdhary et al.

  11. Protein networks as logic functions in development and cancer.

    Directory of Open Access Journals (Sweden)

    Janusz Dutkowski

    2011-09-01

    Full Text Available Many biological and clinical outcomes are based not on single proteins, but on modules of proteins embedded in protein networks. A fundamental question is how the proteins within each module contribute to the overall module activity. Here, we study the modules underlying three representative biological programs related to tissue development, breast cancer metastasis, or progression of brain cancer, respectively. For each case we apply a new method, called Network-Guided Forests, to identify predictive modules together with logic functions which tie the activity of each module to the activity of its component genes. The resulting modules implement a diverse repertoire of decision logic which cannot be captured using the simple approximations suggested in previous work such as gene summation or subtraction. We show that in cancer, certain combinations of oncogenes and tumor suppressors exert competing forces on the system, suggesting that medical genetics should move beyond cataloguing individual cancer genes to cataloguing their combinatorial logic.

  12. Network analysis and cross species comparison of protein-protein interaction networks of human, mouse and rat cytochrome P450 proteins that degrade xenobiotics.

    Science.gov (United States)

    Karthikeyan, Bagavathy Shanmugam; Akbarsha, Mohammad Abdulkader; Parthasarathy, Subbiah

    2016-06-21

    Cytochrome P450 (CYP) enzymes that degrade xenobiotics play a critical role in the metabolism and biotransformation of drugs and xenobiotics in humans as well as experimental animal models such as mouse and rat. These proteins function as a network collectively as well as independently. Though there are several reports on the organization, regulation and functionality of various CYP enzymes at the molecular level, the understanding of organization and functionality of these proteins at the holistic level remain unclear. The objective of this study is to understand the organization and functionality of xenobiotic degrading CYP enzymes of human, mouse and rat using network theory approaches and to study species differences that exist among them at the holistic level. For our analysis, a protein-protein interaction (PPI) network for CYP enzymes of human, mouse and rat was constructed using the STRING database. Topology, centrality, modularity and robustness analyses were performed for our predicted CYP PPI networks that were then validated by comparison with randomly generated network models. Network centrality analyses of CYP PPI networks reveal the central/hub proteins in the network. Modular analysis of the CYP PPI networks of human, mouse and rat resulted in functional clusters. These clusters were subjected to ontology and pathway enrichment analysis. The analyses show that the cluster of the human CYP PPI network is enriched with pathways principally related to xenobiotic/drug metabolism. Endo-xenobiotic crosstalk dominated in mouse and rat CYP PPI networks, and they were highly enriched with endogenous metabolic and signaling pathways. Thus, cross-species comparisons and analyses of human, mouse and rat CYP PPI networks gave insights about species differences that existed at the holistic level. More investigations from both reductionist and holistic perspectives can help understand CYP metabolism and species extrapolation in a much better way.

  13. Differential variation patterns between hubs and bottlenecks in human protein-protein interaction networks.

    Science.gov (United States)

    Pang, Erli; Hao, Yu; Sun, Ying; Lin, Kui

    2016-12-01

    The identification, description and understanding of protein-protein networks are important in cell biology and medicine, especially for the study of system biology where the focus concerns the interaction of biomolecules. Hubs and bottlenecks refer to the important proteins of a protein interaction network. Until now, very little attention has been paid to differentiate these two protein groups. By integrating human protein-protein interaction networks and human genome-wide variations across populations, we described the differences between hubs and bottlenecks in this study. Our findings showed that similar to interspecies, hubs and bottlenecks changed significantly more slowly than non-hubs and non-bottlenecks. To distinguish hubs from bottlenecks, we extracted their special members: hub-non-bottlenecks and non-hub-bottlenecks. The differences between these two groups represent what is between hubs and bottlenecks. We found that the variation rate of hubs was significantly lower than that of bottlenecks. In addition, we verified that stronger constraint is exerted on hubs than on bottlenecks. We further observed fewer non-synonymous sites on the domains of hubs than on those of bottlenecks and different molecular functions between them. Based on these results, we conclude that in recent human history, different variation patterns exist in hubs and bottlenecks in protein interaction networks. By revealing the difference between hubs and bottlenecks, our results might provide further insights in the relationship between evolution and biological structure.

  14. Deciphering the protein-protein interaction network regulating hepatocellular carcinoma metastasis.

    Science.gov (United States)

    Qin, Guoxuan; Dang, Mengjiao; Gao, Huajun; Wang, Hao; Luo, Fengting; Chen, Ruibing

    2017-09-01

    Hepatocellular carcinoma (HCC) is one of the leading causes of mortality related to cancer all over the world. To better understand the molecular mechanisms of HCC metastasis, we analyzed the proteome of three HCC cell lines with different metastasis potentials by quantitative proteomics and bioinformatics analysis. As a result, we identified 378 cellular proteins potentially associated to HCC metastasis, and constructed a highly connected protein-protein interaction (PPI) network. Functional annotation of the network uncovered prominent pathways and key roles of these proteins, suggesting that the metabolism and cytoskeleton biological processes are greatly involved with HCC metastasis. Furthermore, the integrative network analysis revealed a rich-club organization within the PPI network, indicating a hub center of connections. The rich-club nodes include several well-known cancer-related proteins, such as proto-oncogene non-receptor tyrosine kinase (SRC) and pyruvate kinase M2 (PKM2). Moreover, the differential expressions of two identified proteins, including PKM2 and actin-related protein 2/3 complex subunit 4 (ARPC4), were validated using Western blotting. These two proteins were revealed as potential prognostic markers for HCC as shown by survival rate analysis. Copyright © 2017. Published by Elsevier B.V.

  15. ATP binding to p97/VCP D1 domain regulates selective recruitment of adaptors to its proximal N-domain.

    Directory of Open Access Journals (Sweden)

    Wei Sheng Chia

    Full Text Available p97/Valosin-containing protein (VCP is a member of the AAA-ATPase family involved in many cellular processes including cell division, intracellular trafficking and extraction of misfolded proteins in endoplasmic reticulum-associated degradation (ERAD. It is a homohexamer with each subunit containing two tandem D1 and D2 ATPase domains and N- and C-terminal regions that function as adaptor protein binding domains. p97/VCP is directed to its many different functional pathways by associating with various adaptor proteins. The regulation of the recruitment of the adaptor proteins remains unclear. Two adaptor proteins, Ufd1/Npl4 and p47, which bind exclusively to the p97/VCP N-domain and direct p97/VCP to either ERAD-related processes or homotypic fusion of Golgi fragments, were studied here. Surface plasmon resonance biosensor-based assays allowed the study of binding kinetics in real time. In competition experiments, it was observed that in the presence of ATP, Ufd1/Npl4 was able to compete more effectively with p47 for binding to p97/VCP. By using non-hydrolysable ATP analogues and the hexameric truncated p97/N-D1 fragment, it was shown that binding rather than hydrolysis of ATP to the proximal D1 domain strengthened the Ufd1/Npl4 association with the N-domain, thus regulating the recruitment of either Ufd1/Npl4 or p47. This novel role of ATP and an assigned function to the D1 AAA-ATPase domain link the multiple functions of p97/VCP to the metabolic status of the cell.

  16. NatalieQ: a web server for protein-protein interaction network querying.

    Science.gov (United States)

    El-Kebir, Mohammed; Brandt, Bernd W; Heringa, Jaap; Klau, Gunnar W

    2014-04-01

    Molecular interactions need to be taken into account to adequately model the complex behavior of biological systems. These interactions are captured by various types of biological networks, such as metabolic, gene-regulatory, signal transduction and protein-protein interaction networks. We recently developed Natalie, which computes high-quality network alignments via advanced methods from combinatorial optimization. Here, we present NatalieQ, a web server for topology-based alignment of a specified query protein-protein interaction network to a selected target network using the Natalie algorithm. By incorporating similarity at both the sequence and the network level, we compute alignments that allow for the transfer of functional annotation as well as for the prediction of missing interactions. We illustrate the capabilities of NatalieQ with a biological case study involving the Wnt signaling pathway. We show that topology-based network alignment can produce results complementary to those obtained by using sequence similarity alone. We also demonstrate that NatalieQ is able to predict putative interactions. The server is available at: http://www.ibi.vu.nl/programs/natalieq/.

  17. The topology of the bacterial co-conserved protein network and its implications for predicting protein function

    Directory of Open Access Journals (Sweden)

    Leach Sonia M

    2008-06-01

    Full Text Available Abstract Background Protein-protein interactions networks are most often generated from physical protein-protein interaction data. Co-conservation, also known as phylogenetic profiles, is an alternative source of information for generating protein interaction networks. Co-conservation methods generate interaction networks among proteins that are gained or lost together through evolution. Co-conservation is a particularly useful technique in the compact bacteria genomes. Prior studies in yeast suggest that the topology of protein-protein interaction networks generated from physical interaction assays can offer important insight into protein function. Here, we hypothesize that in bacteria, the topology of protein interaction networks derived via co-conservation information could similarly improve methods for predicting protein function. Since the topology of bacteria co-conservation protein-protein interaction networks has not previously been studied in depth, we first perform such an analysis for co-conservation networks in E. coli K12. Next, we demonstrate one way in which network connectivity measures and global and local function distribution can be exploited to predict protein function for previously uncharacterized proteins. Results Our results showed, like most biological networks, our bacteria co-conserved protein-protein interaction networks had scale-free topologies. Our results indicated that some properties of the physical yeast interaction network hold in our bacteria co-conservation networks, such as high connectivity for essential proteins. However, the high connectivity among protein complexes in the yeast physical network was not seen in the co-conservation network which uses all bacteria as the reference set. We found that the distribution of node connectivity varied by functional category and could be informative for function prediction. By integrating of functional information from different annotation sources and using the

  18. Elucidation of Novel Structural Scaffold in Rohu TLR2 and Its Binding Site Analysis with Peptidoglycan, Lipoteichoic Acid and Zymosan Ligands, and Downstream MyD88 Adaptor Protein

    Directory of Open Access Journals (Sweden)

    Bikash Ranjan Sahoo

    2013-01-01

    Full Text Available Toll-like receptors (TLRs play key roles in sensing wide array of microbial signatures and induction of innate immunity. TLR2 in fish resembles higher eukaryotes by sensing peptidoglycan (PGN and lipoteichoic acid (LTA of bacterial cell wall and zymosan of yeasts. However, in fish TLR2, no study yet describes the ligand binding motifs in the leucine rich repeat regions (LRRs of the extracellular domain (ECD and important amino acids in TLR2-TIR (toll/interleukin-1 receptor domain that could be engaged in transmitting downstream signaling. We predicted these in a commercially important freshwater fish species rohu (Labeo rohita by constructing 3D models of TLR2-ECD, TLR2-TIR, and MyD88-TIR by comparative modeling followed by 40 ns (nanosecond molecular dynamics simulation (MDS for TLR2-ECD and 20 ns MDS for TLR2-TIR and MyD88-TIR. Protein (TLR2-ECD–ligands (PGN, LTA, and zymosan docking in rohu by AutoDock4.0, FlexX2.1, and GOLD4.1 anticipated LRR16–19, LRR12–14, and LRR20-CT as the most important ligand binding motifs. Protein (TLR2-TIR—protein (MyD88-TIR interaction by HADDOCK and ZDOCK predicted BB loop, αB-helix, αC-helix, and CD loop in TLR2-TIR and BB loop, αB-helix, and CD loop in MyD88-TIR as the critical binding domains. This study provides ligands recognition and downstream signaling.

  19. Deep recurrent conditional random field network for protein secondary prediction

    DEFF Research Database (Denmark)

    Johansen, Alexander Rosenberg; Sønderby, Søren Kaae; Sønderby, Casper Kaae

    2017-01-01

    Deep learning has become the state-of-the-art method for predicting protein secondary structure from only its amino acid residues and sequence profile. Building upon these results, we propose to combine a bi-directional recurrent neural network (biRNN) with a conditional random field (CRF), which...

  20. Analysis of core–periphery organization in protein contact networks ...

    Indian Academy of Sciences (India)

    2015-09-29

    Sep 29, 2015 ... Caenorhabditis elegans (Chatterjee and Sinha 2007) and the protein interaction network of Escherichia coli (Lin et al. 2009). Recently, this decomposition technique has been used to disentangle the hierarchical structure of Internet router-level connection topology (Zhang et al. 2009), to show that software ...

  1. Analysis of core–periphery organization in protein contact networks ...

    Indian Academy of Sciences (India)

    From mutation sensitivity analysis, we show that the probability of deleterious or intolerant mutations also increases with the core order. We also show that stabilization centre residues are in the innermost cores, suggesting that the network core is critically important in maintaining the structural stability of the protein.

  2. Predicting protein complex in protein interaction network - a supervised learning based method.

    Science.gov (United States)

    Yu, Feng; Yang, Zhi; Tang, Nan; Lin, Hong; Wang, Jian; Yang, Zhi

    2014-01-01

    Protein complexes are important for understanding principles of cellular organization and function. High-throughput experimental techniques have produced a large amount of protein interactions, making it possible to predict protein complexes from protein -protein interaction networks. However, most of current methods are unsupervised learning based methods which can't utilize the information of the large amount of available known complexes. We present a supervised learning-based method for predicting protein complexes in protein - protein interaction networks. The method extracts rich features from both the unweighted and weighted networks to train a Regression model, which is then used for the cliques filtering, growth, and candidate complex filtering. The model utilizes additional "uncertainty" samples and, therefore, is more discriminative when used in the complex detection algorithm. In addition, our method uses the maximal cliques found by the Cliques algorithm as the initial cliques, which has been proven to be more effective than the method of expanding from the seeding proteins used in other methods. The experimental results on several PIN datasets show that in most cases the performance of our method are superior to comparable state-of-the-art protein complex detection techniques. The results demonstrate the several advantages of our method over other state-of-the-art techniques. Firstly, our method is a supervised learning-based method that can make full use of the information of the available known complexes instead of being only based on the topological structure of the PIN. That also means, if more training samples are provided, our method can achieve better performance than those unsupervised methods. Secondly, we design the rich feature set to describe the properties of the known complexes, which includes not only the features from the unweighted network, but also those from the weighted network built based on the Gene Ontology information. Thirdly

  3. FACETS: multi-faceted functional decomposition of protein interaction networks

    Science.gov (United States)

    Seah, Boon-Siew; Bhowmick, Sourav S.; Forbes Dewey, C.

    2012-01-01

    Motivation: The availability of large-scale curated protein interaction datasets has given rise to the opportunity to investigate higher level organization and modularity within the protein–protein interaction (PPI) network using graph theoretic analysis. Despite the recent progress, systems level analysis of high-throughput PPIs remains a daunting task because of the amount of data they present. In this article, we propose a novel PPI network decomposition algorithm called FACETS in order to make sense of the deluge of interaction data using Gene Ontology (GO) annotations. FACETS finds not just a single functional decomposition of the PPI network, but a multi-faceted atlas of functional decompositions that portray alternative perspectives of the functional landscape of the underlying PPI network. Each facet in the atlas represents a distinct interpretation of how the network can be functionally decomposed and organized. Our algorithm maximizes interpretative value of the atlas by optimizing inter-facet orthogonality and intra-facet cluster modularity. Results: We tested our algorithm on the global networks from IntAct, and compared it with gold standard datasets from MIPS and KEGG. We demonstrated the performance of FACETS. We also performed a case study that illustrates the utility of our approach. Contact: seah0097@ntu.edu.sg or assourav@ntu.edu.sg Supplementary information: Supplementary data are available at the Bioinformatics online. Availability: Our software is available freely for non-commercial purposes from: http://www.cais.ntu.edu.sg/∼assourav/Facets/ PMID:22908217

  4. Amyloid precursor protein interaction network in human testis: sentinel proteins for male reproduction.

    Science.gov (United States)

    Silva, Joana Vieira; Yoon, Sooyeon; Domingues, Sara; Guimarães, Sofia; Goltsev, Alexander V; da Cruz E Silva, Edgar Figueiredo; Mendes, José Fernando F; da Cruz E Silva, Odete Abreu Beirão; Fardilha, Margarida

    2015-01-16

    Amyloid precursor protein (APP) is widely recognized for playing a central role in Alzheimer's disease pathogenesis. Although APP is expressed in several tissues outside the human central nervous system, the functions of APP and its family members in other tissues are still poorly understood. APP is involved in several biological functions which might be potentially important for male fertility, such as cell adhesion, cell motility, signaling, and apoptosis. Furthermore, APP superfamily members are known to be associated with fertility. Knowledge on the protein networks of APP in human testis and spermatozoa will shed light on the function of APP in the male reproductive system. We performed a Yeast Two-Hybrid screen and a database search to study the interaction network of APP in human testis and sperm. To gain insights into the role of APP superfamily members in fertility, the study was extended to APP-like protein 2 (APLP2). We analyzed several topological properties of the APP interaction network and the biological and physiological properties of the proteins in the APP interaction network were also specified by gene ontologyand pathways analyses. We classified significant features related to the human male reproduction for the APP interacting proteins and identified modules of proteins with similar functional roles which may show cooperative behavior for male fertility. The present work provides the first report on the APP interactome in human testis. Our approach allowed the identification of novel interactions and recognition of key APP interacting proteins for male reproduction, particularly in sperm-oocyte interaction.

  5. AtPIN: Arabidopsis thaliana Protein Interaction Network

    Directory of Open Access Journals (Sweden)

    Silva-Filho Marcio C

    2009-12-01

    Full Text Available Abstract Background Protein-protein interactions (PPIs constitute one of the most crucial conditions to sustain life in living organisms. To study PPI in Arabidopsis thaliana we have developed AtPIN, a database and web interface for searching and building interaction networks based on publicly available protein-protein interaction datasets. Description All interactions were divided into experimentally demonstrated or predicted. The PPIs in the AtPIN database present a cellular compartment classification (C3 which divides the PPI into 4 classes according to its interaction evidence and subcellular localization. It has been shown in the literature that a pair of genuine interacting proteins are generally expected to have a common cellular role and proteins that have common interaction partners have a high chance of sharing a common function. In AtPIN, due to its integrative profile, the reliability index for a reported PPI can be postulated in terms of the proportion of interaction partners that two proteins have in common. For this, we implement the Functional Similarity Weight (FSW calculation for all first level interactions present in AtPIN database. In order to identify target proteins of cytosolic glutamyl-tRNA synthetase (Cyt-gluRS (AT5G26710 we combined two approaches, AtPIN search and yeast two-hybrid screening. Interestingly, the proteins glutamine synthetase (AT5G35630, a disease resistance protein (AT3G50950 and a zinc finger protein (AT5G24930, which has been predicted as target proteins for Cyt-gluRS by AtPIN, were also detected in the experimental screening. Conclusions AtPIN is a friendly and easy-to-use tool that aggregates information on Arabidopsis thaliana PPIs, ontology, and sub-cellular localization, and might be a useful and reliable strategy to map protein-protein interactions in Arabidopsis. AtPIN can be accessed at http://bioinfo.esalq.usp.br/atpin.

  6. Prediction of Protein-Protein Interacting Sites: How to Bridge Molecular Events to Large Scale Protein Interaction Networks

    Science.gov (United States)

    Bartoli, Lisa; Martelli, Pier Luigi; Rossi, Ivan; Fariselli, Piero; Casadio, Rita

    Most of the cellular functions are the result of the concerted action of protein complexes forming pathways and networks. For this reason, efforts were devoted to the study of protein-protein interactions. Large-scale experiments on whole genomes allowed the identification of interacting protein pairs. However residues involved in the interaction are generally not known and the majority of the interactions still lack a structural characterization. A crucial step towards the deciphering of the interaction mechanism of proteins is the recognition of their interacting surfaces, particularly in those structures for which also the most recent interaction network resources do not contain information. To this purpose, we developed a neural network-based method that is able to characterize protein complexes, by predicting amino acid residues that mediate the interactions. All the Protein Data Bank (PDB) chains, both in the unbound and in the complexed form, are predicted and the results are stored in a database of interaction surfaces (http://gpcr.biocomp.unibo.it/zenpatches). Finally, we performed a survey on the different computational methods for protein-protein interaction prediction and on their training/testing sets in order to highlight the most informative properties of protein interfaces.

  7. Evolution of an intricate J-protein network driving protein disaggregation in eukaryotes.

    Science.gov (United States)

    Nillegoda, Nadinath B; Stank, Antonia; Malinverni, Duccio; Alberts, Niels; Szlachcic, Anna; Barducci, Alessandro; De Los Rios, Paolo; Wade, Rebecca C; Bukau, Bernd

    2017-05-15

    Hsp70 participates in a broad spectrum of protein folding processes extending from nascent chain folding to protein disaggregation. This versatility in function is achieved through a diverse family of J-protein cochaperones that select substrates for Hsp70. Substrate selection is further tuned by transient complexation between different classes of J-proteins, which expands the range of protein aggregates targeted by metazoan Hsp70 for disaggregation. We assessed the prevalence and evolutionary conservation of J-protein complexation and cooperation in disaggregation. We find the emergence of a eukaryote-specific signature for interclass complexation of canonical J-proteins. Consistently, complexes exist in yeast and human cells, but not in bacteria, and correlate with cooperative action in disaggregation in vitro. Signature alterations exclude some J-proteins from networking, which ensures correct J-protein pairing, functional network integrity and J-protein specialization. This fundamental change in J-protein biology during the prokaryote-to-eukaryote transition allows for increased fine-tuning and broadening of Hsp70 function in eukaryotes.

  8. In vitro and in vivo Analysis of the Binding of the C Terminus of the HDL Receptor Scavenger Receptor Class B type I (SR-BI) to the PDZ1 Domain of its Cytoplasmic Adaptor Protein PDZK1

    Energy Technology Data Exchange (ETDEWEB)

    O Kocher; G Birrane; K Tsukamoto; S Fenske; A Yesilaltay; R Pal; K Daniels; J Ladias; M Krieger

    2011-12-31

    The PDZ1 domain of the four PDZ domain-containing protein PDZK1 has been reported to bind the C terminus of the HDL receptor scavenger receptor class B, type I (SR-BI), and to control hepatic SR-BI expression and function. We generated wild-type (WT) and mutant murine PDZ1 domains, the mutants bearing single amino acid substitutions in their carboxylate binding loop (Lys(14)-Xaa(4)-Asn(19)-Tyr-Gly-Phe-Phe-Leu(24)), and measured their binding affinity for a 7-residue peptide corresponding to the C terminus of SR-BI ((503)VLQEAKL(509)). The Y20A and G21Y substitutions abrogated all binding activity. Surprisingly, binding affinities (K(d)) of the K14A and F22A mutants were 3.2 and 4.0 ?M, respectively, similar to 2.6 ?M measured for the WT PDZ1. To understand these findings, we determined the high resolution structure of WT PDZ1 bound to a 5-residue sequence from the C-terminal SR-BI ((505)QEAKL(509)) using x-ray crystallography. In addition, we incorporated the K14A and Y20A substitutions into full-length PDZK1 liver-specific transgenes and expressed them in WT and PDZK1 knock-out mice. In WT mice, the transgenes did not alter endogenous hepatic SR-BI protein expression (intracellular distribution or amount) or lipoprotein metabolism (total plasma cholesterol, lipoprotein size distribution). In PDZK1 knock-out mice, as expected, the K14A mutant behaved like wild-type PDZK1 and completely corrected their hepatic SR-BI and plasma lipoprotein abnormalities. Unexpectedly, the 10-20-fold overexpressed Y20A mutant also substantially, but not completely, corrected these abnormalities. The results suggest that there may be an additional site(s) within PDZK1 that bind(s) SR-BI and mediate(s) productive SR-BI-PDZK1 interaction previously attributed exclusively to the canonical binding of the C-terminal SR-BI to PDZ1.

  9. Prioritizing disease candidate proteins in cardiomyopathy-specific protein-protein interaction networks based on "guilt by association" analysis.

    Directory of Open Access Journals (Sweden)

    Wan Li

    Full Text Available The cardiomyopathies are a group of heart muscle diseases which can be inherited (familial. Identifying potential disease-related proteins is important to understand mechanisms of cardiomyopathies. Experimental identification of cardiomyophthies is costly and labour-intensive. In contrast, bioinformatics approach has a competitive advantage over experimental method. Based on "guilt by association" analysis, we prioritized candidate proteins involving in human cardiomyopathies. We first built weighted human cardiomyopathy-specific protein-protein interaction networks for three subtypes of cardiomyopathies using the known disease proteins from Online Mendelian Inheritance in Man as seeds. We then developed a method in prioritizing disease candidate proteins to rank candidate proteins in the network based on "guilt by association" analysis. It was found that most candidate proteins with high scores shared disease-related pathways with disease seed proteins. These top ranked candidate proteins were related with the corresponding disease subtypes, and were potential disease-related proteins. Cross-validation and comparison with other methods indicated that our approach could be used for the identification of potentially novel disease proteins, which may provide insights into cardiomyopathy-related mechanisms in a more comprehensive and integrated way.

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

    Science.gov (United States)

    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

  11. A Physical Interaction Network of Dengue Virus and Human Proteins*

    Science.gov (United States)

    Khadka, Sudip; Vangeloff, Abbey D.; Zhang, Chaoying; Siddavatam, Prasad; Heaton, Nicholas S.; Wang, Ling; Sengupta, Ranjan; Sahasrabudhe, Sudhir; Randall, Glenn; Gribskov, Michael; Kuhn, Richard J.; Perera, Rushika; LaCount, Douglas J.

    2011-01-01

    Dengue virus (DENV), an emerging mosquito-transmitted pathogen capable of causing severe disease in humans, interacts with host cell factors to create a more favorable environment for replication. However, few interactions between DENV and human proteins have been reported to date. To identify DENV-human protein interactions, we used high-throughput yeast two-hybrid assays to screen the 10 DENV proteins against a human liver activation domain library. From 45 DNA-binding domain clones containing either full-length viral genes or partially overlapping gene fragments, we identified 139 interactions between DENV and human proteins, the vast majority of which are novel. These interactions involved 105 human proteins, including six previously implicated in DENV infection and 45 linked to the replication of other viruses. Human proteins with functions related to the complement and coagulation cascade, the centrosome, and the cytoskeleton were enriched among the DENV interaction partners. To determine if the cellular proteins were required for DENV infection, we used small interfering RNAs to inhibit their expression. Six of 12 proteins targeted (CALR, DDX3X, ERC1, GOLGA2, TRIP11, and UBE2I) caused a significant decrease in the replication of a DENV replicon. We further showed that calreticulin colocalized with viral dsRNA and with the viral NS3 and NS5 proteins in DENV-infected cells, consistent with a direct role for calreticulin in DENV replication. Human proteins that interacted with DENV had significantly higher average degree and betweenness than expected by chance, which provides additional support for the hypothesis that viruses preferentially target cellular proteins that occupy central position in the human protein interaction network. This study provides a valuable starting point for additional investigations into the roles of human proteins in DENV infection. PMID:21911577

  12. A physical interaction network of dengue virus and human proteins.

    Science.gov (United States)

    Khadka, Sudip; Vangeloff, Abbey D; Zhang, Chaoying; Siddavatam, Prasad; Heaton, Nicholas S; Wang, Ling; Sengupta, Ranjan; Sahasrabudhe, Sudhir; Randall, Glenn; Gribskov, Michael; Kuhn, Richard J; Perera, Rushika; LaCount, Douglas J

    2011-12-01

    Dengue virus (DENV), an emerging mosquito-transmitted pathogen capable of causing severe disease in humans, interacts with host cell factors to create a more favorable environment for replication. However, few interactions between DENV and human proteins have been reported to date. To identify DENV-human protein interactions, we used high-throughput yeast two-hybrid assays to screen the 10 DENV proteins against a human liver activation domain library. From 45 DNA-binding domain clones containing either full-length viral genes or partially overlapping gene fragments, we identified 139 interactions between DENV and human proteins, the vast majority of which are novel. These interactions involved 105 human proteins, including six previously implicated in DENV infection and 45 linked to the replication of other viruses. Human proteins with functions related to the complement and coagulation cascade, the centrosome, and the cytoskeleton were enriched among the DENV interaction partners. To determine if the cellular proteins were required for DENV infection, we used small interfering RNAs to inhibit their expression. Six of 12 proteins targeted (CALR, DDX3X, ERC1, GOLGA2, TRIP11, and UBE2I) caused a significant decrease in the replication of a DENV replicon. We further showed that calreticulin colocalized with viral dsRNA and with the viral NS3 and NS5 proteins in DENV-infected cells, consistent with a direct role for calreticulin in DENV replication. Human proteins that interacted with DENV had significantly higher average degree and betweenness than expected by chance, which provides additional support for the hypothesis that viruses preferentially target cellular proteins that occupy central position in the human protein interaction network. This study provides a valuable starting point for additional investigations into the roles of human proteins in DENV infection.

  13. p130Cas scaffolds the signalosome to direct adaptor-effector cross talk during Kaposi's sarcoma-associated herpesvirus trafficking in human microvascular dermal endothelial cells.

    Science.gov (United States)

    Bandyopadhyay, Chirosree; Veettil, Mohanan Valiya; Dutta, Sujoy; Chandran, Bala

    2014-12-01

    enzymatic activity, are well known to allow a great diversity of specific and coordinated protein-protein interactions imparting signal amplification to different networks for physiological and pathological signaling. They are involved in integrating signals from growth factors, extracellular matrix molecules, bacterial pathogens, and apoptotic cells. The present study identifies human microvascular dermal endothelial (HMVEC-d) cellular scaffold protein p130Cas (Crk-associated substrate) as a platform to promote Kaposi's sarcoma-associated herpesvirus (KSHV) trafficking. Early during KSHV de novo infection, p130Cas associates with lipid rafts and scaffolds EphrinA2 (EphA2)-associated critical adaptor members to downstream effector molecules, promoting successful nuclear delivery of the KSHV genome. Hence, simultaneous targeting of the receptor EphA2 and scaffolding action of p130Cas can potentially uncouple the signal cross talk of the KSHV entry-associated upstream signal complex from the immediate downstream trafficking-associated signalosome, consequently routing KSHV toward lysosomal degradation and eventually blocking KSHV infection and associated malignancies. Copyright © 2014, American Society for Microbiology. All Rights Reserved.

  14. What properties characterize the hub proteins of the protein-protein interaction network of Saccharomyces cerevisiae?

    OpenAIRE

    Ekman, Diana; Light, Sara; Bj?rklund, ?sa K; Elofsson, Arne

    2006-01-01

    Background Most proteins interact with only a few other proteins while a small number of proteins (hubs) have many interaction partners. Hub proteins and non-hub proteins differ in several respects; however, understanding is not complete about what properties characterize the hubs and set them apart from proteins of low connectivity. Therefore, we have investigated what differentiates hubs from non-hubs and static hubs (party hubs) from dynamic hubs (date hubs) in the protein-protein interact...

  15. DMPD: The SAP family of adaptors in immune regulation. [Dynamic Macrophage Pathway CSML Database

    Lifescience Database Archive (English)

    Full Text Available 15541655 The SAP family of adaptors in immune regulation. Latour S, Veillette A. Se...min Immunol. 2004 Dec;16(6):409-19. (.png) (.svg) (.html) (.csml) Show The SAP family of adaptors in immune ...regulation. PubmedID 15541655 Title The SAP family of adaptors in immune regulation. Authors Latour S, Veill

  16. Convolutional LSTM Networks for Subcellular Localization of Proteins

    DEFF Research Database (Denmark)

    Nielsen, Henrik; Sønderby, Søren Kaae; Sønderby, Casper Kaae

    2015-01-01

    Machine learning is widely used to analyze biological sequence data. Non-sequential models such as SVMs or feed-forward neural networks are often used although they have no natural way of handling sequences of varying length. Recurrent neural networks such as the long short term memory (LSTM) model...... convolutional filters and experiment with an attention mechanism which lets the LSTM focus on specific parts of the protein. Lastly we introduce new visualizations of both the convolutional filters and the attention mechanisms and show how they can be used to extract biologically relevant knowledge from...

  17. Probing RNA-protein networks: biochemistry meets genomics.

    Science.gov (United States)

    Campbell, Zachary T; Wickens, Marvin

    2015-03-01

    RNA-protein interactions are pervasive. The specificity of these interactions dictates which RNAs are controlled by what protein. Here we describe a class of revolutionary new methods that enable global views of RNA-binding specificity in vitro, for both single proteins and multiprotein complexes. These methods provide insight into central issues in RNA regulation in living cells, including understanding the balance between free and bound components, the basis for exclusion of binding sites, detection of binding events in the absence of discernible regulatory elements, and new approaches to targeting endogenous transcripts by design. Comparisons of in vitro and in vivo binding provide a foundation for comprehensive understanding of the biochemistry of protein-mediated RNA regulatory networks. Copyright © 2015 Elsevier Ltd. All rights reserved.

  18. Protein Kinase C Epsilon and Genetic Networks in Osteosarcoma Metastasis

    International Nuclear Information System (INIS)

    Goudarzi, Atta; Gokgoz, Nalan; Gill, Mona; Pinnaduwage, Dushanthi; Merico, Daniele; Wunder, Jay S.; Andrulis, Irene L.

    2013-01-01

    Osteosarcoma (OS) is the most common primary malignant tumor of the bone, and pulmonary metastasis is the most frequent cause of OS mortality. The aim of this study was to discover and characterize genetic networks differentially expressed in metastatic OS. Expression profiling of OS tumors, and subsequent supervised network analysis, was performed to discover genetic networks differentially activated or organized in metastatic OS compared to localized OS. Broad trends among the profiles of metastatic tumors include aberrant activity of intracellular organization and translation networks, as well as disorganization of metabolic networks. The differentially activated PRKCε-RASGRP3-GNB2 network, which interacts with the disorganized DLG2 hub, was also found to be differentially expressed among OS cell lines with differing metastatic capacity in xenograft models. PRKCε transcript was more abundant in some metastatic OS tumors; however the difference was not significant overall. In functional studies, PRKCε was not found to be involved in migration of M132 OS cells, but its protein expression was induced in M112 OS cells following IGF-1 stimulation

  19. Detection of Locally Over-Represented GO Terms in Protein-Protein Interaction Networks

    Science.gov (United States)

    LAVALLÉE-ADAM, MATHIEU; COULOMBE, BENOIT; BLANCHETTE, MATHIEU

    2015-01-01

    High-throughput methods for identifying protein-protein interactions produce increasingly complex and intricate interaction networks. These networks are extremely rich in information, but extracting biologically meaningful hypotheses from them and representing them in a human-readable manner is challenging. We propose a method to identify Gene Ontology terms that are locally over-represented in a subnetwork of a given biological network. Specifically, we propose several methods to evaluate the degree of clustering of proteins associated to a particular GO term in both weighted and unweighted PPI networks, and describe efficient methods to estimate the statistical significance of the observed clustering. We show, using Monte Carlo simulations, that our best approximation methods accurately estimate the true p-value, for random scale-free graphs as well as for actual yeast and human networks. When applied to these two biological networks, our approach recovers many known complexes and pathways, but also suggests potential functions for many subnetworks. Online Supplementary Material is available at www.liebertonline.com. PMID:20377456

  20. ROS Control Mitochondrial Motility through p38 and the Motor Adaptor Miro/Trak

    Directory of Open Access Journals (Sweden)

    Valentina Debattisti

    2017-11-01

    Full Text Available Mitochondrial distribution and motility are recognized as central to many cellular functions, but their regulation by signaling mechanisms remains to be elucidated. Here, we report that reactive oxygen species (ROS, either derived from an extracellular source or intracellularly generated, control mitochondrial distribution and function by dose-dependently, specifically, and reversibly decreasing mitochondrial motility in both rat hippocampal primary cultured neurons and cell lines. ROS decrease motility independently of cytoplasmic [Ca2+], mitochondrial membrane potential, or permeability transition pore opening, known effectors of oxidative stress. However, multiple lines of genetic and pharmacological evidence support that a ROS-activated mitogen-activated protein kinase (MAPK, p38α, is required for the motility inhibition. Furthermore, anchoring mitochondria directly to kinesins without involvement of the physiological adaptors between the organelles and the motor protein prevents the H2O2-induced decrease in mitochondrial motility. Thus, ROS engage p38α and the motor adaptor complex to exert changes in mitochondrial motility, which likely has both physiological and pathophysiological relevance.

  1. Evolution versus "intelligent design": comparing the topology of protein-protein interaction networks to the Internet.

    Science.gov (United States)

    Yang, Q; Siganos, G; Faloutsos, M; Lonardi, S

    2006-01-01

    Recent research efforts have made available genome-wide, high-throughput protein-protein interaction (PPI) maps for several model organisms. This has enabled the systematic analysis of PPI networks, which has become one of the primary challenges for the system biology community. In this study, we attempt to understand better the topological structure of PPI networks by comparing them against man-made communication networks, and more specifically, the Internet. Our comparative study is based on a comprehensive set of graph metrics. Our results exhibit an interesting dichotomy. On the one hand, both networks share several macroscopic properties such as scale-free and small-world properties. On the other hand, the two networks exhibit significant topological differences, such as the cliqueishness of the highest degree nodes. We attribute these differences to the distinct design principles and constraints that both networks are assumed to satisfy. We speculate that the evolutionary constraints that favor the survivability and diversification are behind the building process of PPI networks, whereas the leading force in shaping the Internet topology is a decentralized optimization process geared towards efficient node communication.

  2. PROSHIFT: Protein chemical shift prediction using artificial neural networks

    International Nuclear Information System (INIS)

    Meiler, Jens

    2003-01-01

    The importance of protein chemical shift values for the determination of three-dimensional protein structure has increased in recent years because of the large databases of protein structures with assigned chemical shift data. These databases have allowed the investigation of the quantitative relationship between chemical shift values obtained by liquid state NMR spectroscopy and the three-dimensional structure of proteins. A neural network was trained to predict the 1 H, 13 C, and 15 N of proteins using their three-dimensional structure as well as experimental conditions as input parameters. It achieves root mean square deviations of 0.3 ppm for hydrogen, 1.3 ppm for carbon, and 2.6 ppm for nitrogen chemical shifts. The model reflects important influences of the covalent structure as well as of the conformation not only for backbone atoms (as, e.g., the chemical shift index) but also for side-chain nuclei. For protein models with a RMSD smaller than 5 A a correlation of the RMSD and the r.m.s. deviation between the predicted and the experimental chemical shift is obtained. Thus the method has the potential to not only support the assignment process of proteins but also help with the validation and the refinement of three-dimensional structural proposals. It is freely available for academic users at the PROSHIFT server: www.jens-meiler.de/proshift.html

  3. Peptide microarrays to probe for competition for binding sites in a protein interaction network

    NARCIS (Netherlands)

    Sinzinger, M.D.S.; Ruttekolk, I.R.R.; Gloerich, J.; Wessels, H.; Chung, Y.D.; Adjobo-Hermans, M.J.W.; Brock, R.E.

    2013-01-01

    Cellular protein interaction networks are a result of the binding preferences of a particular protein and the entirety of interactors that mutually compete for binding sites. Therefore, the reconstruction of interaction networks by the accumulation of interaction networks for individual proteins

  4. Rbfox2 controls autoregulation in RNA-binding protein networks.

    Science.gov (United States)

    Jangi, Mohini; Boutz, Paul L; Paul, Prakriti; Sharp, Phillip A

    2014-03-15

    The tight regulation of splicing networks is critical for organismal development. To maintain robust splicing patterns, many splicing factors autoregulate their expression through alternative splicing-coupled nonsense-mediated decay (AS-NMD). However, as negative autoregulation results in a self-limiting window of splicing factor expression, it is unknown how variations in steady-state protein levels can arise in different physiological contexts. Here, we demonstrate that Rbfox2 cross-regulates AS-NMD events within RNA-binding proteins to alter their expression. Using individual nucleotide-resolution cross-linking immunoprecipitation coupled to high-throughput sequencing (iCLIP) and mRNA sequencing, we identified >200 AS-NMD splicing events that are bound by Rbfox2 in mouse embryonic stem cells. These "silent" events are characterized by minimal apparent splicing changes but appreciable changes in gene expression upon Rbfox2 knockdown due to degradation of the NMD-inducing isoform. Nearly 70 of these AS-NMD events fall within genes encoding RNA-binding proteins, many of which are autoregulated. As with the coding splicing events that we found to be regulated by Rbfox2, silent splicing events are evolutionarily conserved and frequently contain the Rbfox2 consensus UGCAUG. Our findings uncover an unexpectedly broad and multilayer regulatory network controlled by Rbfox2 and offer an explanation for how autoregulatory splicing networks are tuned.

  5. The construction of an amino acid network for understanding protein structure and function.

    Science.gov (United States)

    Yan, Wenying; Zhou, Jianhong; Sun, Maomin; Chen, Jiajia; Hu, Guang; Shen, Bairong

    2014-06-01

    Amino acid networks (AANs) are undirected networks consisting of amino acid residues and their interactions in three-dimensional protein structures. The analysis of AANs provides novel insight into protein science, and several common amino acid network properties have revealed diverse classes of proteins. In this review, we first summarize methods for the construction and characterization of AANs. We then compare software tools for the construction and analysis of AANs. Finally, we review the application of AANs for understanding protein structure and function, including the identification of functional residues, the prediction of protein folding, analyzing protein stability and protein-protein interactions, and for understanding communication within and between proteins.

  6. Spiral biasing adaptor for use in Si drift detectors and Si drift detector arrays

    Science.gov (United States)

    Li, Zheng; Chen, Wei

    2016-07-05

    A drift detector array, preferably a silicon drift detector (SDD) array, that uses a low current biasing adaptor is disclosed. The biasing adaptor is customizable for any desired geometry of the drift detector single cell with minimum drift time of carriers. The biasing adaptor has spiral shaped ion-implants that generate the desired voltage profile. The biasing adaptor can be processed on the same wafer as the drift detector array and only one biasing adaptor chip/side is needed for one drift detector array to generate the voltage profiles on the front side and back side of the detector array.

  7. Kit- and Fc epsilonRI-induced differential phosphorylation of the transmembrane adaptor molecule NTAL/LAB/LAT2 allows flexibility in its scaffolding function in mast cells

    DEFF Research Database (Denmark)

    Iwaki, Shoko; Spicka, Jiri; Tkaczyk, Christine

    2008-01-01

    The transmembrane adaptor protein (TRAP), NTAL, is phosphorylated in mast cells following FcvarepsilonRI aggregation whereby it cooperates with LAT to induce degranulation. The Kit ligand, stem cell factor (SCF), enhances antigen-induced degranulation and this also appears to be NTAL-dependent. H...

  8. An automated approach to network features of protein structure ensembles

    Science.gov (United States)

    Bhattacharyya, Moitrayee; Bhat, Chanda R; Vishveshwara, Saraswathi

    2013-01-01

    Network theory applied to protein structures provides insights into numerous problems of biological relevance. The explosion in structural data available from PDB and simulations establishes a need to introduce a standalone-efficient program that assembles network concepts/parameters under one hood in an automated manner. Herein, we discuss the development/application of an exhaustive, user-friendly, standalone program package named PSN-Ensemble, which can handle structural ensembles generated through molecular dynamics (MD) simulation/NMR studies or from multiple X-ray structures. The novelty in network construction lies in the explicit consideration of side-chain interactions among amino acids. The program evaluates network parameters dealing with topological organization and long-range allosteric communication. The introduction of a flexible weighing scheme in terms of residue pairwise cross-correlation/interaction energy in PSN-Ensemble brings in dynamical/chemical knowledge into the network representation. Also, the results are mapped on a graphical display of the structure, allowing an easy access of network analysis to a general biological community. The potential of PSN-Ensemble toward examining structural ensemble is exemplified using MD trajectories of an ubiquitin-conjugating enzyme (UbcH5b). Furthermore, insights derived from network parameters evaluated using PSN-Ensemble for single-static structures of active/inactive states of β2-adrenergic receptor and the ternary tRNA complexes of tyrosyl tRNA synthetases (from organisms across kingdoms) are discussed. PSN-Ensemble is freely available from http://vishgraph.mbu.iisc.ernet.in/PSN-Ensemble/psn_index.html. PMID:23934896

  9. Motors and Adaptors : Transport Regulation within Neurons

    NARCIS (Netherlands)

    van Spronsen, C.S.A.M.|info:eu-repo/dai/nl/337616655

    2012-01-01

    Human thoughts and behavior are the outcome of communication between neurons in our brains. There is an entire world inside each of these neurons where transactions are established and meeting points are set. By using molecular motors to transport proteins and organelles along cytoskeletal tracks,

  10. Prediction and characterization of protein-protein interaction networks in swine

    Directory of Open Access Journals (Sweden)

    Wang Fen

    2012-01-01

    Full Text Available Abstract Background Studying the large-scale protein-protein interaction (PPI network is important in understanding biological processes. The current research presents the first PPI map of swine, which aims to give new insights into understanding their biological processes. Results We used three methods, Interolog-based prediction of porcine PPI network, domain-motif interactions from structural topology-based prediction of porcine PPI network and motif-motif interactions from structural topology-based prediction of porcine PPI network, to predict porcine protein interactions among 25,767 porcine proteins. We predicted 20,213, 331,484, and 218,705 porcine PPIs respectively, merged the three results into 567,441 PPIs, constructed four PPI networks, and analyzed the topological properties of the porcine PPI networks. Our predictions were validated with Pfam domain annotations and GO annotations. Averages of 70, 10,495, and 863 interactions were related to the Pfam domain-interacting pairs in iPfam database. For comparison, randomized networks were generated, and averages of only 4.24, 66.79, and 44.26 interactions were associated with Pfam domain-interacting pairs in iPfam database. In GO annotations, we found 52.68%, 75.54%, 27.20% of the predicted PPIs sharing GO terms respectively. However, the number of PPI pairs sharing GO terms in the 10,000 randomized networks reached 52.68%, 75.54%, 27.20% is 0. Finally, we determined the accuracy and precision of the methods. The methods yielded accuracies of 0.92, 0.53, and 0.50 at precisions of about 0.93, 0.74, and 0.75, respectively. Conclusion The results reveal that the predicted PPI networks are considerably reliable. The present research is an important pioneering work on protein function research. The porcine PPI data set, the confidence score of each interaction and a list of related data are available at (http://pppid.biositemap.com/.

  11. Small-strain dynamic rheology of food protein networks.

    Science.gov (United States)

    Tunick, Michael H

    2011-03-09

    Small-amplitude oscillatory shear analyses of samples containing protein are useful for determining the nature of the protein matrix without damaging it. G' (elastic or storage modulus), G'' (viscous or loss modulus), and tan δ (loss tangent, the ratio of G'' to G') give information on the properties of the network. Strain, frequency, time, and temperature sweeps provide information on the linear viscoelastic region, structural assembly, and thermal characteristics. The gelation point may be determined by locating the time at which tan δ is independent of frequency or the temperature at which G' becomes greater than G''. The logarithm of η* (complex viscosity) may be plotted against the reciprocal of the absolute temperature, with the slope being proportional to the activation energy. Dynamic tests of protein-containing samples reveal a great deal about their rheological characteristics.

  12. The non-motor adaptor HMMR dampens Eg5-mediated forces to preserve the kinetics and integrity of chromosome segregation.

    Science.gov (United States)

    Chen, Helen; Connell, Marisa; Mei, Lin; Reid, Gregor S D; Maxwell, Christopher A

    2018-01-31

    Mitotic spindle assembly and organization require forces generated by motor proteins. The activity of these motors is regulated by non-motor adaptor proteins. However, there are limited studies reporting the functional importance of adaptors on the balance of motor forces and the promotion of faithful and timely cell division. Here, we show that genomic deletion or siRNA silencing of the non-motor adaptor Hmmr/ HMMR disturbs spindle microtubule organization and bipolar chromosome-kinetochore attachments with a consequent elevated occurrence of aneuploidy. Rescue experiments show a conserved motif in HMMR is required to generate inter-kinetochore tension and promote anaphase entry. This motif bears high homology with the kinesin Kif15 and is known to interact with TPX2, a spindle assembly factor. We find that HMMR is required to dampen kinesin Eg5-mediated forces through localizing TPX2 and promoting the formation of inhibitory TPX2-Eg5 complexes. In HMMR-silenced cells, K-fiber stability is reduced while the frequency of unattached chromosomes and the time needed for chromosome segregation are both increased. These defects can be alleviated in HMMR-silenced cells with chemical inhibition of Eg5, but not through the silencing of Kif15. Together, our findings indicate that HMMR balances Eg5-mediated forces to preserve the kinetics and integrity of chromosome segregation. © 2018 by The American Society for Cell Biology.

  13. Information theory in systems biology. Part II: protein-protein interaction and signaling networks.

    Science.gov (United States)

    Mousavian, Zaynab; Díaz, José; Masoudi-Nejad, Ali

    2016-03-01

    By the development of information theory in 1948 by Claude Shannon to address the problems in the field of data storage and data communication over (noisy) communication channel, it has been successfully applied in many other research areas such as bioinformatics and systems biology. In this manuscript, we attempt to review some of the existing literatures in systems biology, which are using the information theory measures in their calculations. As we have reviewed most of the existing information-theoretic methods in gene regulatory and metabolic networks in the first part of the review, so in the second part of our study, the application of information theory in other types of biological networks including protein-protein interaction and signaling networks will be surveyed. Copyright © 2015 Elsevier Ltd. All rights reserved.

  14. Validation of protein models by a neural network approach

    Directory of Open Access Journals (Sweden)

    Fantucci Piercarlo

    2008-01-01

    Full Text Available Abstract Background The development and improvement of reliable computational methods designed to evaluate the quality of protein models is relevant in the context of protein structure refinement, which has been recently identified as one of the bottlenecks limiting the quality and usefulness of protein structure prediction. Results In this contribution, we present a computational method (Artificial Intelligence Decoys Evaluator: AIDE which is able to consistently discriminate between correct and incorrect protein models. In particular, the method is based on neural networks that use as input 15 structural parameters, which include energy, solvent accessible surface, hydrophobic contacts and secondary structure content. The results obtained with AIDE on a set of decoy structures were evaluated using statistical indicators such as Pearson correlation coefficients, Znat, fraction enrichment, as well as ROC plots. It turned out that AIDE performances are comparable and often complementary to available state-of-the-art learning-based methods. Conclusion In light of the results obtained with AIDE, as well as its comparison with available learning-based methods, it can be concluded that AIDE can be successfully used to evaluate the quality of protein structures. The use of AIDE in combination with other evaluation tools is expected to further enhance protein refinement efforts.

  15. Protein interaction networks as metric spaces: a novel perspective on distribution of hubs

    Science.gov (United States)

    2014-01-01

    Background In the post-genomic era, a central and overarching question in the analysis of protein-protein interaction networks continues to be whether biological characteristics and functions of proteins such as lethality, physiological malfunctions and malignancy are intimately linked to the topological role proteins play in the network as a mathematical structure. One of the key features that have implicitly been presumed is the existence of hubs, highly connected proteins considered to play a crucial role in biological networks. We explore the structure of protein interaction networks of a number of organisms as metric spaces and show that hubs are non randomly positioned and, from a distance point of view, centrally located. Results By analysing how the human functional protein interaction network, the human signalling network, Saccharomyces cerevisiae, Arabidopsis thaliana and Escherichia coli protein-protein interaction networks from various databases are distributed as metric spaces, we found that proteins interact radially through a central node, high degree proteins coagulate in the centre of the network, and those far away from the centre have low degree. We further found that the distribution of proteins from the centre is in some hierarchy of importance and has biological significance. Conclusions We conclude that structurally, protein interaction networks are mathematical entities that share properties between organisms but not necessarily with other networks that follow power-law. We therefore conclude that (i) if there are hubs defined by degree, they are not distributed randomly; (ii) zones closest to the centre of the network are enriched for critically important proteins and are also functionally very specialised for specific 'house keeping’ functions; (iii) proteins closest to the network centre are functionally less dispensable and may present good targets for therapy development; and (iv) network biology requires its own network theory

  16. Protein interaction networks as metric spaces: a novel perspective on distribution of hubs.

    Science.gov (United States)

    Fadhal, Emad; Gamieldien, Junaid; Mwambene, Eric C

    2014-01-18

    In the post-genomic era, a central and overarching question in the analysis of protein-protein interaction networks continues to be whether biological characteristics and functions of proteins such as lethality, physiological malfunctions and malignancy are intimately linked to the topological role proteins play in the network as a mathematical structure. One of the key features that have implicitly been presumed is the existence of hubs, highly connected proteins considered to play a crucial role in biological networks. We explore the structure of protein interaction networks of a number of organisms as metric spaces and show that hubs are non randomly positioned and, from a distance point of view, centrally located. By analysing how the human functional protein interaction network, the human signalling network, Saccharomyces cerevisiae, Arabidopsis thaliana and Escherichia coli protein-protein interaction networks from various databases are distributed as metric spaces, we found that proteins interact radially through a central node, high degree proteins coagulate in the centre of the network, and those far away from the centre have low degree. We further found that the distribution of proteins from the centre is in some hierarchy of importance and has biological significance. We conclude that structurally, protein interaction networks are mathematical entities that share properties between organisms but not necessarily with other networks that follow power-law. We therefore conclude that (i) if there are hubs defined by degree, they are not distributed randomly; (ii) zones closest to the centre of the network are enriched for critically important proteins and are also functionally very specialised for specific 'house keeping' functions; (iii) proteins closest to the network centre are functionally less dispensable and may present good targets for therapy development; and (iv) network biology requires its own network theory modelled on actual biological evidence

  17. Disease candidate gene identification and prioritization using protein interaction networks

    Directory of Open Access Journals (Sweden)

    Aronow Bruce J

    2009-02-01

    Full Text Available Abstract Background Although most of the current disease candidate gene identification and prioritization methods depend on functional annotations, the coverage of the gene functional annotations is a limiting factor. In the current study, we describe a candidate gene prioritization method that is entirely based on protein-protein interaction network (PPIN analyses. Results For the first time, extended versions of the PageRank and HITS algorithms, and the K-Step Markov method are applied to prioritize disease candidate genes in a training-test schema. Using a list of known disease-related genes from our earlier study as a training set ("seeds", and the rest of the known genes as a test list, we perform large-scale cross validation to rank the candidate genes and also evaluate and compare the performance of our approach. Under appropriate settings – for example, a back probability of 0.3 for PageRank with Priors and HITS with Priors, and step size 6 for K-Step Markov method – the three methods achieved a comparable AUC value, suggesting a similar performance. Conclusion Even though network-based methods are generally not as effective as integrated functional annotation-based methods for disease candidate gene prioritization, in a one-to-one comparison, PPIN-based candidate gene prioritization performs better than all other gene features or annotations. Additionally, we demonstrate that methods used for studying both social and Web networks can be successfully used for disease candidate gene prioritization.

  18. Construction and analysis of protein-protein interaction network correlated with ankylosing spondylitis.

    Science.gov (United States)

    Kanwal, Attiya; Fazal, Sahar

    2018-01-05

    Ankylosing spondylitis, a systemic illness is a foundation of progressing joint swelling that for the most part influences the spine. However, it frequently causes aggravation in different joints far from the spine, and in addition organs, for example, the eyes, heart, lungs, and kidneys. It's an immune system ailment that may be activated by specific sorts of bacterial or viral diseases that initiate an invulnerable reaction that don't close off after the contamination is recuperated. The particular reason for ankylosing spondylitis is obscure, yet hereditary qualities assume a huge part in this condition. The rising apparatuses of network medicine offer a stage to investigate an unpredictable illness at framework level. In this study, we meant to recognize the key proteins and the biological regulator pathways including in AS and further investigating the molecular connectivity between these pathways by the topological examination of the Protein-protein communication (PPI) system. The extended network including of 93 nodes and have 199 interactions respectively scanned from STRING database and some separated small networks. 24 proteins with high BC at the threshold of 0.01 and 55 proteins with large degree at the threshold of 1 have been identified. CD4 with highest BC and Closeness centrality located in the centre of the network. The backbone network derived from high BC proteins presents a clear and visual overview which shows all important regulatory pathways for AS and the crosstalk between them. The finding of this research suggests that AS variation is orchestrated by an integrated PPI network centered on CD4 out of 93 nodes. Ankylosing spondylitis, a systemic disease is an establishment of advancing joint swelling that generally impacts the spine. Be that as it may, it as often as possible causes disturbance in various joints a long way from the spine, and what's more organs. It's a resistant framework affliction that might be actuated by particular sorts

  19. Gene, protein and network of male sterility in rice

    Directory of Open Access Journals (Sweden)

    Wang eKun

    2013-04-01

    Full Text Available Rice is one of the most important model crop plants whose heterosis has been well exploited in commercial hybrid seed production via a variety of types of male sterile lines. Hybrid rice cultivation area is steadily expanding around the world, especially in Southern Asia. Characterization of genes and proteins related to male sterility aims to understand how and why the male sterility occurs, and which proteins are the key players for microspores abortion. Recently, a series of genes and proteins related to cytoplasmic male sterility, photoperiod sensitive male sterility, self-incompatibility and other types of microspores deterioration have been characterized through genetics or proteomics. Especially the latter, offers us a powerful and high throughput approach to discern the novel proteins involving in male-sterile pathways which may help us to breed artificial male-sterile system. This represents an alternative tool to meet the critical challenge of further development of hybrid rice. In this paper, we reviewed the recent developments in our understanding of male sterility in rice hybrid production across gene, protein and integrated network levels, and also, present a perspective on the engineering of male sterile lines for hybrid rice production.

  20. Multivariate Entropy Characterizes the Gene Expression and Protein-Protein Networks in Four Types of Cancer

    Directory of Open Access Journals (Sweden)

    Angel Juarez-Flores

    2018-02-01

    Full Text Available There is an important urgency to detect cancer at early stages to treat it, to improve the patients’ lifespans, and even to cure it. In this work, we determined the entropic contributions of genes in cancer networks. We detected sudden changes in entropy values in melanoma, hepatocellular carcinoma, pancreatic cancer, and squamous lung cell carcinoma associated to transitions from healthy controls to cancer. We also identified the most relevant genes involved in carcinogenic process of the four types of cancer with the help of entropic changes in local networks. Their corresponding proteins could be used as potential targets for treatments and as biomarkers of cancer.

  1. Computational 3D imaging to quantify structural components and assembly of protein networks.

    Science.gov (United States)

    Asgharzadeh, Pouyan; Özdemir, Bugra; Reski, Ralf; Röhrle, Oliver; Birkhold, Annette I

    2018-03-15

    Traditionally, protein structures have been described by the secondary structure architecture and fold arrangement. However, the relatively novel method of 3D confocal microscopy of fluorescent-protein-tagged networks in living cells allows resolving the detailed spatial organization of these networks. This provides new possibilities to predict network functionality, as structure and function seem to be linked at various scales. Here, we propose a quantitative approach using 3D confocal microscopy image data to describe protein networks based on their nano-structural characteristics. This analysis is constructed in four steps: (i) Segmentation of the microscopic raw data into a volume model and extraction of a spatial graph representing the protein network. (ii) Quantifying protein network gross morphology using the volume model. (iii) Quantifying protein network components using the spatial graph. (iv) Linking these two scales to obtain insights into network assembly. Here, we quantitatively describe the filamentous temperature sensitive Z protein network of the moss Physcomitrella patens and elucidate relations between network size and assembly details. Future applications will link network structure and functionality by tracking dynamic structural changes over time and comparing different states or types of networks, possibly allowing more precise identification of (mal) functions or the design of protein-engineered biomaterials for applications in regenerative medicine. Protein networks are highly complex and dynamic structures that play various roles in biological environments. Analyzing the detailed spatial structure of these networks may lead to new insight into biological functions and malfunctions. Here, we propose a tool set that extracts structural information at two scales of the protein network and allows therefore to address questions such as "how is the network built?" or "how networks grow?". Copyright © 2018 Acta Materialia Inc. Published by

  2. Deep recurrent conditional random field network for protein secondary prediction

    DEFF Research Database (Denmark)

    Johansen, Alexander Rosenberg; Sønderby, Søren Kaae; Sønderby, Casper Kaae

    2017-01-01

    Deep learning has become the state-of-the-art method for predicting protein secondary structure from only its amino acid residues and sequence profile. Building upon these results, we propose to combine a bi-directional recurrent neural network (biRNN) with a conditional random field (CRF), which...... of the labels for all time-steps. We condition the CRF on the output of biRNN, which learns a distributed representation based on the entire sequence. The biRNN-CRF is therefore close to ideally suited for the secondary structure task because a high degree of cross-talk between neighboring elements can...

  3. APS, an adaptor molecule containing PH and SH2 domains, has a negative regulatory role in B cell proliferation

    International Nuclear Information System (INIS)

    Iseki, Masanori; Kubo-Akashi, Chiyomi; Kwon, Sang-Mo; Yamaguchi, Akiko; Takatsu, Kiyoshi; Takaki, Satoshi

    2005-01-01

    Adaptor molecule containing PH and SH2 domains (APS) is an intracellular adaptor protein that forms part of an adaptor family along with Lnk and SH2-B. APS transcripts are expressed in various tissues including brain, kidney, and muscle, as well as in splenic B cells but not in T cells. We investigated the functions of APS in B cell development and activation by generating APS-transgenic (APS-Tg) mice that overexpressed APS in lymphocytes. The number of B-1 cells in the peritoneal cavity was reduced in APS-Tg mice, as were B-2 cells in the spleen. B cell development in the bone marrow was partially impaired at the transition stage from proliferating large pre-B to small pre-B cells. B cell proliferation induced by B cell receptor (BCR) crosslinking but not by other B cell mitogens was also impaired in APS-Tg mice. APS co-localized with BCR complexes and filamentous actin in activated APS-Tg B cells. Thus, APS appears to play novel negative regulatory roles in BCR signaling, actin reorganization pathways, and control of compartment sizes of B-lineage cells

  4. 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.

  5. Dynamic circadian protein-protein interaction networks predict temporal organization of cellular functions.

    Directory of Open Access Journals (Sweden)

    Thomas Wallach

    2013-03-01

    Full Text Available Essentially all biological processes depend on protein-protein interactions (PPIs. Timing of such interactions is crucial for regulatory function. Although circadian (~24-hour clocks constitute fundamental cellular timing mechanisms regulating important physiological processes, PPI dynamics on this timescale are largely unknown. Here, we identified 109 novel PPIs among circadian clock proteins via a yeast-two-hybrid approach. Among them, the interaction of protein phosphatase 1 and CLOCK/BMAL1 was found to result in BMAL1 destabilization. We constructed a dynamic circadian PPI network predicting the PPI timing using circadian expression data. Systematic circadian phenotyping (RNAi and overexpression suggests a crucial role for components involved in dynamic interactions. Systems analysis of a global dynamic network in liver revealed that interacting proteins are expressed at similar times likely to restrict regulatory interactions to specific phases. Moreover, we predict that circadian PPIs dynamically connect many important cellular processes (signal transduction, cell cycle, etc. contributing to temporal organization of cellular physiology in an unprecedented manner.

  6. The role of exon shuffling in shaping protein-protein interaction networks

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    França Gustavo S

    2010-12-01

    Full Text Available Abstract Background Physical protein-protein interaction (PPI is a critical phenomenon for the function of most proteins in living organisms and a significant fraction of PPIs are the result of domain-domain interactions. Exon shuffling, intron-mediated recombination of exons from existing genes, is known to have been a major mechanism of domain shuffling in metazoans. Thus, we hypothesized that exon shuffling could have a significant influence in shaping the topology of PPI networks. Results We tested our hypothesis by compiling exon shuffling and PPI data from six eukaryotic species: Homo sapiens, Mus musculus, Drosophila melanogaster, Caenorhabditis elegans, Cryptococcus neoformans and Arabidopsis thaliana. For all four metazoan species, genes enriched in exon shuffling events presented on average higher vertex degree (number of interacting partners in PPI networks. Furthermore, we verified that a set of protein domains that are simultaneously promiscuous (known to interact to multiple types of other domains, self-interacting (able to interact with another copy of themselves and abundant in the genomes presents a stronger signal for exon shuffling. Conclusions Exon shuffling appears to have been a recurrent mechanism for the emergence of new PPIs along metazoan evolution. In metazoan genomes, exon shuffling also promoted the expansion of some protein domains. We speculate that their promiscuous and self-interacting properties may have been decisive for that expansion.

  7. Visualization of protein interaction networks: problems and solutions

    Science.gov (United States)

    2013-01-01

    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 possibility to

  8. Reconstruction of the yeast protein-protein interaction network involved in nutrient sensing and global metabolic regulation

    DEFF Research Database (Denmark)

    Nandy, Subir Kumar; Jouhten, Paula; Nielsen, Jens

    2010-01-01

    BACKGROUND: Several protein-protein interaction studies have been performed for the yeast Saccharomyces cerevisiae using different high-throughput experimental techniques. All these results are collected in the BioGRID database and the SGD database provide detailed annotation of the different......-sensing and metabolic regulatory signal transduction pathways (STP) operating in Saccharomyces cerevisiae. The reconstructed STP network includes a full protein-protein interaction network including the key nodes Snf1, Tor1, Hog1 and Pka1. The network includes a total of 623 structural open reading frames (ORFs...

  9. A human protein interaction network shows conservation of aging processes between human and invertebrate species.

    Directory of Open Access Journals (Sweden)

    Russell Bell

    2009-03-01

    Full Text Available We have mapped a protein interaction network of human homologs of proteins that modify longevity in invertebrate species. This network is derived from a proteome-scale human protein interaction Core Network generated through unbiased high-throughput yeast two-hybrid searches. The longevity network is composed of 175 human homologs of proteins known to confer increased longevity through loss of function in yeast, nematode, or fly, and 2,163 additional human proteins that interact with these homologs. Overall, the network consists of 3,271 binary interactions among 2,338 unique proteins. A comparison of the average node degree of the human longevity homologs with random sets of proteins in the Core Network indicates that human homologs of longevity proteins are highly connected hubs with a mean node degree of 18.8 partners. Shortest path length analysis shows that proteins in this network are significantly more connected than would be expected by chance. To examine the relationship of this network to human aging phenotypes, we compared the genes encoding longevity network proteins to genes known to be changed transcriptionally during aging in human muscle. In the case of both the longevity protein homologs and their interactors, we observed enrichments for differentially expressed genes in the network. To determine whether homologs of human longevity interacting proteins can modulate life span in invertebrates, homologs of 18 human FRAP1 interacting proteins showing significant changes in human aging muscle were tested for effects on nematode life span using RNAi. Of 18 genes tested, 33% extended life span when knocked-down in Caenorhabditis elegans. These observations indicate that a broad class of longevity genes identified in invertebrate models of aging have relevance to human aging. They also indicate that the longevity protein interaction network presented here is enriched for novel conserved longevity proteins.

  10. A Topology Potential-Based Method for Identifying Essential Proteins from PPI Networks.

    Science.gov (United States)

    Li, Min; Lu, Yu; Wang, Jianxin; Wu, Fang-Xiang; Pan, Yi

    2015-01-01

    Essential proteins are indispensable for cellular life. It is of great significance to identify essential proteins that can help us understand the minimal requirements for cellular life and is also very important for drug design. However, identification of essential proteins based on experimental approaches are typically time-consuming and expensive. With the development of high-throughput technology in the post-genomic era, more and more protein-protein interaction data can be obtained, which make it possible to study essential proteins from the network level. There have been a series of computational approaches proposed for predicting essential proteins based on network topologies. Most of these topology based essential protein discovery methods were to use network centralities. In this paper, we investigate the essential proteins' topological characters from a completely new perspective. To our knowledge it is the first time that topology potential is used to identify essential proteins from a protein-protein interaction (PPI) network. The basic idea is that each protein in the network can be viewed as a material particle which creates a potential field around itself and the interaction of all proteins forms a topological field over the network. By defining and computing the value of each protein's topology potential, we can obtain a more precise ranking which reflects the importance of proteins from the PPI network. The experimental results show that topology potential-based methods TP and TP-NC outperform traditional topology measures: degree centrality (DC), betweenness centrality (BC), closeness centrality (CC), subgraph centrality (SC), eigenvector centrality (EC), information centrality (IC), and network centrality (NC) for predicting essential proteins. In addition, these centrality measures are improved on their performance for identifying essential proteins in biological network when controlled by topology potential.

  11. Effective comparative analysis of protein-protein interaction networks by measuring the steady-state network flow using a Markov model.

    Science.gov (United States)

    Jeong, Hyundoo; Qian, Xiaoning; Yoon, Byung-Jun

    2016-10-06

    Comparative analysis of protein-protein interaction (PPI) networks provides an effective means of detecting conserved functional network modules across different species. Such modules typically consist of orthologous proteins with conserved interactions, which can be exploited to computationally predict the modules through network comparison. In this work, we propose a novel probabilistic framework for comparing PPI networks and effectively predicting the correspondence between proteins, represented as network nodes, that belong to conserved functional modules across the given PPI networks. The basic idea is to estimate the steady-state network flow between nodes that belong to different PPI networks based on a Markov random walk model. The random walker is designed to make random moves to adjacent nodes within a PPI network as well as cross-network moves between potential orthologous nodes with high sequence similarity. Based on this Markov random walk model, we estimate the steady-state network flow - or the long-term relative frequency of the transitions that the random walker makes - between nodes in different PPI networks, which can be used as a probabilistic score measuring their potential correspondence. Subsequently, the estimated scores can be used for detecting orthologous proteins in conserved functional modules through network alignment. Through evaluations based on multiple real PPI networks, we demonstrate that the proposed scheme leads to improved alignment results that are biologically more meaningful at reduced computational cost, outperforming the current state-of-the-art algorithms. The source code and datasets can be downloaded from http://www.ece.tamu.edu/~bjyoon/CUFID .

  12. Towards a map of the Populus biomass protein-protein interaction network

    Energy Technology Data Exchange (ETDEWEB)

    Beers, Eric [Virginia Polytechnic Inst. and State Univ. (Virginia Tech), Blacksburg, VA (United States); Brunner, Amy [Virginia Polytechnic Inst. and State Univ. (Virginia Tech), Blacksburg, VA (United States); Helm, Richard [Virginia Polytechnic Inst. and State Univ. (Virginia Tech), Blacksburg, VA (United States); Dickerman, Allan [Virginia Polytechnic Inst. and State Univ. (Virginia Tech), Blacksburg, VA (United States)

    2015-07-31

    -depth characterizations. Characterizations involved both in vivo and in vitro independent methods to confirm protein-protein interactions and the evaluation of novel phenotypes resulting from creation of transgenic poplar and Arabidopsis plants engineered for increased or decreased expression of the selected genes. Transgenic poplar trees were studied in growth chamber, greenhouse, and two separate replicated field trials involving over 25 distinct wood-associated proteins. In-depth characterizations yielding positive results include the following. First, a NAC domain transcription factor (NAC154) that is a promoter of stress response and dormancy in trees was discovered. Increasing expression of NAC154 caused stunted growth and premature senescence, while decreasing expression led to both delayed bud and leaf expansion in spring and delayed leaf drop (i.e., prolonged leaf retention) in fall. Second, we discovered and characterized a new connection between a negative regulator of wood formation, the NAC domain transcription factor XND1, and an important regulator of cell division and cell differentiation, RBR. Third, we identified a new network of interacting wood-associated transcription factors belonging to the MYB and HD families. One of the HD family proteins, WOX13, was used to prepare transgenic poplar for high-level expression, resulting in significantly increased lateral branch growth. Finally, we modeled and performed in vitro analyses of the insect protein rubber resilin and we prepared transgenic Arabidopsis plants for expression of resilin to test the feasibility of using resilin to modify lignin cross-linking in wood and reduce recalcitrance and improve yield of fermentable sugars for biofuels production. Analysis of these and additional transgenics created with this support is continuing.

  13. Weighted Protein Interaction Network Analysis of Frontotemporal Dementia.

    Science.gov (United States)

    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.

  14. Category Theoretic Analysis of Hierarchical Protein Materials and Social Networks

    Science.gov (United States)

    Spivak, David I.; Giesa, Tristan; Wood, Elizabeth; Buehler, Markus J.

    2011-01-01

    Materials in biology span all the scales from Angstroms to meters and typically consist of complex hierarchical assemblies of simple building blocks. Here we describe an application of category theory to describe structural and resulting functional properties of biological protein materials by developing so-called ologs. An olog is like a “concept web” or “semantic network” except that it follows a rigorous mathematical formulation based on category theory. This key difference ensures that an olog is unambiguous, highly adaptable to evolution and change, and suitable for sharing concepts with other olog. We consider simple cases of beta-helical and amyloid-like protein filaments subjected to axial extension and develop an olog representation of their structural and resulting mechanical properties. We also construct a representation of a social network in which people send text-messages to their nearest neighbors and act as a team to perform a task. We show that the olog for the protein and the olog for the social network feature identical category-theoretic representations, and we proceed to precisely explicate the analogy or isomorphism between them. The examples presented here demonstrate that the intrinsic nature of a complex system, which in particular includes a precise relationship between structure and function at different hierarchical levels, can be effectively represented by an olog. This, in turn, allows for comparative studies between disparate materials or fields of application, and results in novel approaches to derive functionality in the design of de novo hierarchical systems. We discuss opportunities and challenges associated with the description of complex biological materials by using ologs as a powerful tool for analysis and design in the context of materiomics, and we present the potential impact of this approach for engineering, life sciences, and medicine. PMID:21931622

  15. SLIDER: a generic metaheuristic for the discovery of correlated motifs in protein-protein interaction networks.

    Science.gov (United States)

    Boyen, Peter; Van Dyck, Dries; Neven, Frank; van Ham, Roeland C H J; van Dijk, Aalt D J

    2011-01-01

    Correlated motif mining (cmm) is the problem of finding overrepresented pairs of patterns, called motifs, in sequences of interacting proteins. Algorithmic solutions for cmm thereby provide a computational method for predicting binding sites for protein interaction. In this paper, we adopt a motif-driven approach where the support of candidate motif pairs is evaluated in the network. We experimentally establish the superiority of the Chi-square-based support measure over other support measures. Furthermore, we obtain that cmm is an np-hard problem for a large class of support measures (including Chi-square) and reformulate the search for correlated motifs as a combinatorial optimization problem. We then present the generic metaheuristic slider which uses steepest ascent with a neighborhood function based on sliding motifs and employs the Chi-square-based support measure. We show that slider outperforms existing motif-driven cmm methods and scales to large protein-protein interaction networks. The slider-implementation and the data used in the experiments are available on http://bioinformatics.uhasselt.be.

  16. Protein-protein interaction network and subcellular localization of the Arabidopsis thaliana ESCRT machinery

    Directory of Open Access Journals (Sweden)

    Lynn eRichardson

    2011-06-01

    Full Text Available The Endosomal Sorting Complex Required for Transport (ESCRT consists of several multi-protein subcomplexes which assemble sequentially at the endosomal surface and function in multivesicular body (MVB biogenesis. While ESCRT has been relatively well characterized in yeasts and mammals, comparably little is known about ESCRT in plants. Here we explored the yeast two-hybrid protein interaction network and subcellular localization of the Arabidopsis thaliana ESCRT machinery. We show that Arabidopsis ESCRT interactome possess a number of protein-protein interactions that are either conserved in yeasts and mammals or distinct to plants. We show also that most of the Arabidopsis ESCRT proteins examined at least partially localize to MVBs in plant cells when ectopically expressed on their own or co-expressed with other interacting ESCRT proteins, and some also induce abnormal MVB phenotypes, consistent with their proposed functional roles in MVB biogenesis. Overall, our results help define the plant ESCRT machinery by highlighting both conserved and unique features when compared to ESCRT in other evolutionarily diverse organisms, providing a foundation for further exploration of ESCRT in plants.

  17. Discovering Protein-Protein Interactions within the Programmed Cell Death Network Using a Protein-Fragment Complementation Screen

    Directory of Open Access Journals (Sweden)

    Yuval Gilad

    2014-08-01

    Full Text Available Apoptosis and autophagy are distinct biological processes, each driven by a different set of protein-protein interactions, with significant crosstalk via direct interactions among apoptotic and autophagic proteins. To measure the global profile of these interactions, we adapted the Gaussia luciferase protein-fragment complementation assay (GLuc PCA, which monitors binding between proteins fused to complementary fragments of a luciferase reporter. A library encompassing 63 apoptotic and autophagic proteins was constructed for the analysis of ∼3,600 protein-pair combinations. This generated a detailed landscape of the apoptotic and autophagic modules and points of interface between them, identifying 46 previously unknown interactions. One of these interactions, between DAPK2, a Ser/Thr kinase that promotes autophagy, and 14-3-3τ, was further investigated. We mapped the region responsible for 14-3-3τ binding and proved that this interaction inhibits DAPK2 dimerization and activity. This proof of concept underscores the power of the GLuc PCA platform for the discovery of biochemical pathways within the cell death network.

  18. Predicting human protein subcellular locations by the ensemble of multiple predictors via protein-protein interaction network with edge clustering coefficients.

    Directory of Open Access Journals (Sweden)

    Pufeng Du

    Full Text Available One of the fundamental tasks in biology is to identify the functions of all proteins to reveal the primary machinery of a cell. Knowledge of the subcellular locations of proteins will provide key hints to reveal their functions and to understand the intricate pathways that regulate biological processes at the cellular level. Protein subcellular location prediction has been extensively studied in the past two decades. A lot of methods have been developed based on protein primary sequences as well as protein-protein interaction network. In this paper, we propose to use the protein-protein interaction network as an infrastructure to integrate existing sequence based predictors. When predicting the subcellular locations of a given protein, not only the protein itself, but also all its interacting partners were considered. Unlike existing methods, our method requires neither the comprehensive knowledge of the protein-protein interaction network nor the experimentally annotated subcellular locations of most proteins in the protein-protein interaction network. Besides, our method can be used as a framework to integrate multiple predictors. Our method achieved 56% on human proteome in absolute-true rate, which is higher than the state-of-the-art methods.

  19. STRING v9.1: protein-protein interaction networks, with increased coverage and integration.

    Science.gov (United States)

    Franceschini, Andrea; Szklarczyk, Damian; Frankild, Sune; Kuhn, Michael; Simonovic, Milan; Roth, Alexander; Lin, Jianyi; Minguez, Pablo; Bork, Peer; von Mering, Christian; Jensen, Lars J

    2013-01-01

    Complete knowledge of all direct and indirect interactions between proteins in a given cell would represent an important milestone towards a comprehensive description of cellular mechanisms and functions. Although this goal is still elusive, considerable progress has been made-particularly for certain model organisms and functional systems. Currently, protein interactions and associations are annotated at various levels of detail in online resources, ranging from raw data repositories to highly formalized pathway databases. For many applications, a global view of all the available interaction data is desirable, including lower-quality data and/or computational predictions. The STRING database (http://string-db.org/) aims to provide such a global perspective for as many organisms as feasible. Known and predicted associations are scored and integrated, resulting in comprehensive protein networks covering >1100 organisms. Here, we describe the update to version 9.1 of STRING, introducing several improvements: (i) we extend the automated mining of scientific texts for interaction information, to now also include full-text articles; (ii) we entirely re-designed the algorithm for transferring interactions from one model organism to the other; and (iii) we provide users with statistical information on any functional enrichment observed in their networks.

  20. Interaction and localization diversities of global and local hubs in human protein-protein interaction networks.

    Science.gov (United States)

    Kiran, M; Nagarajaram, H A

    2016-08-16

    Hubs, the highly connected nodes in protein-protein interaction networks (PPINs), are associated with several characteristic properties and are known to perform vital roles in cells. We defined two classes of hubs, global (housekeeping) and local (tissue-specific) hubs. These two categories of hubs are distinct from each other with respect to their abundance, structure and function. However, how distinct are the spatial expression pattern and other characteristics of their interacting partners is still not known. Our investigations revealed that the partners of the local hubs compared with those of global hubs are conserved across the tissues in which they are expressed. Partners of local hubs show diverse subcellular localizations as compared with the partners of global hubs. We examined the nature of interacting domains in both categories of hubs and found that they are promiscuous in global hubs but not so in local hubs. Deletion of some of the local and global hubs has an impact on the characteristic path length of the network indicating that those hubs are inter-modular in nature. Our present study has, therefore, shed further light on the characteristic features of the local and global hubs in human PPIN. This knowledge of different topological aspects of hubs with regard to their types and subtypes is essential as it helps in better understanding of roles of hub proteins in various cellular processes under various conditions including those caused by host-pathogen interactions and therefore useful in prioritizing targets for drug design and repositioning.

  1. Global versus local hubs in human protein-protein interaction network.

    Science.gov (United States)

    Kiran, Manjari; Nagarajaram, Hampapathalu Adimurthy

    2013-12-06

    In this study, we have constructed tissue-specific protein-protein interaction networks for 70 human tissues and have identified three types of hubs based on their expression breadths: (a) tissue-specific hubs (TSHs) (proteins that are expressed in ≤ 10 tissues and also form hubs in ≤ 10 tissues), (b) tissue-preferred hubs (TPHs) (proteins expressed in ≥ 60 tissues but are highly connected in ≤ 10 tissues), and (c) housekeeping hubs (HKHs) (proteins that are expressed in ≥ 60 tissues and also form hubs in ≥ 60 tissues). Comparative analyses revealed significant differences between TSHs and HKHs and also revealed that TPHs behave more like HKHs. TSHs are lengthier, more disordered, and also quickly evolving proteins as compared with HKHs. Despite having a similar number of binding surfaces and interacting domains, TSHs are associated with a lower degree of centrality as compared with HKHs, suggesting that TSHs are "unsaturated" with regard to their binding capability and are perhaps evolving with regard to their interactions. TSHs are less abundantly expressed as compared with HKHs and are enriched with PEST motifs, indicating their tight regulation. All of these properties of TSHs and HKHs correlate with their distinct functional roles; TSHs are involved in tissue-specific functional roles, viz., secretors, receptors, and signaling proteins, whereas HKHs are involved in core-cellular functions such as transcription, translation, and so on. Our study, therefore, brings forth a clear and distinct classification of hubs simply based on their expression breadth and further assumes significance in the light of the highly debated dichotomy of date and party hubs, which is based on the coexpression pattern of hubs with their partners.

  2. Insight into bacterial virulence mechanisms against host immune response via the Yersinia pestis-human protein-protein interaction network.

    Science.gov (United States)

    Yang, Huiying; Ke, Yuehua; Wang, Jian; Tan, Yafang; Myeni, Sebenzile K; Li, Dong; Shi, Qinghai; Yan, Yanfeng; Chen, Hui; Guo, Zhaobiao; Yuan, Yanzhi; Yang, Xiaoming; Yang, Ruifu; Du, Zongmin

    2011-11-01

    A Yersinia pestis-human protein interaction network is reported here to improve our understanding of its pathogenesis. Up to 204 interactions between 66 Y. pestis bait proteins and 109 human proteins were identified by yeast two-hybrid assay and then combined with 23 previously published interactions to construct a protein-protein interaction network. Topological analysis of the interaction network revealed that human proteins targeted by Y. pestis were significantly enriched in the proteins that are central in the human protein-protein interaction network. Analysis of this network showed that signaling pathways important for host immune responses were preferentially targeted by Y. pestis, including the pathways involved in focal adhesion, regulation of cytoskeleton, leukocyte transendoepithelial migration, and Toll-like receptor (TLR) and mitogen-activated protein kinase (MAPK) signaling. Cellular pathways targeted by Y. pestis are highly relevant to its pathogenesis. Interactions with host proteins involved in focal adhesion and cytoskeketon regulation pathways could account for resistance of Y. pestis to phagocytosis. Interference with TLR and MAPK signaling pathways by Y. pestis reflects common characteristics of pathogen-host interaction that bacterial pathogens have evolved to evade host innate immune response by interacting with proteins in those signaling pathways. Interestingly, a large portion of human proteins interacting with Y. pestis (16/109) also interacted with viral proteins (Epstein-Barr virus [EBV] and hepatitis C virus [HCV]), suggesting that viral and bacterial pathogens attack common cellular functions to facilitate infections. In addition, we identified vasodilator-stimulated phosphoprotein (VASP) as a novel interaction partner of YpkA and showed that YpkA could inhibit in vitro actin assembly mediated by VASP.

  3. Perturbation waves in proteins and protein networks: applications of percolation and game theories in signaling and drug design.

    Science.gov (United States)

    Antal, Miklós A; Böde, Csaba; Csermely, Peter

    2009-04-01

    The network paradigm is increasingly used to describe the dynamics of complex systems. Here we review the current results and propose future development areas in the assessment of perturbation waves, i.e. propagating structural changes in amino acid networks building individual protein molecules and in protein-protein interaction networks (interactomes). We assess the possibilities and critically review the initial attempts for the application of game theory to the often rather complicated process, when two protein molecules approach each other, mutually adjust their conformations via multiple communication steps and finally, bind to each other. We also summarize available data on the application of percolation theory for the prediction of amino acid network- and interactome-dynamics. Furthermore, we give an overview of the dissection of signals and noise in the cellular context of various perturbations. Finally, we propose possible applications of the reviewed methodologies in drug design.

  4. A Big-Five Personality Profile of the Adaptor and Innovator.

    Science.gov (United States)

    Kwang, Ng Aik; Rodrigues, Daphne

    2002-01-01

    A study explored the relationship between two creative types (adaptor and innovator) and the Big Five personality traits (extraversion, agreeableness, conscientiousness, neuroticism, and openness to experience), in 164 teachers in Singapore. Adaptors were significantly more conscientious than innovators, while innovators were significantly more…

  5. 21 CFR 870.4290 - Cardiopulmonary bypass adaptor, stopcock, manifold, or fitting.

    Science.gov (United States)

    2010-04-01

    ..., or fitting. 870.4290 Section 870.4290 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF... Devices § 870.4290 Cardiopulmonary bypass adaptor, stopcock, manifold, or fitting. (a) Identification. A cardiopulmonary bypass adaptor, stopcock, manifold, or fitting is a device used in cardiovascular diagnostic...

  6. Arabidopsis protein phosphatase DBP1 nucleates a protein network with a role in regulating plant defense.

    Directory of Open Access Journals (Sweden)

    José Luis Carrasco

    Full Text Available Arabidopsis thaliana DBP1 belongs to the plant-specific family of DNA-binding protein phosphatases. Although recently identified as a novel host factor mediating susceptibility to potyvirus, little is known about DBP1 targets and partners and the molecular mechanisms underlying its function. Analyzing changes in the phosphoproteome of a loss-of-function dbp1 mutant enabled the identification of 14-3-3λ isoform (GRF6, a previously reported DBP1 interactor, and MAP kinase (MAPK MPK11 as components of a small protein network nucleated by DBP1, in which GRF6 stability is modulated by MPK11 through phosphorylation, while DBP1 in turn negatively regulates MPK11 activity. Interestingly, grf6 and mpk11 loss-of-function mutants showed altered response to infection by the potyvirus Plum pox virus (PPV, and the described molecular mechanism controlling GRF6 stability was recapitulated upon PPV infection. These results not only contribute to a better knowledge of the biology of DBP factors, but also of MAPK signalling in plants, with the identification of GRF6 as a likely MPK11 substrate and of DBP1 as a protein phosphatase regulating MPK11 activity, and unveils the implication of this protein module in the response to PPV infection in Arabidopsis.

  7. Large-scale identification of potential drug targets based on the topological features of human protein-protein interaction network.

    Science.gov (United States)

    Li, Zhan-Chao; Zhong, Wen-Qian; Liu, Zhi-Qing; Huang, Meng-Hua; Xie, Yun; Dai, Zong; Zou, Xiao-Yong

    2015-04-29

    Identifying potential drug target proteins is a crucial step in the process of drug discovery and plays a key role in the study of the molecular mechanisms of disease. Based on the fact that the majority of proteins exert their functions through interacting with each other, we propose a method to recognize target proteins by using the human protein-protein interaction network and graph theory. In the network, vertexes and edges are weighted by using the confidence scores of interactions and descriptors of protein primary structure, respectively. The novel network topological features are defined and employed to characterize protein using existing databases. A widely used minimum redundancy maximum relevance and random forests algorithm are utilized to select the optimal feature subset and construct model for the identification of potential drug target proteins at the proteome scale. The accuracies of training set and test set are 89.55% and 85.23%. Using the constructed model, 2127 potential drug target proteins have been recognized and 156 drug target proteins have been validated in the database of drug target. In addition, some new drug target proteins can be considered as targets for treating diseases of mucopolysaccharidosis, non-arteritic anterior ischemic optic neuropathy, Bernard-Soulier syndrome and pseudo-von Willebrand, etc. It is anticipated that the proposed method may became a powerful high-throughput virtual screening tool of drug target. Copyright © 2015 Elsevier B.V. All rights reserved.

  8. Phospho-dependent binding of the clathrin AP2 adaptor complex to GABAA receptors regulates the efficacy of inhibitory synaptic transmission

    OpenAIRE

    Kittler, Josef T.; Chen, Guojun; Honing, Stephan; Bogdanov, Yury; McAinsh, Kristina; Arancibia-Carcamo, I. Lorena; Jovanovic, Jasmina N.; Pangalos, Menelas N.; Haucke, Volker; Yan, Zhen; Moss, Stephen J.

    2005-01-01

    The efficacy of synaptic inhibition depends on the number of γ-aminobutyric acid type A receptors (GABAARs) expressed on the cell surface of neurons. The clathrin adaptor protein 2 (AP2) complex is a critical regulator of GABAAR endocytosis and, hence, surface receptor number. Here, we identify a previously uncharacterized atypical AP2 binding motif conserved within the intracellular domains of all GABAAR β subunit isoforms. This AP2 binding motif (KTHLRRRSSQLK in the β3 subunit) incorporates...

  9. Cost Function Network-based Design of Protein-Protein Interactions: predicting changes in binding affinity.

    Science.gov (United States)

    Viricel, Clément; de Givry, Simon; Schiex, Thomas; Barbe, Sophie

    2018-02-20

    Accurate and economic methods to predict change in protein binding free energy upon mutation are imperative to accelerate the design of proteins for a wide range of applications. Free energy is defined by enthalpic and entropic contributions. Following the recent progresses of Artificial Intelligence-based algorithms for guaranteed NP-hard energy optimization and partition function computation, it becomes possible to quickly compute minimum energy conformations and to reliably estimate the entropic contribution of side-chains in the change of free energy of large protein interfaces. Using guaranteed Cost Function Network algorithms, Rosetta energy functions and Dunbrack's rotamer library, we developed and assessed EasyE and JayZ, two methods for binding affinity estimation that ignore or include conformational entropic contributions on a large benchmark of binding affinity experimental measures. If both approaches outperform most established tools, we observe that side-chain conformational entropy brings little or no improvement on most systems but becomes crucial in some rare cases. as open-source Python/C ++ code at sourcesup.renater.fr/projects/easy-jayz. thomas.schiex@inra.fr and sophie.barbe@insa-toulouse.fr. Supplementary data are available at Bioinformatics online.

  10. Reconstituting Protein Interaction Networks Using Parameter-Dependent Domain-Domain Interactions

    Science.gov (United States)

    2013-05-07

    that approximately 80% of eukaryotic proteins and 67% of prokaryotic proteins have multiple domains [13,14]. Most annotation databases characterize...domain annotations, Domain-domain interactions, Protein-protein interaction networks Background The living cell is a dynamic, interconnected system...detailed in Methods. Here, we illustrate its application on a well- annotated single- cell organism. We created a merged set of protein-domain annotations

  11. Combining sequence and Gene Ontology for protein module detection in the Weighted Network.

    Science.gov (United States)

    Yu, Yang; Liu, Jie; Feng, Nuan; Song, Bo; Zheng, Zeyu

    2017-01-07

    Studies of protein modules in a Protein-Protein Interaction (PPI) network contribute greatly to the understanding of biological mechanisms. With the development of computing science, computational approaches have played an important role in locating protein modules. In this paper, a new approach combining Gene Ontology and amino acid background frequency is introduced to detect the protein modules in the weighted PPI networks. The proposed approach mainly consists of three parts: the feature extraction, the weighted graph construction and the protein complex detection. Firstly, the topology-sequence information is utilized to present the feature of protein complex. Secondly, six types of the weighed graph are constructed by combining PPI network and Gene Ontology information. Lastly, protein complex algorithm is applied to the weighted graph, which locates the clusters based on three conditions, including density, network diameter and the included angle cosine. Experiments have been conducted on two protein complex benchmark sets for yeast and the results show that the approach is more effective compared to five typical algorithms with the performance of f-measure and precision. The combination of protein interaction network with sequence and gene ontology data is helpful to improve the performance and provide a optional method for protein module detection. Copyright © 2016 Elsevier Ltd. All rights reserved.

  12. A network biology approach to understanding the importance of chameleon proteins in human physiology and pathology.

    Science.gov (United States)

    Bahramali, Golnaz; Goliaei, Bahram; Minuchehr, Zarrin; Marashi, Sayed-Amir

    2017-02-01

    Chameleon proteins are proteins which include sequences that can adopt α-helix-β-strand (HE-chameleon) or α-helix-coil (HC-chameleon) or β-strand-coil (CE-chameleon) structures to operate their crucial biological functions. In this study, using a network-based approach, we examined the chameleon proteins to give a better knowledge on these proteins. We focused on proteins with identical chameleon sequences with more than or equal to seven residues long in different PDB entries, which adopt HE-chameleon, HC-chameleon, and CE-chameleon structures in the same protein. One hundred and ninety-one human chameleon proteins were identified via our in-house program. Then, protein-protein interaction (PPI) networks, Gene ontology (GO) enrichment, disease network, and pathway enrichment analyses were performed for our derived data set. We discovered that there are chameleon sequences which reside in protein-protein interaction regions between two proteins critical for their dual function. Analysis of the PPI networks for chameleon proteins introduced five hub proteins, namely TP53, EGFR, HSP90AA1, PPARA, and HIF1A, which were presented in four PPI clusters. The outcomes demonstrate that the chameleon regions are in critical domains of these proteins and are important in the development and treatment of human cancers. The present report is the first network-based functional study of chameleon proteins using computational approaches and might provide a new perspective for understanding the mechanisms of diseases helping us in developing new medical therapies along with discovering new proteins with chameleon properties which are highly important in cancer.

  13. Creating a specialist protein resource network: a meeting report for the protein bioinformatics and community resources retreat

    DEFF Research Database (Denmark)

    Babbitt, Patricia C.; Bagos, Pantelis G.; Bairoch, Amos

    2015-01-01

    protein databases from the large Bioinformatics centres (including UniProt and RefSeq). The retreat was divided into five sessions: (1) key challenges, (2) the databases represented, (3) best practices for maintenance and curation, (4) information flow to and from large data centers and (5) communication...... and funding. An important outcome of this meeting was the creation of a Specialist Protein Resource Network that we believe will improve coordination of the activities of its member resources. We invite further protein database resources to join the network and continue the dialogue....

  14. Protein Signaling Networks from Single Cell Fluctuations and Information Theory Profiling

    Science.gov (United States)

    Shin, Young Shik; Remacle, F.; Fan, Rong; Hwang, Kiwook; Wei, Wei; Ahmad, Habib; Levine, R.D.; Heath, James R.

    2011-01-01

    Protein signaling networks among cells play critical roles in a host of pathophysiological processes, from inflammation to tumorigenesis. We report on an approach that integrates microfluidic cell handling, in situ protein secretion profiling, and information theory to determine an extracellular protein-signaling network and the role of perturbations. We assayed 12 proteins secreted from human macrophages that were subjected to lipopolysaccharide challenge, which emulates the macrophage-based innate immune responses against Gram-negative bacteria. We characterize the fluctuations in protein secretion of single cells, and of small cell colonies (n = 2, 3,···), as a function of colony size. Measuring the fluctuations permits a validation of the conditions required for the application of a quantitative version of the Le Chatelier's principle, as derived using information theory. This principle provides a quantitative prediction of the role of perturbations and allows a characterization of a protein-protein interaction network. PMID:21575571

  15. MetaGO: Predicting Gene Ontology of non-homologous proteins through low-resolution protein structure prediction and protein-protein network mapping.

    Science.gov (United States)

    Zhang, Chengxin; Zheng, Wei; Freddolino, Peter L; Zhang, Yang

    2018-03-10

    Homology-based transferal remains the major approach to computational protein function annotations, but it becomes increasingly unreliable when the sequence identity between query and template decreases below 30%. We propose a novel pipeline, MetaGO, to deduce Gene Ontology attributes of proteins by combining sequence homology-based annotation with low-resolution structure prediction and comparison, and partner's-homology based protein-protein network mapping. The pipeline was tested on a large-scale set of 1000 non-redundant proteins from the CAFA3 experiment. Under the stringent benchmark conditions where templates with >30% sequence identity to the query are excluded, MetaGO achieves average F-measures of 0.487, 0.408, and 0.598, for Molecular Function, Biological Process, and Cellular Component, respectively, which are significantly higher than those achieved by other state-of-the-art function annotations methods. Detailed data analysis shows that the major advantage of the MetaGO lies in the new functional homolog detections from partner's-homology based network mapping and structure-based local and global structure alignments, the confidence scores of which can be optimally combined through logistic regression. These data demonstrate the power of using a hybrid model incorporating protein structure and interaction networks to deduce new functional insights beyond traditional sequence-homology based referrals, especially for proteins that lack homologous function templates. The MetaGO pipeline is available at http://zhanglab.ccmb.med.umich.edu/MetaGO/. Copyright © 2018. Published by Elsevier Ltd.

  16. 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

  17. Identifying potential survival strategies of HIV-1 through virus-host protein interaction networks

    Directory of Open Access Journals (Sweden)

    Boucher Charles AB

    2010-07-01

    Full Text Available Abstract Background The National Institute of Allergy and Infectious Diseases has launched the HIV-1 Human Protein Interaction Database in an effort to catalogue all published interactions between HIV-1 and human proteins. In order to systematically investigate these interactions functionally and dynamically, we have constructed an HIV-1 human protein interaction network. This network was analyzed for important proteins and processes that are specific for the HIV life-cycle. In order to expose viral strategies, network motif analysis was carried out showing reoccurring patterns in virus-host dynamics. Results Our analyses show that human proteins interacting with HIV form a densely connected and central sub-network within the total human protein interaction network. The evaluation of this sub-network for connectivity and centrality resulted in a set of proteins essential for the HIV life-cycle. Remarkably, we were able to associate proteins involved in RNA polymerase II transcription with hubs and proteasome formation with bottlenecks. Inferred network motifs show significant over-representation of positive and negative feedback patterns between virus and host. Strikingly, such patterns have never been reported in combined virus-host systems. Conclusions HIV infection results in a reprioritization of cellular processes reflected by an increase in the relative importance of transcriptional machinery and proteasome formation. We conclude that during the evolution of HIV, some patterns of interaction have been selected for resulting in a system where virus proteins preferably interact with central human proteins for direct control and with proteasomal proteins for indirect control over the cellular processes. Finally, the patterns described by network motifs illustrate how virus and host interact with one another.

  18. Similar pathogen targets in Arabidopsis thaliana and homo sapiens protein networks.

    Directory of Open Access Journals (Sweden)

    Paulo Shakarian

    Full Text Available We study the behavior of pathogens on host protein networks for humans and Arabidopsis - noting striking similarities. Specifically, we preform [Formula: see text]-shell decomposition analysis on these networks - which groups the proteins into various "shells" based on network structure. We observe that shells with a higher average degree are more highly targeted (with a power-law relationship and that highly targeted nodes lie in shells closer to the inner-core of the network. Additionally, we also note that the inner core of the network is significantly under-targeted. We show that these core proteins may have a role in intra-cellular communication and hypothesize that they are less attacked to ensure survival of the host. This may explain why certain high-degree proteins are not significantly attacked.

  19. Exploring hierarchical and overlapping modular structure in the yeast protein interaction network

    Directory of Open Access Journals (Sweden)

    Zhao Yi

    2010-12-01

    Full Text Available Abstract Background Developing effective strategies to reveal modular structures in protein interaction networks is crucial for better understanding of molecular mechanisms of underlying biological processes. In this paper, we propose a new density-based algorithm (ADHOC for clustering vertices of a protein interaction network using a novel subgraph density measurement. Results By statistically evaluating several independent criteria, we found that ADHOC could significantly improve the outcome as compared with five previously reported density-dependent methods. We further applied ADHOC to investigate the hierarchical and overlapping modular structure in the yeast PPI network. Our method could effectively detect both protein modules and the overlaps between them, and thus greatly promote the precise prediction of protein functions. Moreover, by further assaying the intermodule layer of the yeast PPI network, we classified hubs into two types, module hubs and inter-module hubs. Each type presents distinct characteristics both in network topology and biological functions, which could conduce to the better understanding of relationship between network architecture and biological implications. Conclusions Our proposed algorithm based on the novel subgraph density measurement makes it possible to more precisely detect hierarchical and overlapping modular structures in protein interaction networks. In addition, our method also shows a strong robustness against the noise in network, which is quite critical for analyzing such a high noise network.

  20. The organisational structure of protein networks: revisiting the centrality-lethality hypothesis.

    Science.gov (United States)

    Raman, Karthik; Damaraju, Nandita; Joshi, Govind Krishna

    2014-03-01

    Protein networks, describing physical interactions as well as functional associations between proteins, have been unravelled for many organisms in the recent past. Databases such as the STRING provide excellent resources for the analysis of such networks. In this contribution, we revisit the organisation of protein networks, particularly the centrality-lethality hypothesis, which hypothesises that nodes with higher centrality in a network are more likely to produce lethal phenotypes on removal, compared to nodes with lower centrality. We consider the protein networks of a diverse set of 20 organisms, with essentiality information available in the Database of Essential Genes and assess the relationship between centrality measures and lethality. For each of these organisms, we obtained networks of high-confidence interactions from the STRING database, and computed network parameters such as degree, betweenness centrality, closeness centrality and pairwise disconnectivity indices. We observe that the networks considered here are predominantly disassortative. Further, we observe that essential nodes in a network have a significantly higher average degree and betweenness centrality, compared to the network average. Most previous studies have evaluated the centrality-lethality hypothesis for Saccharomyces cerevisiae and Escherichia coli; we here observe that the centrality-lethality hypothesis hold goods for a large number of organisms, with certain limitations. Betweenness centrality may also be a useful measure to identify essential nodes, but measures like closeness centrality and pairwise disconnectivity are not significantly higher for essential nodes.

  1. PADPIN: protein-protein interaction networks of angiogenesis, arteriogenesis, and inflammation in peripheral arterial disease

    Science.gov (United States)

    Vijay, Chaitanya G.; Annex, Brian H.; Bader, Joel S.; Popel, Aleksander S.

    2015-01-01

    Peripheral arterial disease (PAD) results from an obstruction of blood flow in the arteries other than the heart, most commonly the arteries that supply the legs. The complexity of the known signaling pathways involved in PAD, including various growth factor pathways and their cross talks, suggests that analyses of high-throughput experimental data could lead to a new level of understanding of the disease as well as novel and heretofore unanticipated potential targets. Such bioinformatic analyses have not been systematically performed for PAD. We constructed global protein-protein interaction networks of angiogenesis (Angiome), immune response (Immunome), and arteriogenesis (Arteriome) using our previously developed algorithm GeneHits. The term “PADPIN” refers to the angiome, immunome, and arteriome in PAD. Here we analyze four microarray gene expression datasets from ischemic and nonischemic gastrocnemius muscles at day 3 posthindlimb ischemia (HLI) in two genetically different C57BL/6 and BALB/c mouse strains that display differential susceptibility to HLI to identify potential targets and signaling pathways in angiogenesis, immune, and arteriogenesis networks. We hypothesize that identification of the differentially expressed genes in ischemic and nonischemic muscles between the strains that recovers better (C57BL/6) vs. the strain that recovers more poorly (BALB/c) will help for the prediction of target genes in PAD. Our bioinformatics analysis identified several genes that are differentially expressed between the two mouse strains with known functions in PAD including TLR4, THBS1, and PRKAA2 and several genes with unknown functions in PAD including EphA4, TSPAN7, SLC22A4, and EIF2a. PMID:26058837

  2. Automatic extraction of gene ontology annotation and its correlation with clusters in protein networks

    Directory of Open Access Journals (Sweden)

    Mazo Ilya

    2007-07-01

    Full Text Available Abstract Background Uncovering cellular roles of a protein is a task of tremendous importance and complexity that requires dedicated experimental work as well as often sophisticated data mining and processing tools. Protein functions, often referred to as its annotations, are believed to manifest themselves through topology of the networks of inter-proteins interactions. In particular, there is a growing body of evidence that proteins performing the same function are more likely to interact with each other than with proteins with other functions. However, since functional annotation and protein network topology are often studied separately, the direct relationship between them has not been comprehensively demonstrated. In addition to having the general biological significance, such demonstration would further validate the data extraction and processing methods used to compose protein annotation and protein-protein interactions datasets. Results We developed a method for automatic extraction of protein functional annotation from scientific text based on the Natural Language Processing (NLP technology. For the protein annotation extracted from the entire PubMed, we evaluated the precision and recall rates, and compared the performance of the automatic extraction technology to that of manual curation used in public Gene Ontology (GO annotation. In the second part of our presentation, we reported a large-scale investigation into the correspondence between communities in the literature-based protein networks and GO annotation groups of functionally related proteins. We found a comprehensive two-way match: proteins within biological annotation groups form significantly denser linked network clusters than expected by chance and, conversely, densely linked network communities exhibit a pronounced non-random overlap with GO groups. We also expanded the publicly available GO biological process annotation using the relations extracted by our NLP technology

  3. Discovering overlapped protein complexes from weighted PPI networks by removing inter-module hubs.

    Science.gov (United States)

    Maddi, A M A; Eslahchi, Ch

    2017-06-12

    Detecting known protein complexes and predicting undiscovered protein complexes from protein-protein interaction (PPI) networks help us to understand principles of cell organization and its functions. Nevertheless, the discovery of protein complexes based on experiment still needs to be explored. Therefore, computational methods are useful approaches to overcome the experimental limitations. Nevertheless, extraction of protein complexes from PPI network is often nontrivial. Two major constraints are large amount of noise and ignorance of occurrence time of different interactions in PPI network. In this paper, an efficient algorithm, Inter Module Hub Removal Clustering (IMHRC), is developed based on inter-module hub removal in the weighted PPI network which can detect overlapped complexes. By removing some of the inter-module hubs and module hubs, IMHRC eliminates high amount of noise in dataset and implicitly considers different occurrence time of the PPI in network. The performance of the IMHRC was evaluated on several benchmark datasets and results were compared with some of the state-of-the-art models. The protein complexes discovered with the IMHRC method show significantly better agreement with the real complexes than other current methods. Our algorithm provides an accurate and scalable method for detecting and predicting protein complexes from PPI networks.

  4. Study on the isothermal forging process of MB26 magnesium alloy adaptor

    Directory of Open Access Journals (Sweden)

    Xu Wenchen

    2015-01-01

    Full Text Available The isothermal forging process is an effective method to manufacture complex-shaped components of hard-to-work materials, such as magnesium alloys. This study investigates the isothermal forging process of an MB26 magnesium alloy adaptor with three branches. The results show that two-step forging process is appropriate to form the adaptor forging, which not only improves the filling quality but also reduces the forging load compared with one-step forging process. Moreover, the flow line is distributed along the contour of the complex-shaped adaptor forging.

  5. Creating a specialist protein resource network: a meeting report for the protein bioinformatics and community resources retreat.

    Science.gov (United States)

    Babbitt, Patricia C; Bagos, Pantelis G; Bairoch, Amos; Bateman, Alex; Chatonnet, Arnaud; Chen, Mark Jinan; Craik, David J; Finn, Robert D; Gloriam, David; Haft, Daniel H; Henrissat, Bernard; Holliday, Gemma L; Isberg, Vignir; Kaas, Quentin; Landsman, David; Lenfant, Nicolas; Manning, Gerard; Nagano, Nozomi; Srinivasan, Narayanaswamy; O'Donovan, Claire; Pruitt, Kim D; Sowdhamini, Ramanathan; Rawlings, Neil D; Saier, Milton H; Sharman, Joanna L; Spedding, Michael; Tsirigos, Konstantinos D; Vastermark, Ake; Vriend, Gerrit

    2015-01-01

    During 11-12 August 2014, a Protein Bioinformatics and Community Resources Retreat was held at the Wellcome Trust Genome Campus in Hinxton, UK. This meeting brought together the principal investigators of several specialized protein resources (such as CAZy, TCDB and MEROPS) as well as those from protein databases from the large Bioinformatics centres (including UniProt and RefSeq). The retreat was divided into five sessions: (1) key challenges, (2) the databases represented, (3) best practices for maintenance and curation, (4) information flow to and from large data centers and (5) communication and funding. An important outcome of this meeting was the creation of a Specialist Protein Resource Network that we believe will improve coordination of the activities of its member resources. We invite further protein database resources to join the network and continue the dialogue.

  6. Landscape mapping of functional proteins in insulin signal transduction and insulin resistance: a network-based protein-protein interaction analysis.

    Directory of Open Access Journals (Sweden)

    Chiranjib Chakraborty

    Full Text Available The type 2 diabetes has increased rapidly in recent years throughout the world. The insulin signal transduction mechanism gets disrupted sometimes and it's known as insulin-resistance. It is one of the primary causes associated with type-2 diabetes. The signaling mechanisms involved several proteins that include 7 major functional proteins such as INS, INSR, IRS1, IRS2, PIK3CA, Akt2, and GLUT4. Using these 7 principal proteins, multiple sequences alignment has been created. The scores between sequences also have been developed. We have constructed a phylogenetic tree and modified it with node and distance. Besides, we have generated sequence logos and ultimately developed the protein-protein interaction network. The small insulin signal transduction protein arrangement shows complex network between the functional proteins.

  7. Semantic integration to identify overlapping functional modules in protein interaction networks

    Directory of Open Access Journals (Sweden)

    Ramanathan Murali

    2007-07-01

    Full Text Available Abstract Background The systematic analysis of protein-protein interactions can enable a better understanding of cellular organization, processes and functions. Functional modules can be identified from the protein interaction networks derived from experimental data sets. However, these analyses are challenging because of the presence of unreliable interactions and the complex connectivity of the network. The integration of protein-protein interactions with the data from other sources can be leveraged for improving the effectiveness of functional module detection algorithms. Results We have developed novel metrics, called semantic similarity and semantic interactivity, which use Gene Ontology (GO annotations to measure the reliability of protein-protein interactions. The protein interaction networks can be converted into a weighted graph representation by assigning the reliability values to each interaction as a weight. We presented a flow-based modularization algorithm to efficiently identify overlapping modules in the weighted interaction networks. The experimental results show that the semantic similarity and semantic interactivity of interacting pairs were positively correlated with functional co-occurrence. The effectiveness of the algorithm for identifying modules was evaluated using functional categories from the MIPS database. We demonstrated that our algorithm had higher accuracy compared to other competing approaches. Conclusion The integration of protein interaction networks with GO annotation data and the capability of detecting overlapping modules substantially improve the accuracy of module identification.

  8. Basolateral sorting of the coxsackie and adenovirus receptor through interaction of a canonical YXXPhi motif with the clathrin adaptors AP-1A and AP-1B.

    Science.gov (United States)

    Carvajal-Gonzalez, Jose Maria; Gravotta, Diego; Mattera, Rafael; Diaz, Fernando; Perez Bay, Andres; Roman, Angel C; Schreiner, Ryan P; Thuenauer, Roland; Bonifacino, Juan S; Rodriguez-Boulan, Enrique

    2012-03-06

    The coxsackie and adenovirus receptor (CAR) plays key roles in epithelial barrier function at the tight junction, a localization guided in part by a tyrosine-based basolateral sorting signal, (318)YNQV(321). Sorting motifs of this type are known to route surface receptors into clathrin-mediated endocytosis through interaction with the medium subunit (μ2) of the clathrin adaptor AP-2, but how they guide new and recycling membrane proteins basolaterally is unknown. Here, we show that YNQV functions as a canonical YxxΦ motif, with both Y318 and V321 required for the correct basolateral localization and biosynthetic sorting of CAR, and for interaction with a highly conserved pocket in the medium subunits (μ1A and μ1B) of the clathrin adaptors AP-1A and AP-1B. Knock-down experiments demonstrate that AP-1A plays a role in the biosynthetic sorting of CAR, complementary to the role of AP-1B in basolateral recycling of this receptor. Our study illustrates how two clathrin adaptors direct basolateral trafficking of a plasma membrane protein through interaction with a canonical YxxΦ motif.

  9. The adaptor molecule SAP plays essential roles during invariant NKT cell cytotoxicity and lytic synapse formation.

    Science.gov (United States)

    Das, Rupali; Bassiri, Hamid; Guan, Peng; Wiener, Susan; Banerjee, Pinaki P; Zhong, Ming-Chao; Veillette, André; Orange, Jordan S; Nichols, Kim E

    2013-04-25

    The adaptor molecule signaling lymphocytic activation molecule-associated protein (SAP) plays critical roles during invariant natural killer T (iNKT) cell ontogeny. As a result, SAP-deficient humans and mice lack iNKT cells. The strict developmental requirement for SAP has made it difficult to discern its possible involvement in mature iNKT cell functions. By using temporal Cre recombinase-mediated gene deletion to ablate SAP expression after completion of iNKT cell development, we demonstrate that SAP is essential for T-cell receptor (TCR)-induced iNKT cell cytotoxicity against T-cell and B-cell leukemia targets in vitro and iNKT-cell-mediated control of T-cell leukemia growth in vivo. These findings are not restricted to the murine system: silencing RNA-mediated suppression of SAP expression in human iNKT cells also significantly impairs TCR-induced cytolysis. Mechanistic studies reveal that iNKT cell killing requires the tyrosine kinase Fyn, a known SAP-binding protein. Furthermore, SAP expression is required within iNKT cells to facilitate their interaction with T-cell targets and induce reorientation of the microtubule-organizing center to the immunologic synapse (IS). Collectively, these studies highlight a novel and essential role for SAP during iNKT cell cytotoxicity and formation of a functional IS.

  10. Novel insights through the integration of structural and functional genomics data with protein networks.

    Science.gov (United States)

    Clarke, Declan; Bhardwaj, Nitin; Gerstein, Mark B

    2012-09-01

    In recent years, major advances in genomics, proteomics, macromolecular structure determination, and the computational resources capable of processing and disseminating the large volumes of data generated by each have played major roles in advancing a more systems-oriented appreciation of biological organization. One product of systems biology has been the delineation of graph models for describing genome-wide protein-protein interaction networks. The network organization and topology which emerges in such models may be used to address fundamental questions in an array of cellular processes, as well as biological features intrinsic to the constituent proteins (or "nodes") themselves. However, graph models alone constitute an abstraction which neglects the underlying biological and physical reality that the network's nodes and edges are highly heterogeneous entities. Here, we explore some of the advantages of introducing a protein structural dimension to such models, as the marriage of conventional network representations with macromolecular structural data helps to place static node and edge constructs in a biologically more meaningful context. We emphasize that 3D protein structures constitute a valuable conceptual and predictive framework by discussing examples of the insights provided, such as enabling in silico predictions of protein-protein interactions, providing rational and compelling classification schemes for network elements, as well as revealing interesting intrinsic differences between distinct node types, such as disorder and evolutionary features, which may then be rationalized in light of their respective functions within networks. Copyright © 2012 Elsevier Inc. All rights reserved.

  11. Protein Secondary Structure Prediction Using AutoEncoder Network and Bayes Classifier

    Science.gov (United States)

    Wang, Leilei; Cheng, Jinyong

    2018-03-01

    Protein secondary structure prediction is belong to bioinformatics,and it's important in research area. In this paper, we propose a new prediction way of protein using bayes classifier and autoEncoder network. Our experiments show some algorithms including the construction of the model, the classification of parameters and so on. The data set is a typical CB513 data set for protein. In terms of accuracy, the method is the cross validation based on the 3-fold. Then we can get the Q3 accuracy. Paper results illustrate that the autoencoder network improved the prediction accuracy of protein secondary structure.

  12. Protein-lipid interactions: from membrane domains to cellular networks

    National Research Council Canada - National Science Library

    Tamm, Lukas K

    2005-01-01

    ... membranes is the lipid bilayer. Embedded in the fluid lipid bilayer are proteins of various shapes and traits. This volume illuminates from physical, chemical and biological angles the numerous - mostly quite weak - interactions between lipids, proteins, and proteins and lipids that define the delicate, highly dynamic and yet so stable fabri...

  13. A Web server for predicting proteins involved in pluripotent network

    Indian Academy of Sciences (India)

    2016-11-04

    Nov 4, 2016 ... the self-renewal property. PluriPred predicts whether a protein is involved in pluripotency from primary protein sequence using manually curated pluripotent proteins as training datasets. Machine learning techniques (MLTs) such as Support Vector Machine (SVM), Naïve Base (NB), Random Forest (RF), ...

  14. msiDBN: A Method of Identifying Critical Proteins in Dynamic PPI Networks

    Directory of Open Access Journals (Sweden)

    Yuan Zhang

    2014-01-01

    Full Text Available Dynamics of protein-protein interactions (PPIs reveals the recondite principles of biological processes inside a cell. Shown in a wealth of study, just a small group of proteins, rather than the majority, play more essential roles at crucial points of biological processes. This present work focuses on identifying these critical proteins exhibiting dramatic structural changes in dynamic PPI networks. First, a comprehensive way of modeling the dynamic PPIs is presented which simultaneously analyzes the activity of proteins and assembles the dynamic coregulation correlation between proteins at each time point. Second, a novel method is proposed, named msiDBN, which models a common representation of multiple PPI networks using a deep belief network framework and analyzes the reconstruction errors and the variabilities across the time courses in the biological process. Experiments were implemented on data of yeast cell cycles. We evaluated our network construction method by comparing the functional representations of the derived networks with two other traditional construction methods. The ranking results of critical proteins in msiDBN were compared with the results from the baseline methods. The results of comparison showed that msiDBN had better reconstruction rate and identified more proteins of critical value to yeast cell cycle process.

  15. A Type-2 fuzzy data fusion approach for building reliable weighted protein interaction networks with application in protein complex detection.

    Science.gov (United States)

    Mehranfar, Adele; Ghadiri, Nasser; Kouhsar, Morteza; Golshani, Ashkan

    2017-09-01

    Detecting the protein complexes is an important task in analyzing the protein interaction networks. Although many algorithms predict protein complexes in different ways, surveys on the interaction networks indicate that about 50% of detected interactions are false positives. Consequently, the accuracy of existing methods needs to be improved. In this paper we propose a novel algorithm to detect the protein complexes in 'noisy' protein interaction data. First, we integrate several biological data sources to determine the reliability of each interaction and determine more accurate weights for the interactions. A data fusion component is used for this step, based on the interval type-2 fuzzy voter that provides an efficient combination of the information sources. This fusion component detects the errors and diminishes their effect on the detection protein complexes. So in the first step, the reliability scores have been assigned for every interaction in the network. In the second step, we have proposed a general protein complex detection algorithm by exploiting and adopting the strong points of other algorithms and existing hypotheses regarding real complexes. Finally, the proposed method has been applied for the yeast interaction datasets for predicting the interactions. The results show that our framework has a better performance regarding precision and F-measure than the existing approaches. Copyright © 2017 Elsevier Ltd. All rights reserved.

  16. Prediction of protein hydration sites from sequence by modular neural networks

    DEFF Research Database (Denmark)

    Ehrlich, L.; Reczko, M.; Bohr, Henrik

    1998-01-01

    The hydration properties of a protein are important determinants of its structure and function. Here, modular neural networks are employed to predict ordered hydration sites using protein sequence information. First, secondary structure and solvent accessibility are predicted from sequence with two...... separate neural networks. These predictions are used as input together with protein sequences for networks predicting hydration of residues, backbone atoms and sidechains. These networks are teined with protein crystal structures. The prediction of hydration is improved by adding information on secondary...... structure and solvent accessibility and, using actual values of these properties, redidue hydration can be predicted to 77% accuracy with a Metthews coefficient of 0.43. However, predicted property data with an accuracy of 60-70% result in less than half the improvement in predictive performance observed...

  17. Defining the protein interaction network of human malaria parasite Plasmodium falciparum

    KAUST Repository

    Ramaprasad, Abhinay

    2012-02-01

    Malaria, caused by the protozoan parasite Plasmodium falciparum, affects around 225. million people yearly and a huge international effort is directed towards combating this grave threat to world health and economic development. Considerable advances have been made in malaria research triggered by the sequencing of its genome in 2002, followed by several high-throughput studies defining the malaria transcriptome and proteome. A protein-protein interaction (PPI) network seeks to trace the dynamic interactions between proteins, thereby elucidating their local and global functional relationships. Experimentally derived PPI network from high-throughput methods such as yeast two hybrid (Y2H) screens are inherently noisy, but combining these independent datasets by computational methods tends to give a greater accuracy and coverage. This review aims to discuss the computational approaches used till date to construct a malaria protein interaction network and to catalog the functional predictions and biological inferences made from analysis of the PPI network. © 2011 Elsevier Inc.

  18. Topology and weights in a protein domain interaction network – a novel way to predict protein interactions

    Directory of Open Access Journals (Sweden)

    Wuchty Stefan

    2006-05-01

    Full Text Available Abstract Background While the analysis of unweighted biological webs as diverse as genetic, protein and metabolic networks allowed spectacular insights in the inner workings of a cell, biological networks are not only determined by their static grid of links. In fact, we expect that the heterogeneity in the utilization of connections has a major impact on the organization of cellular activities as well. Results We consider a web of interactions between protein domains of the Protein Family database (PFAM, which are weighted by a probability score. We apply metrics that combine the static layout and the weights of the underlying interactions. We observe that unweighted measures as well as their weighted counterparts largely share the same trends in the underlying domain interaction network. However, we only find weak signals that weights and the static grid of interactions are connected entities. Therefore assuming that a protein interaction is governed by a single domain interaction, we observe strong and significant correlations of the highest scoring domain interaction and the confidence of protein interactions in the underlying interactions of yeast and fly. Modeling an interaction between proteins if we find a high scoring protein domain interaction we obtain 1, 428 protein interactions among 361 proteins in the human malaria parasite Plasmodium falciparum. Assessing their quality by a logistic regression method we observe that increasing confidence of predicted interactions is accompanied by high scoring domain interactions and elevated levels of functional similarity and evolutionary conservation. Conclusion Our results indicate that probability scores are randomly distributed, allowing to treat static grid and weights of domain interactions as separate entities. In particular, these finding confirms earlier observations that a protein interaction is a matter of a single interaction event on domain level. As an immediate application, we

  19. Sub-cellular distribution of UNC-104(KIF1A) upon binding to adaptors as UNC-16(JIP3), DNC-1(DCTN1/Glued) and SYD-2(Liprin-α) in C. elegans neurons.

    Science.gov (United States)

    Hsu, C-C; Moncaleano, J D; Wagner, O I

    2011-03-10

    The accumulation of cargo (tau, amyloid precursor protein, neurofilaments etc.) in neurons is a hallmark of various neurodegenerative diseases while we have only little knowledge how axonal transport is regulated. Kinesin-3 UNC-104(KIF1A) is the major transporter of synaptic vesicles and recent reports suggest that a cargo itself can affect the motor's activity. Inspecting an interactome map, we identify three putative UNC-104 interactors, namely UNC-16(JIP3), DNC-1(DCTN1/Glued) and SYD-2(Liprin-α), known to be adaptors in essential neuronal protein complexes. We then employed the novel method bimolecular fluorescence complementation (BiFC) assay to visualize motor-adaptor complexes in the nervous system of living C. elegans. Interestingly, the binding of UNC-104 to each adaptor protein results in different sub-cellular distributions and has distinctive effects on the motor's motility. Specifically, if UNC-104 bound to UNC-16, the motor is primarily localized in the soma of neurons while bound to DNC-1, the motor is basically found in axonal termini. On the other hand, if UNC-104 is bound to SYD-2 we identify motor populations mostly along axons. Therefore, these three adaptors inherit different functions in steering the motor to specific sub-cellular locations in the neuron. Copyright © 2011 IBRO. Published by Elsevier Ltd. All rights reserved.

  20. Emergence of Complexity in Protein Functions and Metabolic Networks

    Science.gov (United States)

    Pohorille, Andzej

    2009-01-01

    In modern organisms proteins perform a majority of cellular functions, such as chemical catalysis, energy transduction and transport of material across cell walls. Although great strides have been made towards understanding protein evolution, a meaningful extrapolation from contemporary proteins to their earliest ancestors is virtually impossible. In an alternative approach, the origin of water-soluble proteins was probed through the synthesis of very large libraries of random amino acid sequences and subsequently subjecting them to in vitro evolution. In combination with computer modeling and simulations, these experiments allow us to address a number of fundamental questions about the origins of proteins. Can functionality emerge from random sequences of proteins? How did the initial repertoire of functional proteins diversify to facilitate new functions? Did this diversification proceed primarily through drawing novel functionalities from random sequences or through evolution of already existing proto-enzymes? Did protein evolution start from a pool of proteins defined by a frozen accident and other collections of proteins could start a different evolutionary pathway? Although we do not have definitive answers to these questions, important clues have been uncovered. Considerable progress has been also achieved in understanding the origins of membrane proteins. We will address this issue in the example of ion channels - proteins that mediate transport of ions across cell walls. Remarkably, despite overall complexity of these proteins in contemporary cells, their structural motifs are quite simple, with -helices being most common. By combining results of experimental and computer simulation studies on synthetic models and simple, natural channels, I will show that, even though architectures of membrane proteins are not nearly as diverse as those of water-soluble proteins, they are sufficiently flexible to adapt readily to the functional demands arising during

  1. Topological, functional, and dynamic properties of the protein interaction networks rewired by benzo(a)pyrene

    Energy Technology Data Exchange (ETDEWEB)

    Ba, Qian [Key Laboratory of Food Safety Research, Institute for Nutritional Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai (China); Key Laboratory of Food Safety Risk Assessment, Ministry of Health, Beijing (China); Li, Junyang; Huang, Chao [Key Laboratory of Food Safety Research, Institute for Nutritional Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai (China); Li, Jingquan; Chu, Ruiai [Key Laboratory of Food Safety Research, Institute for Nutritional Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai (China); Key Laboratory of Food Safety Risk Assessment, Ministry of Health, Beijing (China); Wu, Yongning, E-mail: wuyongning@cfsa.net.cn [Key Laboratory of Food Safety Risk Assessment, Ministry of Health, Beijing (China); Wang, Hui, E-mail: huiwang@sibs.ac.cn [Key Laboratory of Food Safety Research, Institute for Nutritional Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai (China); Key Laboratory of Food Safety Risk Assessment, Ministry of Health, Beijing (China); School of Life Science and Technology, ShanghaiTech University, Shanghai (China)

    2015-03-01

    Benzo(a)pyrene is a common environmental and foodborne pollutant that has been identified as a human carcinogen. Although the carcinogenicity of benzo(a)pyrene has been extensively reported, its precise molecular mechanisms and the influence on system-level protein networks are not well understood. To investigate the system-level influence of benzo(a)pyrene on protein interactions and regulatory networks, a benzo(a)pyrene-rewired protein interaction network was constructed based on 769 key proteins derived from more than 500 literature reports. The protein interaction network rewired by benzo(a)pyrene was a scale-free, highly-connected biological system. Ten modules were identified, and 25 signaling pathways were enriched, most of which belong to the human diseases category, especially cancer and infectious disease. In addition, two lung-specific and two liver-specific pathways were identified. Three pathways were specific in short and medium-term networks (< 48 h), and five pathways were enriched only in the medium-term network (6 h–48 h). Finally, the expression of linker genes in the network was validated by Western blotting. These findings establish the overall, tissue- and time-specific benzo(a)pyrene-rewired protein interaction networks and provide insights into the biological effects and molecular mechanisms of action of benzo(a)pyrene. - Highlights: • Benzo(a)pyrene induced scale-free, highly-connected protein interaction networks. • 25 signaling pathways were enriched through modular analysis. • Tissue- and time-specific pathways were identified.

  2. Protein-Protein Interaction Article Classification Using a Convolutional Recurrent Neural Network with Pre-trained Word Embeddings.

    Science.gov (United States)

    Matos, Sérgio; Antunes, Rui

    2017-12-13

    Curation of protein interactions from scientific articles is an important task, since interaction networks are essential for the understanding of biological processes associated with disease or pharmacological action for example. However, the increase in the number of publications that potentially contain relevant information turns this into a very challenging and expensive task. In this work we used a convolutional recurrent neural network for identifying relevant articles for extracting information regarding protein interactions. Using the BioCreative III Article Classification Task dataset, we achieved an area under the precision-recall curve of 0.715 and a Matthew's correlation coefficient of 0.600, which represents an improvement over previous works.

  3. A graph modification approach for finding core-periphery structures in protein interaction networks.

    Science.gov (United States)

    Bruckner, Sharon; Hüffner, Falk; Komusiewicz, Christian

    2015-01-01

    The core-periphery model for protein interaction (PPI) networks assumes that protein complexes in these networks consist of a dense core and a possibly sparse periphery that is adjacent to vertices in the core of the complex. In this work, we aim at uncovering a global core-periphery structure for a given PPI network. We propose two exact graph-theoretic formulations for this task, which aim to fit the input network to a hypothetical ground truth network by a minimum number of edge modifications. In one model each cluster has its own periphery, and in the other the periphery is shared. We first analyze both models from a theoretical point of view, showing their NP-hardness. Then, we devise efficient exact and heuristic algorithms for both models and finally perform an evaluation on subnetworks of the S. cerevisiae PPI network.

  4. Structure and evolution of protein interaction networks: a statistical model for link dynamics and gene duplications

    Directory of Open Access Journals (Sweden)

    Wagner Andreas

    2004-11-01

    Full Text Available Abstract Background The structure of molecular networks derives from dynamical processes on evolutionary time scales. For protein interaction networks, global statistical features of their structure can now be inferred consistently from several large-throughput datasets. Understanding the underlying evolutionary dynamics is crucial for discerning random parts of the network from biologically important properties shaped by natural selection. Results We present a detailed statistical analysis of the protein interactions in Saccharomyces cerevisiae based on several large-throughput datasets. Protein pairs resulting from gene duplications are used as tracers into the evolutionary past of the network. From this analysis, we infer rate estimates for two key evolutionary processes shaping the network: (i gene duplications and (ii gain and loss of interactions through mutations in existing proteins, which are referred to as link dynamics. Importantly, the link dynamics is asymmetric, i.e., the evolutionary steps are mutations in just one of the binding parters. The link turnover is shown to be much faster than gene duplications. Both processes are assembled into an empirically grounded, quantitative model for the evolution of protein interaction networks. Conclusions According to this model, the link dynamics is the dominant evolutionary force shaping the statistical structure of the network, while the slower gene duplication dynamics mainly affects its size. Specifically, the model predicts (i a broad distribution of the connectivities (i.e., the number of binding partners of a protein and (ii correlations between the connectivities of interacting proteins, a specific consequence of the asymmetry of the link dynamics. Both features have been observed in the protein interaction network of S. cerevisiae.

  5. Neuronal adaptor FE65 stimulates Rac1-mediated neurite outgrowth by recruiting and activating ELMO1.

    Science.gov (United States)

    Li, Wen; Tam, Ka Ming Vincent; Chan, Wai Wan Ray; Koon, Alex Chun; Ngo, Jacky Chi Ki; Chan, Ho Yin Edwin; Lau, Kwok-Fai

    2018-04-03

    Neurite outgrowth is a crucial process in developing neurons for neural network formation. Understanding the regulatory mechanisms of neurite outgrowth is essential for developing strategies to stimulate neurite regeneration after nerve injury and in neurodegenerative disorders. FE65 is a brain-enriched adaptor that stimulates Rac1-mediated neurite elongation. However, the precise mechanism by which FE65 promotes the process remains elusive. Here, we show that ELMO1, a subunit of ELMO1-DOCK180 bipartite Rac1 GEF, interacts with the FE65 N-terminal region. Overexpression of FE65 and/or ELMO1 enhances whereas knockdown of FE65 or ELMO1 inhibits neurite outgrowth and Rac1 activation. The effect of FE65 alone or together with ELMO1 is attenuated by an FE65 double mutation that disrupts FE65-ELMO1 interaction. Notably, FE65 is found to activate ELMO1 by diminishing ELMO1 intramolecular autoinhibitory interaction and to promote the targeting of ELMO1 to the plasma membrane where Rac1 is activated. We also show that FE65, ELMO1 and DOCK180 form a tripartite complex. Knockdown of DOCK180 reduces the stimulatory effect of FE65-ELMO1 on Rac1 activation and neurite outgrowth. Thus, we identify a novel mechanism that FE65 stimulates Rac1-mediated neurite outgrowth by recruiting and activating of ELMO1. Published under license by The American Society for Biochemistry and Molecular Biology, Inc.

  6. Prioritizing Disease Candidate Proteins in Cardiomyopathy-Specific Protein-Protein Interaction Networks Based on “Guilt by Association” Analysis

    Science.gov (United States)

    He, Weiming; Li, Weiguo; Qu, Xiaoli; Liang, Binhua; Gao, Qianping; Feng, Chenchen; Jia, Xu; Lv, Yana; Zhang, Siya; Li, Xia

    2013-01-01

    The cardiomyopathies are a group of heart muscle diseases which can be inherited (familial). Identifying potential disease-related proteins is important to understand mechanisms of cardiomyopathies. Experimental identification of cardiomyophthies is costly and labour-intensive. In contrast, bioinformatics approach has a competitive advantage over experimental method. Based on “guilt by association” analysis, we prioritized candidate proteins involving in human cardiomyopathies. We first built weighted human cardiomyopathy-specific protein-protein interaction networks for three subtypes of cardiomyopathies using the known disease proteins from Online Mendelian Inheritance in Man as seeds. We then developed a method in prioritizing disease candidate proteins to rank candidate proteins in the network based on “guilt by association” analysis. It was found that most candidate proteins with high scores shared disease-related pathways with disease seed proteins. These top ranked candidate proteins were related with the corresponding disease subtypes, and were potential disease-related proteins. Cross-validation and comparison with other methods indicated that our approach could be used for the identification of potentially novel disease proteins, which may provide insights into cardiomyopathy-related mechanisms in a more comprehensive and integrated way. PMID:23940716

  7. Analysis of hepatocellular carcinoma and metastatic hepatic carcinoma via functional modules in a protein-protein interaction network

    Directory of Open Access Journals (Sweden)

    Jun Pan

    2014-01-01

    Full Text Available Introduction: This study aims to identify protein clusters with potential functional relevance in the pathogenesis of hepatocellular carcinoma (HCC and metastatic hepatic carcinoma using network analysis. Materials and Methods: We used human protein interaction data to build a protein-protein interaction network with Cytoscape and then derived functional clusters using MCODE. Combining the gene expression profiles, we calculated the functional scores for the clusters and selected statistically significant clusters. Meanwhile, Gene Ontology was used to assess the functionality of these clusters. Finally, a support vector machine was trained on the gold standard data sets. Results: The differentially expressed genes of HCC were mainly involved in metabolic and signaling processes. We acquired 13 significant modules from the gene expression profiles. The area under the curve value based on the differentially expressed modules were 98.31%, which outweighed the classification with DEGs. Conclusions: Differentially expressed modules are valuable to screen biomarkers combined with functional modules.

  8. Scale-space measures for graph topology link protein network architecture to function

    NARCIS (Netherlands)

    Hulsman, M.; Dimitrakopoulos, C.; De Ridder, J.

    2014-01-01

    MOTIVATION: The network architecture of physical protein interactions is an important determinant for the molecular functions that are carried out within each cell. To study this relation, the network architecture can be characterized by graph topological characteristics such as shortest paths and

  9. Scale-space measures for graph topology link protein network architecture to function.

    Science.gov (United States)

    Hulsman, Marc; Dimitrakopoulos, Christos; de Ridder, Jeroen

    2014-06-15

    The network architecture of physical protein interactions is an important determinant for the molecular functions that are carried out within each cell. To study this relation, the network architecture can be characterized by graph topological characteristics such as shortest paths and network hubs. These characteristics have an important shortcoming: they do not take into account that interactions occur across different scales. This is important because some cellular functions may involve a single direct protein interaction (small scale), whereas others require more and/or indirect interactions, such as protein complexes (medium scale) and interactions between large modules of proteins (large scale). In this work, we derive generalized scale-aware versions of known graph topological measures based on diffusion kernels. We apply these to characterize the topology of networks across all scales simultaneously, generating a so-called graph topological scale-space. The comprehensive physical interaction network in yeast is used to show that scale-space based measures consistently give superior performance when distinguishing protein functional categories and three major types of functional interactions-genetic interaction, co-expression and perturbation interactions. Moreover, we demonstrate that graph topological scale spaces capture biologically meaningful features that provide new insights into the link between function and protein network architecture. Matlab(TM) code to calculate the scale-aware topological measures (STMs) is available at http://bioinformatics.tudelft.nl/TSSA © The Author 2014. Published by Oxford University Press.

  10. Efficient identification of critical residues based only on protein structure by network analysis.

    Directory of Open Access Journals (Sweden)

    Michael P Cusack

    2007-05-01

    Full Text Available Despite the increasing number of published protein structures, and the fact that each protein's function relies on its three-dimensional structure, there is limited access to automatic programs used for the identification of critical residues from the protein structure, compared with those based on protein sequence. Here we present a new algorithm based on network analysis applied exclusively on protein structures to identify critical residues. Our results show that this method identifies critical residues for protein function with high reliability and improves automatic sequence-based approaches and previous network-based approaches. The reliability of the method depends on the conformational diversity screened for the protein of interest. We have designed a web site to give access to this software at http://bis.ifc.unam.mx/jamming/. In summary, a new method is presented that relates critical residues for protein function with the most traversed residues in networks derived from protein structures. A unique feature of the method is the inclusion of the conformational diversity of proteins in the prediction, thus reproducing a basic feature of the structure/function relationship of proteins.

  11. Protein Network Signatures Associated with Exogenous Biofuels Treatments in Cyanobacterium Synechocystis sp. PCC 6803.

    Science.gov (United States)

    Pei, Guangsheng; Chen, Lei; Wang, Jiangxin; Qiao, Jianjun; Zhang, Weiwen

    2014-01-01

    Although recognized as a promising microbial cell factory for producing biofuels, current productivity in cyanobacterial systems is low. To make the processes economically feasible, one of the hurdles, which need to be overcome is the low tolerance of hosts to toxic biofuels. Meanwhile, little information is available regarding the cellular responses to biofuels stress in cyanobacteria, which makes it challenging for tolerance engineering. Using large proteomic datasets of Synechocystis under various biofuels stress and environmental perturbation, a protein co-expression network was first constructed and then combined with the experimentally determined protein-protein interaction network. Proteins with statistically higher topological overlap in the integrated network were identified as common responsive proteins to both biofuels stress and environmental perturbations. In addition, a weighted gene co-expression network analysis was performed to distinguish unique responses to biofuels from those to environmental perturbations and to uncover metabolic modules and proteins uniquely associated with biofuels stress. The results showed that biofuel-specific proteins and modules were enriched in several functional categories, including photosynthesis, carbon fixation, and amino acid metabolism, which may represent potential key signatures for biofuels stress responses in Synechocystis. Network-based analysis allowed determination of the responses specifically related to biofuels stress, and the results constituted an important knowledge foundation for tolerance engineering against biofuels in Synechocystis.

  12. Inference of a Geminivirus-Host Protein-Protein Interaction Network through Affinity Purification and Mass Spectrometry Analysis.

    Science.gov (United States)

    Wang, Liping; Ding, Xue; Xiao, Jiajing; Jiménez-Gόngora, Tamara; Liu, Renyi; Lozano-Durán, Rosa

    2017-09-25

    Viruses reshape the intracellular environment of their hosts, largely through protein-protein interactions, to co-opt processes necessary for viral infection and interference with antiviral defences. Due to genome size constraints and the concomitant limited coding capacity of viruses, viral proteins are generally multifunctional and have evolved to target diverse host proteins. Inference of the virus-host interaction network can be instrumental for understanding how viruses manipulate the host machinery and how re-wiring of specific pathways can contribute to disease. Here, we use affinity purification and mass spectrometry analysis (AP-MS) to define the global landscape of interactions between the geminivirus Tomato yellow leaf curl virus (TYLCV) and its host Nicotiana benthamiana . For this purpose, we expressed tagged versions of each of TYLCV-encoded proteins (C1/Rep, C2/TrAP, C3/REn, C4, V2, and CP) in planta in the presence of the virus. Using a quantitative scoring system, 728 high-confidence plant interactors were identified, and the interaction network of each viral protein was inferred; TYLCV-targeted proteins are more connected than average, and connect with other proteins through shorter paths, which would allow the virus to exert large effects with few interactions. Comparative analyses of divergence patterns between N. benthamiana and potato, a non-host Solanaceae , showed evolutionary constraints on TYLCV-targeted proteins. Our results provide a comprehensive overview of plant proteins targeted by TYLCV during the viral infection, which may contribute to uncovering the underlying molecular mechanisms of plant viral diseases and provide novel potential targets for anti-viral strategies and crop engineering. Interestingly, some of the TYLCV-interacting proteins appear to be convergently targeted by other pathogen effectors, which suggests a central role for these proteins in plant-pathogen interactions, and pinpoints them as potential targets to

  13. Minimum curvilinearity to enhance topological prediction of protein interactions by network embedding

    KAUST Repository

    Cannistraci, Carlo

    2013-06-21

    Motivation: Most functions within the cell emerge thanks to protein-protein interactions (PPIs), yet experimental determination of PPIs is both expensive and time-consuming. PPI networks present significant levels of noise and incompleteness. Predicting interactions using only PPI-network topology (topological prediction) is difficult but essential when prior biological knowledge is absent or unreliable.Methods: Network embedding emphasizes the relations between network proteins embedded in a low-dimensional space, in which protein pairs that are closer to each other represent good candidate interactions. To achieve network denoising, which boosts prediction performance, we first applied minimum curvilinear embedding (MCE), and then adopted shortest path (SP) in the reduced space to assign likelihood scores to candidate interactions. Furthermore, we introduce (i) a new valid variation of MCE, named non-centred MCE (ncMCE); (ii) two automatic strategies for selecting the appropriate embedding dimension; and (iii) two new randomized procedures for evaluating predictions.Results: We compared our method against several unsupervised and supervisedly tuned embedding approaches and node neighbourhood techniques. Despite its computational simplicity, ncMCE-SP was the overall leader, outperforming the current methods in topological link prediction.Conclusion: Minimum curvilinearity is a valuable non-linear framework that we successfully applied to the embedding of protein networks for the unsupervised prediction of novel PPIs. The rationale for our approach is that biological and evolutionary information is imprinted in the non-linear patterns hidden behind the protein network topology, and can be exploited for predicting new protein links. The predicted PPIs represent good candidates for testing in high-throughput experiments or for exploitation in systems biology tools such as those used for network-based inference and prediction of disease-related functional modules. The

  14. Scoring protein relationships in functional interaction networks predicted from sequence data.

    Directory of Open Access Journals (Sweden)

    Gaston K Mazandu

    Full Text Available UNLABELLED: The abundance of diverse biological data from various sources constitutes a rich source of knowledge, which has the power to advance our understanding of organisms. This requires computational methods in order to integrate and exploit these data effectively and elucidate local and genome wide functional connections between protein pairs, thus enabling functional inferences for uncharacterized proteins. These biological data are primarily in the form of sequences, which determine functions, although functional properties of a protein can often be predicted from just the domains it contains. Thus, protein sequences and domains can be used to predict protein pair-wise functional relationships, and thus contribute to the function prediction process of uncharacterized proteins in order to ensure that knowledge is gained from sequencing efforts. In this work, we introduce information-theoretic based approaches to score protein-protein functional interaction pairs predicted from protein sequence similarity and conserved protein signature matches. The proposed schemes are effective for data-driven scoring of connections between protein pairs. We applied these schemes to the Mycobacterium tuberculosis proteome to produce a homology-based functional network of the organism with a high confidence and coverage. We use the network for predicting functions of uncharacterised proteins. AVAILABILITY: Protein pair-wise functional relationship scores for Mycobacterium tuberculosis strain CDC1551 sequence data and python scripts to compute these scores are available at http://web.cbio.uct.ac.za/~gmazandu/scoringschemes.

  15. The human-bacterial pathogen protein interaction networks of Bacillus anthracis, Francisella tularensis, and Yersinia pestis.

    Directory of Open Access Journals (Sweden)

    Matthew D Dyer

    2010-08-01

    Full Text Available Bacillus anthracis, Francisella tularensis, and Yersinia pestis are bacterial pathogens that can cause anthrax, lethal acute pneumonic disease, and bubonic plague, respectively, and are listed as NIAID Category A priority pathogens for possible use as biological weapons. However, the interactions between human proteins and proteins in these bacteria remain poorly characterized leading to an incomplete understanding of their pathogenesis and mechanisms of immune evasion.In this study, we used a high-throughput yeast two-hybrid assay to identify physical interactions between human proteins and proteins from each of these three pathogens. From more than 250,000 screens performed, we identified 3,073 human-B. anthracis, 1,383 human-F. tularensis, and 4,059 human-Y. pestis protein-protein interactions including interactions involving 304 B. anthracis, 52 F. tularensis, and 330 Y. pestis proteins that are uncharacterized. Computational analysis revealed that pathogen proteins preferentially interact with human proteins that are hubs and bottlenecks in the human PPI network. In addition, we computed modules of human-pathogen PPIs that are conserved amongst the three networks. Functionally, such conserved modules reveal commonalities between how the different pathogens interact with crucial host pathways involved in inflammation and immunity.These data constitute the first extensive protein interaction networks constructed for bacterial pathogens and their human hosts. This study provides novel insights into host-pathogen interactions.

  16. The function of communities in protein interaction networks at multiple scales

    Directory of Open Access Journals (Sweden)

    Jones Nick S

    2010-07-01

    Full Text Available Abstract Background If biology is modular then clusters, or communities, of proteins derived using only protein interaction network structure should define protein modules with similar biological roles. We investigate the link between biological modules and network communities in yeast and its relationship to the scale at which we probe the network. Results Our results demonstrate that the functional homogeneity of communities depends on the scale selected, and that almost all proteins lie in a functionally homogeneous community at some scale. We judge functional homogeneity using a novel test and three independent characterizations of protein function, and find a high degree of overlap between these measures. We show that a high mean clustering coefficient of a community can be used to identify those that are functionally homogeneous. By tracing the community membership of a protein through multiple scales we demonstrate how our approach could be useful to biologists focusing on a particular protein. Conclusions We show that there is no one scale of interest in the community structure of the yeast protein interaction network, but we can identify the range of resolution parameters that yield the most functionally coherent communities, and predict which communities are most likely to be functionally homogeneous.

  17. Identifying protein complex by integrating characteristic of core-attachment into dynamic PPI network.

    Directory of Open Access Journals (Sweden)

    Xianjun Shen

    Full Text Available How to identify protein complex is an important and challenging task in proteomics. It would make great contribution to our knowledge of molecular mechanism in cell life activities. However, the inherent organization and dynamic characteristic of cell system have rarely been incorporated into the existing algorithms for detecting protein complexes because of the limitation of protein-protein interaction (PPI data produced by high throughput techniques. The availability of time course gene expression profile enables us to uncover the dynamics of molecular networks and improve the detection of protein complexes. In order to achieve this goal, this paper proposes a novel algorithm DCA (Dynamic Core-Attachment. It detects protein-complex core comprising of continually expressed and highly connected proteins in dynamic PPI network, and then the protein complex is formed by including the attachments with high adhesion into the core. The integration of core-attachment feature into the dynamic PPI network is responsible for the superiority of our algorithm. DCA has been applied on two different yeast dynamic PPI networks and the experimental results show that it performs significantly better than the state-of-the-art techniques in terms of prediction accuracy, hF-measure and statistical significance in biology. In addition, the identified complexes with strong biological significance provide potential candidate complexes for biologists to validate.

  18. Identification of phosphorylation sites in protein kinase A substrates using artificial neural networks and mass spectrometry

    DEFF Research Database (Denmark)

    Hjerrild, Majbrit; Stensballe, Allan; Rasmussen, Thomas E

    2011-01-01

    Protein phosphorylation plays a key role in cell regulation and identification of phosphorylation sites is important for understanding their functional significance. Here, we present an artificial neural network algorithm: NetPhosK (http://www.cbs.dtu.dk/services/NetPhosK/) that predicts protein...

  19. A Web server for predicting proteins involved in pluripotent network

    Indian Academy of Sciences (India)

    2016-11-04

    Nov 4, 2016 ... Furthermore, PluriPred gives the confidence of the prediction from training dataset's. SVM score distribution ... Machine learning techniques; Pluripotency; primary protein sequence; self-renewal; sequence alignment technique. Supplementary ... sets by discarding the proteins used in 5-fold cross validation.

  20. Topological and functional properties of the small GTPases protein interaction network.

    Directory of Open Access Journals (Sweden)

    Anna Delprato

    Full Text Available Small GTP binding proteins of the Ras superfamily (Ras, Rho, Rab, Arf, and Ran regulate key cellular processes such as signal transduction, cell proliferation, cell motility, and vesicle transport. A great deal of experimental evidence supports the existence of signaling cascades and feedback loops within and among the small GTPase subfamilies suggesting that these proteins function in a coordinated and cooperative manner. The interplay occurs largely through association with bi-partite regulatory and effector proteins but can also occur through the active form of the small GTPases themselves. In order to understand the connectivity of the small GTPases signaling routes, a systems-level approach that analyzes data describing direct and indirect interactions was used to construct the small GTPases protein interaction network. The data were curated from the Search Tool for the Retrieval of Interacting Genes (STRING database and include only experimentally validated interactions. The network method enables the conceptualization of the overall structure as well as the underlying organization of the protein-protein interactions. The interaction network described here is comprised of 778 nodes and 1943 edges and has a scale-free topology. Rac1, Cdc42, RhoA, and HRas are identified as the hubs. Ten sub-network motifs are also identified in this study with themes in apoptosis, cell growth/proliferation, vesicle traffic, cell adhesion/junction dynamics, the nicotinamide adenine dinucleotide phosphate (NADPH oxidase response, transcription regulation, receptor-mediated endocytosis, gene silencing, and growth factor signaling. Bottleneck proteins that bridge signaling paths and proteins that overlap in multiple small GTPase networks are described along with the functional annotation of all proteins in the network.

  1. Integration and visualization of non-coding RNA and protein interaction networks

    DEFF Research Database (Denmark)

    Junge, Alexander; Refsgaard, Jan Christian; Garde, Christian

    Association and Interaction Networks) - a database that combines ncRNA-ncRNA, ncRNA-mRNA and ncRNA-protein interactions with large-scale protein association networks available in the STRING database. By integrating ncRNA and protein networks, RAIN provides a more complete picture of the cell’s complex...... interaction network. RAIN aggregates associations and (predicted) interactions of a vast collection of ncRNA classes, including microRNAs and long ncRNAs, collected from a wide range of resources: a) curated knowledge, b) experimentally supported interactions, c) predicted microRNA-target interactions, and d......) co-occurrences found by text mining Medline abstracts. Each resource was assigned a reliability score by assessing its agreement with a gold standard set of microRNA-target interactions. RAIN is available at: http://rth.dk/resources/rain...

  2. Identification of phosphorylation sites in protein kinase A substrates using artificial neural networks and mass spectrometry

    DEFF Research Database (Denmark)

    Hjerrild, M.; Stensballe, A.; Rasmussen, T.E.

    2004-01-01

    Protein phosphorylation plays a key role in cell regulation and identification of phosphorylation sites is important for understanding their functional significance. Here, we present an artificial neural network algorithm: NetPhosK (http://www.cbs.dtu.dk/services/NetPhosK/) that predicts protein...... kinase A (PKA) phosphorylation sites. The neural network was trained with a positive set of 258 experimentally verified PKA phosphorylation sites. The predictions by NetPhosK were! validated using four novel PKA substrates: Necdin, RFX5, En-2, and Wee 1. The four proteins were phosphorylated by PKA...

  3. Protein Network Signatures Associated with Exogenous Biofuels Treatments in Cyanobacterium Synechocystis sp. PCC 6803

    International Nuclear Information System (INIS)

    Pei, Guangsheng; Chen, Lei; Wang, Jiangxin; Qiao, Jianjun; Zhang, Weiwen

    2014-01-01

    Although recognized as a promising microbial cell factory for producing biofuels, current productivity in cyanobacterial systems is low. To make the processes economically feasible, one of the hurdles, which need to be overcome is the low tolerance of hosts to toxic biofuels. Meanwhile, little information is available regarding the cellular responses to biofuels stress in cyanobacteria, which makes it challenging for tolerance engineering. Using large proteomic datasets of Synechocystis under various biofuels stress and environmental perturbation, a protein co-expression network was first constructed and then combined with the experimentally determined protein–protein interaction network. Proteins with statistically higher topological overlap in the integrated network were identified as common responsive proteins to both biofuels stress and environmental perturbations. In addition, a weighted gene co-expression network analysis was performed to distinguish unique responses to biofuels from those to environmental perturbations and to uncover metabolic modules and proteins uniquely associated with biofuels stress. The results showed that biofuel-specific proteins and modules were enriched in several functional categories, including photosynthesis, carbon fixation, and amino acid metabolism, which may represent potential key signatures for biofuels stress responses in Synechocystis. Network-based analysis allowed determination of the responses specifically related to biofuels stress, and the results constituted an important knowledge foundation for tolerance engineering against biofuels in Synechocystis.

  4. Domain distribution and intrinsic disorder in hubs in the human protein–protein interaction network

    OpenAIRE

    Patil, Ashwini; Kinoshita, Kengo; Nakamura, Haruki

    2010-01-01

    Intrinsic disorder and distributed surface charge have been previously identified as some of the characteristics that differentiate hubs (proteins with a large number of interactions) from non-hubs in protein–protein interaction networks. In this study, we investigated the differences in the quantity, diversity, and functional nature of Pfam domains, and their relationship with intrinsic disorder, in hubs and non-hubs. We found that proteins with a more diverse domain composition were over-re...

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

    DEFF Research Database (Denmark)

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

    2017-01-01

    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...

  6. Protein and signaling networks in vertebrate photoreceptor cells

    Directory of Open Access Journals (Sweden)

    Karl-Wilhelm eKoch

    2015-11-01

    Full Text Available Vertebrate photoreceptor cells are exquisite light detectors operating under very dim and bright illumination. The photoexcitation and adaptation machinery in photoreceptor cells consists of protein complexes that can form highly ordered supramolecular structures and control the homeostasis and mutual dependence of the secondary messengers cGMP and Ca2+. The visual pigment in rod photoreceptors, the G protein-coupled receptor rhodopsin is organized in tracks of dimers thereby providing a signaling platform for the dynamic scaffolding of the G protein transducin. Illuminated rhodopsin is turned off by phosphorylation catalyzed by rhodopsin kinase GRK1 under control of Ca2+-recoverin. The GRK1 protein complex partly assembles in lipid raft structures, where shutting off rhodopsin seems to be more effective. Re-synthesis of cGMP is another crucial step in the recovery of the photoresponse after illumination. It is catalyzed by membrane bound sensory guanylate cyclases and is regulated by specific neuronal Ca2+-sensor proteins called GCAPs. At least one guanylate cyclase (ROS-GC1 was shown to be part of a multiprotein complex having strong interactions with the cytoskeleton and being controlled in a multimodal Ca2+-dependent fashion. The final target of the cGMP signaling cascade is a cyclic nucleotide-gated channel that is a hetero-oligomeric protein located in the plasma membrane and interacting with accessory proteins in highly organized microdomains. We summarize results and interpretations of findings related to the inhomogeneous organization of signaling units in photoreceptor outer segments.

  7. Why do hubs in the yeast protein interaction network tend to be essential: reexamining the connection between the network topology and essentiality.

    Directory of Open Access Journals (Sweden)

    Elena Zotenko

    2008-08-01

    Full Text Available The centrality-lethality rule, which notes that high-degree nodes in a protein interaction network tend to correspond to proteins that are essential, suggests that the topological prominence of a protein in a protein interaction network may be a good predictor of its biological importance. Even though the correlation between degree and essentiality was confirmed by many independent studies, the reason for this correlation remains illusive. Several hypotheses about putative connections between essentiality of hubs and the topology of protein-protein interaction networks have been proposed, but as we demonstrate, these explanations are not supported by the properties of protein interaction networks. To identify the main topological determinant of essentiality and to provide a biological explanation for the connection between the network topology and essentiality, we performed a rigorous analysis of six variants of the genomewide protein interaction network for Saccharomyces cerevisiae obtained using different techniques. We demonstrated that the majority of hubs are essential due to their involvement in Essential Complex Biological Modules, a group of densely connected proteins with shared biological function that are enriched in essential proteins. Moreover, we rejected two previously proposed explanations for the centrality-lethality rule, one relating the essentiality of hubs to their role in the overall network connectivity and another relying on the recently published essential protein interactions model.

  8. Identification of putative drug targets for human sperm-egg interaction defect using protein network approach.

    Science.gov (United States)

    Sabetian, Soudabeh; Shamsir, Mohd Shahir

    2015-07-18

    Sperm-egg interaction defect is a significant cause of in-vitro fertilization failure for infertile cases. Numerous molecular interactions in the form of protein-protein interactions mediate the sperm-egg membrane interaction process. Recent studies have demonstrated that in addition to experimental techniques, computational methods, namely protein interaction network approach, can address protein-protein interactions between human sperm and egg. Up to now, no drugs have been detected to treat sperm-egg interaction disorder, and the initial step in drug discovery research is finding out essential proteins or drug targets for a biological process. The main purpose of this study is to identify putative drug targets for human sperm-egg interaction deficiency and consider if the detected essential proteins are targets for any known drugs using protein-protein interaction network and ingenuity pathway analysis. We have created human sperm-egg protein interaction networks with high confidence, including 106 nodes and 415 interactions. Through topological analysis of the network with calculation of some metrics, such as connectivity and betweenness centrality, we have identified 13 essential proteins as putative drug targets. The potential drug targets are from integrins, fibronectins, epidermal growth factor receptors, collagens and tetraspanins protein families. We evaluated these targets by ingenuity pathway analysis, and the known drugs for the targets have been detected, and the possible effective role of the drugs on sperm-egg interaction defect has been considered. These results showed that the drugs ocriplasmin (Jetrea©), gefitinib (Iressa©), erlotinib hydrochloride (Tarceva©), clingitide, cetuximab (Erbitux©) and panitumumab (Vectibix©) are possible candidates for efficacy testing for the treatment of sperm-egg interaction deficiency. Further experimental validation can be carried out to confirm these results. We have identified the first potential list of

  9. Prediction of Protein Thermostability by an Efficient Neural Network Approach

    Directory of Open Access Journals (Sweden)

    Jalal Rezaeenour

    2016-10-01

    Full Text Available Introduction: Manipulation of protein stability is important for understanding the principles that govern protein thermostability, both in basic research and industrial applications. Various data mining techniques exist for prediction of thermostable proteins. Furthermore, ANN methods have attracted significant attention for prediction of thermostability, because they constitute an appropriate approach to mapping the non-linear input-output relationships and massive parallel computing. Method: An Extreme Learning Machine (ELM was applied to estimate thermal behavior of 1289 proteins. In the proposed algorithm, the parameters of ELM were optimized using a Genetic Algorithm (GA, which tuned a set of input variables, hidden layer biases, and input weights, to and enhance the prediction performance. The method was executed on a set of amino acids, yielding a total of 613 protein features. A number of feature selection algorithms were used to build subsets of the features. A total of 1289 protein samples and 613 protein features were calculated from UniProt database to understand features contributing to the enzymes’ thermostability and find out the main features that influence this valuable characteristic. Results:At the primary structure level, Gln, Glu and polar were the features that mostly contributed to protein thermostability. At the secondary structure level, Helix_S, Coil, and charged_Coil were the most important features affecting protein thermostability. These results suggest that the thermostability of proteins is mainly associated with primary structural features of the protein. According to the results, the influence of primary structure on the thermostabilty of a protein was more important than that of the secondary structure. It is shown that prediction accuracy of ELM (mean square error can improve dramatically using GA with error rates RMSE=0.004 and MAPE=0.1003. Conclusion: The proposed approach for forecasting problem

  10. Mining protein interactomes to improve their reliability and support the advancement of network medicine

    KAUST Repository

    Alanis Lobato, Gregorio

    2015-09-23

    High-throughput detection of protein interactions has had a major impact in our understanding of the intricate molecular machinery underlying the living cell, and has permitted the construction of very large protein interactomes. The protein networks that are currently available are incomplete and a significant percentage of their interactions are false positives. Fortunately, the structural properties observed in good quality social or technological networks are also present in biological systems. This has encouraged the development of tools, to improve the reliability of protein networks and predict new interactions based merely on the topological characteristics of their components. Since diseases are rarely caused by the malfunction of a single protein, having a more complete and reliable interactome is crucial in order to identify groups of inter-related proteins involved in disease etiology. These system components can then be targeted with minimal collateral damage. In this article, an important number of network mining tools is reviewed, together with resources from which reliable protein interactomes can be constructed. In addition to the review, a few representative examples of how molecular and clinical data can be integrated to deepen our understanding of pathogenesis are discussed.

  11. Exploring overlapping functional units with various structure in protein interaction networks.

    Directory of Open Access Journals (Sweden)

    Xiao-Fei Zhang

    Full Text Available Revealing functional units in protein-protein interaction (PPI networks are important for understanding cellular functional organization. Current algorithms for identifying functional units mainly focus on cohesive protein complexes which have more internal interactions than external interactions. Most of these approaches do not handle overlaps among complexes since they usually allow a protein to belong to only one complex. Moreover, recent studies have shown that other non-cohesive structural functional units beyond complexes also exist in PPI networks. Thus previous algorithms that just focus on non-overlapping cohesive complexes are not able to present the biological reality fully. Here, we develop a new regularized sparse random graph model (RSRGM to explore overlapping and various structural functional units in PPI networks. RSRGM is principally dominated by two model parameters. One is used to define the functional units as groups of proteins that have similar patterns of connections to others, which allows RSRGM to detect non-cohesive structural functional units. The other one is used to represent the degree of proteins belonging to the units, which supports a protein belonging to more than one revealed unit. We also propose a regularizer to control the smoothness between the estimators of these two parameters. Experimental results on four S. cerevisiae PPI networks show that the performance of RSRGM on detecting cohesive complexes and overlapping complexes is superior to that of previous competing algorithms. Moreover, RSRGM has the ability to discover biological significant functional units besides complexes.

  12. Control of Cellular Structural Networks Through Unstructured Protein Domains

    Science.gov (United States)

    2016-07-01

    Distribution Unlimited UU UU UU UU 01-07-2016 1-Oct-2009 30-Sep-2015 Final Report: WHITEPAPER ; Research Area 8; Control of cellular structural networks...Projects Office 2150 Shattuck Avenue, Suite 300 Berkeley, CA 94704 -5940 ABSTRACT Final Report: WHITEPAPER ; Research Area 8; Control of cellular structural

  13. Toward a rigorous network of protein-protein interactions of the model sulfate reducer Desulfovibrio vulgaris Hildenborough

    Energy Technology Data Exchange (ETDEWEB)

    Chhabra, S.R.; Joachimiak, M.P.; Petzold, C.J.; Zane, G.M.; Price, M.N.; Gaucher, S.; Reveco, S.A.; Fok, V.; Johanson, A.R.; Batth, T.S.; Singer, M.; Chandonia, J.M.; Joyner, D.; Hazen, T.C.; Arkin, A.P.; Wall, J.D.; Singh, A.K.; Keasling, J.D.

    2011-05-01

    Protein–protein interactions offer an insight into cellular processes beyond what may be obtained by the quantitative functional genomics tools of proteomics and transcriptomics. The aforementioned tools have been extensively applied to study E. coli and other aerobes and more recently to study the stress response behavior of Desulfovibrio 5 vulgaris Hildenborough, a model anaerobe and sulfate reducer. In this paper we present the first attempt to identify protein-protein interactions in an obligate anaerobic bacterium. We used suicide vector-assisted chromosomal modification of 12 open reading frames encoded by this sulfate reducer to append an eight amino acid affinity tag to the carboxy-terminus of the chosen proteins. Three biological replicates of the 10 ‘pulled-down’ proteins were separated and analyzed using liquid chromatography-mass spectrometry. Replicate agreement ranged between 35% and 69%. An interaction network among 12 bait and 90 prey proteins was reconstructed based on 134 bait-prey interactions computationally identified to be of high confidence. We discuss the biological significance of several unique metabolic features of D. vulgaris revealed by this protein-protein interaction data 15 and protein modifications that were observed. These include the distinct role of the putative carbon monoxide-induced hydrogenase, unique electron transfer routes associated with different oxidoreductases, and the possible role of methylation in regulating sulfate reduction.

  14. A combinatorial approach to detect coevolved amino acid networks in protein families of variable divergence.

    Directory of Open Access Journals (Sweden)

    Julie Baussand

    2009-09-01

    Full Text Available Communication between distant sites often defines the biological role of a protein: amino acid long-range interactions are as important in binding specificity, allosteric regulation and conformational change as residues directly contacting the substrate. The maintaining of functional and structural coupling of long-range interacting residues requires coevolution of these residues. Networks of interaction between coevolved residues can be reconstructed, and from the networks, one can possibly derive insights into functional mechanisms for the protein family. We propose a combinatorial method for mapping conserved networks of amino acid interactions in a protein which is based on the analysis of a set of aligned sequences, the associated distance tree and the combinatorics of its subtrees. The degree of coevolution of all pairs of coevolved residues is identified numerically, and networks are reconstructed with a dedicated clustering algorithm. The method drops the constraints on high sequence divergence limiting the range of applicability of the statistical approaches previously proposed. We apply the method to four protein families where we show an accurate detection of functional networks and the possibility to treat sets of protein sequences of variable divergence.

  15. Exploring the Ligand-Protein Networks in Traditional Chinese Medicine: Current Databases, Methods, and Applications

    Directory of Open Access Journals (Sweden)

    Mingzhu Zhao

    2013-01-01

    Full Text Available The traditional Chinese medicine (TCM, which has thousands of years of clinical application among China and other Asian countries, is the pioneer of the “multicomponent-multitarget” and network pharmacology. Although there is no doubt of the efficacy, it is difficult to elucidate convincing underlying mechanism of TCM due to its complex composition and unclear pharmacology. The use of ligand-protein networks has been gaining significant value in the history of drug discovery while its application in TCM is still in its early stage. This paper firstly surveys TCM databases for virtual screening that have been greatly expanded in size and data diversity in recent years. On that basis, different screening methods and strategies for identifying active ingredients and targets of TCM are outlined based on the amount of network information available, both on sides of ligand bioactivity and the protein structures. Furthermore, applications of successful in silico target identification attempts are discussed in detail along with experiments in exploring the ligand-protein networks of TCM. Finally, it will be concluded that the prospective application of ligand-protein networks can be used not only to predict protein targets of a small molecule, but also to explore the mode of action of TCM.

  16. Discovery of intramolecular signal transduction network based on a new protein dynamics model of energy dissipation.

    Directory of Open Access Journals (Sweden)

    Cheng-Wei Ma

    Full Text Available A novel approach to reveal intramolecular signal transduction network is proposed in this work. To this end, a new algorithm of network construction is developed, which is based on a new protein dynamics model of energy dissipation. A key feature of this approach is that direction information is specified after inferring protein residue-residue interaction network involved in the process of signal transduction. This enables fundamental analysis of the regulation hierarchy and identification of regulation hubs of the signaling network. A well-studied allosteric enzyme, E. coli aspartokinase III, is used as a model system to demonstrate the new method. Comparison with experimental results shows that the new approach is able to predict all the sites that have been experimentally proved to desensitize allosteric regulation of the enzyme. In addition, the signal transduction network shows a clear preference for specific structural regions, secondary structural types and residue conservation. Occurrence of super-hubs in the network indicates that allosteric regulation tends to gather residues with high connection ability to collectively facilitate the signaling process. Furthermore, a new parameter of propagation coefficient is defined to determine the propagation capability of residues within a signal transduction network. In conclusion, the new approach is useful for fundamental understanding of the process of intramolecular signal transduction and thus has significant impact on rational design of novel allosteric proteins.

  17. Molecular Principles of Gene Fusion Mediated Rewiring of Protein Interaction Networks in Cancer.

    Science.gov (United States)

    Latysheva, Natasha S; Oates, Matt E; Maddox, Louis; Flock, Tilman; Gough, Julian; Buljan, Marija; Weatheritt, Robert J; Babu, M Madan

    2016-08-18

    Gene fusions are common cancer-causing mutations, but the molecular principles by which fusion protein products affect interaction networks and cause disease are not well understood. Here, we perform an integrative analysis of the structural, interactomic, and regulatory properties of thousands of putative fusion proteins. We demonstrate that genes that form fusions (i.e., parent genes) tend to be highly connected hub genes, whose protein products are enriched in structured and disordered interaction-mediating features. Fusion often results in the loss of these parental features and the depletion of regulatory sites such as post-translational modifications. Fusion products disproportionately connect proteins that did not previously interact in the protein interaction network. In this manner, fusion products can escape cellular regulation and constitutively rewire protein interaction networks. We suggest that the deregulation of central, interaction-prone proteins may represent a widespread mechanism by which fusion proteins alter the topology of cellular signaling pathways and promote cancer. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

  18. Dynamic changes in protein functional linkage networks revealed by integration with gene expression data.

    Directory of Open Access Journals (Sweden)

    Shubhada R Hegde

    2008-11-01

    Full Text Available Response of cells to changing environmental conditions is governed by the dynamics of intricate biomolecular interactions. It may be reasonable to assume, proteins being the dominant macromolecules that carry out routine cellular functions, that understanding the dynamics of protein:protein interactions might yield useful insights into the cellular responses. The large-scale protein interaction data sets are, however, unable to capture the changes in the profile of protein:protein interactions. In order to understand how these interactions change dynamically, we have constructed conditional protein linkages for Escherichia coli by integrating functional linkages and gene expression information. As a case study, we have chosen to analyze UV exposure in wild-type and SOS deficient E. coli at 20 minutes post irradiation. The conditional networks exhibit similar topological properties. Although the global topological properties of the networks are similar, many subtle local changes are observed, which are suggestive of the cellular response to the perturbations. Some such changes correspond to differences in the path lengths among the nodes of carbohydrate metabolism correlating with its loss in efficiency in the UV treated cells. Similarly, expression of hubs under unique conditions reflects the importance of these genes. Various centrality measures applied to the networks indicate increased importance for replication, repair, and other stress proteins for the cells under UV treatment, as anticipated. We thus propose a novel approach for studying an organism at the systems level by integrating genome-wide functional linkages and the gene expression data.

  19. Regulation of lifespan, metabolism, and stress responses by the Drosophila SH2B protein, Lnk.

    Directory of Open Access Journals (Sweden)

    Cathy Slack

    2010-03-01

    Full Text Available Drosophila Lnk is the single ancestral orthologue of a highly conserved family of structurally-related intracellular adaptor proteins, the SH2B proteins. As adaptors, they lack catalytic activity but contain several protein-protein interaction domains, thus playing a critical role in signal transduction from receptor tyrosine kinases to form protein networks. Physiological studies of SH2B function in mammals have produced conflicting data. However, a recent study in Drosophila has shown that Lnk is an important regulator of the insulin/insulin-like growth factor (IGF-1 signaling (IIS pathway during growth, functioning in parallel to the insulin receptor substrate, Chico. As this pathway also has an evolutionary conserved role in the determination of organism lifespan, we investigated whether Lnk is required for normal lifespan in Drosophila. Phenotypic analysis of mutants for Lnk revealed that loss of Lnk function results in increased lifespan and improved survival under conditions of oxidative stress and starvation. Starvation resistance was found to be associated with increased metabolic stores of carbohydrates and lipids indicative of impaired metabolism. Biochemical and genetic data suggest that Lnk functions in both the IIS and Ras/Mitogen activated protein Kinase (MapK signaling pathways. Microarray studies support this model, showing transcriptional feedback onto genes in both pathways as well as indicating global changes in both lipid and carbohydrate metabolism. Finally, our data also suggest that Lnk itself may be a direct target of the IIS responsive transcription factor, dFoxo, and that dFoxo may repress Lnk expression. We therefore describe novel functions for a member of the SH2B protein family and provide the first evidence for potential mechanisms of SH2B regulation. Our findings suggest that IIS signaling in Drosophila may require the activity of a second intracellular adaptor, thereby yielding fundamental new insights into the

  20. Eukaryotic LYR Proteins Interact with Mitochondrial Protein Complexes

    Directory of Open Access Journals (Sweden)

    Heike Angerer

    2015-02-01

    Full Text Available In eukaryotic cells, mitochondria host ancient essential bioenergetic and biosynthetic pathways. LYR (leucine/tyrosine/arginine motif proteins (LYRMs of the Complex1_LYR-like superfamily interact with protein complexes of bacterial origin. Many LYR proteins function as extra subunits (LYRM3 and LYRM6 or novel assembly factors (LYRM7, LYRM8, ACN9 and FMC1 of the oxidative phosphorylation (OXPHOS core complexes. Structural insights into complex I accessory subunits LYRM6 and LYRM3 have been provided by analyses of EM and X-ray structures of complex I from bovine and the yeast Yarrowia lipolytica, respectively. Combined structural and biochemical studies revealed that LYRM6 resides at the matrix arm close to the ubiquinone reduction site. For LYRM3, a position at the distal proton-pumping membrane arm facing the matrix space is suggested. Both LYRMs are supposed to anchor an acyl-carrier protein (ACPM independently to complex I. The function of this duplicated protein interaction of ACPM with respiratory complex I is still unknown. Analysis of protein-protein interaction screens, genetic analyses and predicted multi-domain LYRMs offer further clues on an interaction network and adaptor-like function of LYR proteins in mitochondria.

  1. Bio::Homology::InterologWalk--a Perl module to build putative protein-protein interaction networks through interolog mapping.

    Science.gov (United States)

    Gallone, Giuseppe; Simpson, T Ian; Armstrong, J Douglas; Jarman, Andrew P

    2011-07-18

    Protein-protein interaction (PPI) data are widely used to generate network models that aim to describe the relationships between proteins in biological systems. The fidelity and completeness of such networks is primarily limited by the paucity of protein interaction information and by the restriction of most of these data to just a few widely studied experimental organisms. In order to extend the utility of existing PPIs, computational methods can be used that exploit functional conservation between orthologous proteins across taxa to predict putative PPIs or 'interologs'. To date most interolog prediction efforts have been restricted to specific biological domains with fixed underlying data sources and there are no software tools available that provide a generalised framework for 'on-the-fly' interolog prediction. We introduce Bio::Homology::InterologWalk, a Perl module to retrieve, prioritise and visualise putative protein-protein interactions through an orthology-walk method. The module uses orthology and experimental interaction data to generate putative PPIs and optionally collates meta-data into an Interaction Prioritisation Index that can be used to help prioritise interologs for further analysis. We show the application of our interolog prediction method to the genomic interactome of the fruit fly, Drosophila melanogaster. We analyse the resulting interaction networks and show that the method proposes new interactome members and interactions that are candidates for future experimental investigation. Our interolog prediction tool employs the Ensembl Perl API and PSICQUIC enabled protein interaction data sources to generate up to date interologs 'on-the-fly'. This represents a significant advance on previous methods for interolog prediction as it allows the use of the latest orthology and protein interaction data for all of the genomes in Ensembl. The module outputs simple text files, making it easy to customise the results by post-processing, allowing the

  2. Bio::Homology::InterologWalk - A Perl module to build putative protein-protein interaction networks through interolog mapping

    Directory of Open Access Journals (Sweden)

    Armstrong J Douglas

    2011-07-01

    Full Text Available Abstract Background Protein-protein interaction (PPI data are widely used to generate network models that aim to describe the relationships between proteins in biological systems. The fidelity and completeness of such networks is primarily limited by the paucity of protein interaction information and by the restriction of most of these data to just a few widely studied experimental organisms. In order to extend the utility of existing PPIs, computational methods can be used that exploit functional conservation between orthologous proteins across taxa to predict putative PPIs or 'interologs'. To date most interolog prediction efforts have been restricted to specific biological domains with fixed underlying data sources and there are no software tools available that provide a generalised framework for 'on-the-fly' interolog prediction. Results We introduce Bio::Homology::InterologWalk, a Perl module to retrieve, prioritise and visualise putative protein-protein interactions through an orthology-walk method. The module uses orthology and experimental interaction data to generate putative PPIs and optionally collates meta-data into an Interaction Prioritisation Index that can be used to help prioritise interologs for further analysis. We show the application of our interolog prediction method to the genomic interactome of the fruit fly, Drosophila melanogaster. We analyse the resulting interaction networks and show that the method proposes new interactome members and interactions that are candidates for future experimental investigation. Conclusions Our interolog prediction tool employs the Ensembl Perl API and PSICQUIC enabled protein interaction data sources to generate up to date interologs 'on-the-fly'. This represents a significant advance on previous methods for interolog prediction as it allows the use of the latest orthology and protein interaction data for all of the genomes in Ensembl. The module outputs simple text files, making it easy

  3. Systematic discovery of new recognition peptides mediating protein interaction networks

    DEFF Research Database (Denmark)

    Neduva, Victor; Linding, Rune; Su-Angrand, Isabelle

    2005-01-01

    Many aspects of cell signalling, trafficking, and targeting are governed by interactions between globular protein domains and short peptide segments. These domains often bind multiple peptides that share a common sequence pattern, or "linear motif" (e.g., SH3 binding to PxxP). Many domains are kn...

  4. Functional protein networks unifying limb girdle muscular dystrophy

    NARCIS (Netherlands)

    Morrée, Antoine de

    2011-01-01

    Limb Girdle Muscular Dystrophy (LGMD) is a rare progressive heterogeneous disorder that can be caused by mutations in at least 21 different genes. These genes are often widely expressed and encode proteins with highly differing functions. And yet mutations in all of them give rise to a similar

  5. Analysis of core–periphery organization in protein contact networks ...

    Indian Academy of Sciences (India)

    Cartoon tube representation of the tertiary structure of Inositol monophosphatase (PDB Id: 1g0h) protein showing binding with a ligand molecule IPD (shown in blue) and two carbon atoms (shown in yellow). Most of the residues interacting with the ligand, indicated in spear format, belong to the innermost core (shown in red) ...

  6. Insights into biological information processing: structural and dynamical analysis of a human protein signalling network

    Energy Technology Data Exchange (ETDEWEB)

    Fuente, Alberto de la; Fotia, Giorgio; Maggio, Fabio; Mancosu, Gianmaria; Pieroni, Enrico [CRS4 Bioinformatica, Parco Tecnologico POLARIS, Ed.1, Loc Piscinamanna, Pula (Italy)], E-mail: alf@crs4.it

    2008-06-06

    We present an investigation on the structural and dynamical properties of a 'human protein signalling network' (HPSN). This biological network is composed of nodes that correspond to proteins and directed edges that represent signal flows. In order to gain insight into the organization of cell information processing this network is analysed taking into account explicitly the edge directions. We explore the topological properties of the HPSN at the global and the local scale, further applying the generating function formalism to provide a suitable comparative model. The relationship between the node degrees and the distribution of signals through the network is characterized using degree correlation profiles. Finally, we analyse the dynamical properties of small sub-graphs showing high correlation between their occurrence and dynamic stability.

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

    Science.gov (United States)

    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.

  8. Dynamic Proteomic Characteristics and Network Integration Revealing Key Proteins for Two Kernel Tissue Developments in Popcorn.

    Directory of Open Access Journals (Sweden)

    Yongbin Dong

    Full Text Available The formation and development of maize kernel is a complex dynamic physiological and biochemical process that involves the temporal and spatial expression of many proteins and the regulation of metabolic pathways. In this study, the protein profiles of the endosperm and pericarp at three important developmental stages were analyzed by isobaric tags for relative and absolute quantification (iTRAQ labeling coupled with LC-MS/MS in popcorn inbred N04. Comparative quantitative proteomic analyses among developmental stages and between tissues were performed, and the protein networks were integrated. A total of 6,876 proteins were identified, of which 1,396 were nonredundant. Specific proteins and different expression patterns were observed across developmental stages and tissues. The functional annotation of the identified proteins revealed the importance of metabolic and cellular processes, and binding and catalytic activities for the development of the tissues. The whole, endosperm-specific and pericarp-specific protein networks integrated 125, 9 and 77 proteins, respectively, which were involved in 54 KEGG pathways and reflected their complex metabolic interactions. Confirmation for the iTRAQ endosperm proteins by two-dimensional gel electrophoresis showed that 44.44% proteins were commonly found. However, the concordance between mRNA level and the protein abundance varied across different proteins, stages, tissues and inbred lines, according to the gene cloning and expression analyses of four relevant proteins with important functions and different expression levels. But the result by western blot showed their same expression tendency for the four proteins as by iTRAQ. These results could provide new insights into the developmental mechanisms of endosperm and pericarp, and grain formation in maize.

  9. Building and analyzing protein interactome networks by cross-species comparisons

    Directory of Open Access Journals (Sweden)

    Blackman Barron

    2010-03-01

    Full Text Available Abstract Background A genomic catalogue of protein-protein interactions is a rich source of information, particularly for exploring the relationships between proteins. Numerous systems-wide and small-scale experiments have been conducted to identify interactions; however, our knowledge of all interactions for any one species is incomplete, and alternative means to expand these network maps is needed. We therefore took a comparative biology approach to predict protein-protein interactions across five species (human, mouse, fly, worm, and yeast and developed InterologFinder for research biologists to easily navigate this data. We also developed a confidence score for interactions based on available experimental evidence and conservation across species. Results The connectivity of the resultant networks was determined to have scale-free distribution, small-world properties, and increased local modularity, indicating that the added interactions do not disrupt our current understanding of protein network structures. We show examples of how these improved interactomes can be used to analyze a genome-scale dataset (RNAi screen and to assign new function to proteins. Predicted interactions within this dataset were tested by co-immunoprecipitation, resulting in a high rate of validation, suggesting the high quality of networks produced. Conclusions Protein-protein interactions were predicted in five species, based on orthology. An InteroScore, a score accounting for homology, number of orthologues with evidence of interactions, and number of unique observations of interactions, is given to each known and predicted interaction. Our website http://www.interologfinder.org provides research biologists intuitive access to this data.

  10. Revisiting date and party hubs: novel approaches to role assignment in protein interaction networks.

    Science.gov (United States)

    Agarwal, Sumeet; Deane, Charlotte M; Porter, Mason A; Jones, Nick S

    2010-06-17

    The idea of "date" and "party" hubs has been influential in the study of protein-protein interaction networks. Date hubs display low co-expression with their partners, whilst party hubs have high co-expression. It was proposed that party hubs are local coordinators whereas date hubs are global connectors. Here, we show that the reported importance of date hubs to network connectivity can in fact be attributed to a tiny subset of them. Crucially, these few, extremely central, hubs do not display particularly low expression correlation, undermining the idea of a link between this quantity and hub function. The date/party distinction was originally motivated by an approximately bimodal distribution of hub co-expression; we show that this feature is not always robust to methodological changes. Additionally, topological properties of hubs do not in general correlate with co-expression. However, we find significant correlations between interaction centrality and the functional similarity of the interacting proteins. We suggest that thinking in terms of a date/party dichotomy for hubs in protein interaction networks is not meaningful, and it might be more useful to conceive of roles for protein-protein interactions rather than for individual proteins.

  11. Revisiting date and party hubs: novel approaches to role assignment in protein interaction networks.

    Directory of Open Access Journals (Sweden)

    Sumeet Agarwal

    2010-06-01

    Full Text Available The idea of "date" and "party" hubs has been influential in the study of protein-protein interaction networks. Date hubs display low co-expression with their partners, whilst party hubs have high co-expression. It was proposed that party hubs are local coordinators whereas date hubs are global connectors. Here, we show that the reported importance of date hubs to network connectivity can in fact be attributed to a tiny subset of them. Crucially, these few, extremely central, hubs do not display particularly low expression correlation, undermining the idea of a link between this quantity and hub function. The date/party distinction was originally motivated by an approximately bimodal distribution of hub co-expression; we show that this feature is not always robust to methodological changes. Additionally, topological properties of hubs do not in general correlate with co-expression. However, we find significant correlations between interaction centrality and the functional similarity of the interacting proteins. We suggest that thinking in terms of a date/party dichotomy for hubs in protein interaction networks is not meaningful, and it might be more useful to conceive of roles for protein-protein interactions rather than for individual proteins.

  12. Mass-action equilibrium and non-specific interactions in protein binding networks

    Science.gov (United States)

    Maslov, Sergei

    2009-03-01

    Large-scale protein binding networks serve as a paradigm of complex properties of living cells. These networks are naturally weighted with edges characterized by binding strength and protein-nodes -- by their concentrations. However, the state-of-the-art high-throughput experimental techniques generate just a binary (yes or no) information about individual interactions. As a result, most of the previous research concentrated just on topology of these networks. In a series of recent publications [1-4] my collaborators and I went beyond purely topological studies and calculated the mass-action equilibrium of a genome-wide binding network using experimentally determined protein concentrations, localizations, and reliable binding interactions in baker's yeast. We then studied how this equilibrium responds to large perturbations [1-2] and noise [3] in concentrations of proteins. We demonstrated that the change in the equilibrium concentration of a protein exponentially decays (and sign-alternates) with its network distance away from the perturbed node. This explains why, despite a globally connected topology, individual functional modules in such networks are able to operate fairly independently. In a separate study [4] we quantified the interplay between specific and non-specific binding interactions under crowded conditions inside living cells. We show how the need to limit the waste of resources constrains the number of types and concentrations of proteins that are present at the same time and at the same place in yeast cells. [1] S Maslov, I. Ispolatov, PNAS 104:13655 (2007). [2] S. Maslov, K. Sneppen, I. Ispolatov, New J. of Phys. 9: 273 (2007). [3] K-K. Yan, D. Walker, S. Maslov, PRL accepted (2008). [4] J. Zhang, S. Maslov, and E. I. Shakhnovich, Mol Syst Biol 4, 210 (2008).

  13. Identification and network of outer membrane proteins regulating streptomysin resistance in Escherichia coli.

    Science.gov (United States)

    Li, Hui; Wang, Bao-Cheng; Xu, Wen-Jiao; Lin, Xiang-Min; Peng, Xuan-Xian

    2008-09-01

    Bacterial Outer membrane (OM) proteins involved in antibiotic resistance have been reported. However, little is known about the OM proteins and their interaction network regulating streptomycin (SM) resistance. In the present study, a subproteomic approach was utilized to characterize OM proteins of Escherichia coli with SM resistance. TolC, OmpT and LamB were found to be up-regulated, and FadL, OmpW and a location-unknown protein Dps were down-regulated in the SM-resistant E. coli strain. These changes at the level of protein expression were validated using Western blotting. The possible roles of the altered proteins involved in the SM resistance were investigated using genetic modified strains with the deletion of these altered genes. It is found that decreased and elevated minimum inhibitory concentrations and survival capabilities of the gene deleted strains and their resistant strains, Delta tolC, Delta ompT, Delta dps, Delta tolC-R, Delta ompT-R, Delta dps-R and Delta fadL-R, were correlated with the changes of TolC, OmpT, Dps and FadL at the protein expression levels detected by 2-DE gels, respectively. The results may suggest that these proteins are the key OM proteins and play important roles in the regulation of SM resistance in E. coli. Furthermore, an interaction network of altered OM proteins involved in the SM resistance was proposed in this report. Of the six altered proteins, TolC may play a central role in the network. These findings may provide novel insights into mechanisms of SM resistance in E. coli.

  14. Sequence similarity network reveals common ancestry of multidomain proteins.

    Directory of Open Access Journals (Sweden)

    Nan Song

    2008-05-01

    Full Text Available We address the problem of homology identification in complex multidomain families with varied domain architectures. The challenge is to distinguish sequence pairs that share common ancestry from pairs that share an inserted domain but are otherwise unrelated. This distinction is essential for accuracy in gene annotation, function prediction, and comparative genomics. There are two major obstacles to multidomain homology identification: lack of a formal definition and lack of curated benchmarks for evaluating the performance of new methods. We offer preliminary solutions to both problems: 1 an extension of the traditional model of homology to include domain insertions; and 2 a manually curated benchmark of well-studied families in mouse and human. We further present Neighborhood Correlation, a novel method that exploits the local structure of the sequence similarity network to identify homologs with great accuracy based on the observation that gene duplication and domain shuffling leave distinct patterns in the sequence similarity network. In a rigorous, empirical comparison using our curated data, Neighborhood Correlation outperforms sequence similarity, alignment length, and domain architecture comparison. Neighborhood Correlation is well suited for automated, genome-scale analyses. It is easy to compute, does not require explicit knowledge of domain architecture, and classifies both single and multidomain homologs with high accuracy. Homolog predictions obtained with our method, as well as our manually curated benchmark and a web-based visualization tool for exploratory analysis of the network neighborhood structure, are available at http://www.neighborhoodcorrelation.org. Our work represents a departure from the prevailing view that the concept of homology cannot be applied to genes that have undergone domain shuffling. In contrast to current approaches that either focus on the homology of individual domains or consider only families with

  15. 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

    and built a CLASP2 protein network in 3T3-L1 adipocytes. Using two different commercially available antibodies for CLASP2 and an antibody for epitope-tagged, overexpressed CLASP2, we performed multiple affinity purification coupled with mass spectrometry (AP-MS) experiments in combination with label-free......, 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...

  16. Protein-protein networks construction and their relevance measurement based on multi-epitope-ligand-kartographie and gene ontology data of T-cell surface proteins for polymyositis.

    Science.gov (United States)

    Li, Fang-Zhen; Gao, Feng

    2012-08-01

    Polymyositis is an inflammatory myopathy characterized by muscle invasion of T-cells penetrating the basal lamina and displacing the plasma membrane of normal muscle fibers. In order to understand the different adhesive mechanisms at the T-cell surface, Schubert randomly selected 19 proteins expressed at the T-cell surface and studied them using MELK technique [4], among which 15 proteins are picked up for further study by us. Two types of functional similarity networks are constructed for these proteins. The first type is MELK similarity network, which is constructed based on their MELK data by using the McNemar's test [24]. The second type is GO similarity network, which is constructed based on their GO annotation data by using the RSS method to measuring functional similarity. Then the subset surprisology theory is employed to measure the degree of similarity between two networks. Our computing results show that these two types of networks are high related. This conclusion added new values on MELK technique and expanded its applications greatly.

  17. Dynamic modular architecture of protein-protein interaction networks beyond the dichotomy of 'date' and 'party' hubs.

    Science.gov (United States)

    Chang, Xiao; Xu, Tao; Li, Yun; Wang, Kai

    2013-01-01

    The protein-protein interaction (PPI) networks are dynamically organized as modules, and are typically described by hub dichotomy: 'party' hubs act as intramodule hubs and are coexpressed with their partners, yet 'date' hubs act as coordinators among modules and are incoherently expressed with their partners. However, there remains skepticism about the existence of hub dichotomy. Since different algorithms and data sets were used in previous studies to test the model of hub classification, the conclusions may be largely influenced by the potential inherent biases. In this study, we evaluated two data sets of yeast interactome, and systematically investigated the behavior of hubs from multiple perspectives including co-expression patterns, topological roles and functional classifications. Our results revealed consistency between the two data sets, confirming the presence of hub dichotomy. Furthermore, we analyzed a human interactome data set, and demonstrated that the modular architecture of the PPI networks was more complicated than hub dichotomy.

  18. Similar Pathogen Targets in Arabidopsis thaliana and Homo sapiens Protein Networks

    Science.gov (United States)

    2012-09-21

    the average degree (kav) and average number of pathogen effectors per protein ( pav ) in each shell for both networks - despite being associated with...species from different kingdoms (for humans, power-law regression produces pav ~0:033:kav 0:744, r2~0:788, p~3:039:10{10, MIC~0:820; for Arabidopsis, pav ...pathogen interactions ( pav ) per node in a shell (log-log scale) with power- law fits. The core of each network is circled. (A) Human protein interaction

  19. Discovery of a Unique Clp Component, ClpF, in Chloroplasts: A Proposed Binary ClpF-ClpS1 Adaptor Complex Functions in Substrate Recognition and Delivery.

    Science.gov (United States)

    Nishimura, Kenji; Apitz, Janina; Friso, Giulia; Kim, Jitae; Ponnala, Lalit; Grimm, Bernhard; van Wijk, Klaas J

    2015-10-01

    Clp proteases are found in prokaryotes, mitochondria, and plastids where they play crucial roles in maintaining protein homeostasis (proteostasis). The plant plastid Clp machinery comprises a hetero-oligomeric ClpPRT proteolytic core, ATP-dependent chaperones ClpC and ClpD, and an adaptor protein, ClpS1. ClpS1 selects substrates to the ClpPR protease-ClpC chaperone complex for degradation, but the underlying substrate recognition and delivery mechanisms are currently unclear. Here, we characterize a ClpS1-interacting protein in Arabidopsis thaliana, ClpF, which can interact with the Clp substrate glutamyl-tRNA reductase. ClpF and ClpS1 mutually stimulate their association with ClpC. ClpF, which is only found in photosynthetic eukaryotes, contains bacterial uvrB/C and YccV protein domains and a unique N-terminal domain. We propose a testable model in which ClpS1 and ClpF form a binary adaptor for selective substrate recognition and delivery to ClpC, reflecting an evolutionary adaptation of the Clp system to the plastid proteome. © 2015 American Society of Plant Biologists. All rights reserved.

  20. An Interaction between KSHV ORF57 and UIF Provides mRNA-Adaptor Redundancy in Herpesvirus Intronless mRNA Export

    Science.gov (United States)

    Jackson, Brian R.; Boyne, James R.; Noerenberg, Marko; Taylor, Adam; Hautbergue, Guillaume M.; Walsh, Matthew J.; Wheat, Rachel; Blackbourn, David J.; Wilson, Stuart A.; Whitehouse, Adrian

    2011-01-01

    The hTREX complex mediates cellular bulk mRNA nuclear export by recruiting the nuclear export factor, TAP, via a direct interaction with the export adaptor, Aly. Intriguingly however, depletion of Aly only leads to a modest reduction in cellular mRNA nuclear export, suggesting the existence of additional mRNA nuclear export adaptor proteins. In order to efficiently export Kaposi's sarcoma-associated herpesvirus (KSHV) intronless mRNAs from the nucleus, the KSHV ORF57 protein recruits hTREX onto viral intronless mRNAs allowing access to the TAP-mediated export pathway. Similarly however, depletion of Aly only leads to a modest reduction in the nuclear export of KSHV intronless mRNAs. Herein, we identify a novel interaction between ORF57 and the cellular protein, UIF. We provide the first evidence that the ORF57-UIF interaction enables the recruitment of hTREX and TAP to KSHV intronless mRNAs in Aly-depleted cells. Strikingly, depletion of both Aly and UIF inhibits the formation of an ORF57-mediated nuclear export competent ribonucleoprotein particle and consequently prevents ORF57-mediated mRNA nuclear export and KSHV protein production. Importantly, these findings highlight that redundancy exists in the eukaryotic system for certain hTREX components involved in the mRNA nuclear export of intronless KSHV mRNAs. PMID:21814512

  1. A Bayesian framework for cell-level protein network analysis for multivariate proteomics image data

    Science.gov (United States)

    Kovacheva, Violet N.; Sirinukunwattana, Korsuk; Rajpoot, Nasir M.

    2014-03-01

    The recent development of multivariate imaging techniques, such as the Toponome Imaging System (TIS), has facilitated the analysis of multiple co-localisation of proteins. This could hold the key to understanding complex phenomena such as protein-protein interaction in cancer. In this paper, we propose a Bayesian framework for cell level network analysis allowing the identification of several protein pairs having significantly higher co-expression levels in cancerous tissue samples when compared to normal colon tissue. It involves segmenting the DAPI-labeled image into cells and determining the cell phenotypes according to their protein-protein dependence profile. The cells are phenotyped using Gaussian Bayesian hierarchical clustering (GBHC) after feature selection is performed. The phenotypes are then analysed using Difference in Sums of Weighted cO-dependence Profiles (DiSWOP), which detects differences in the co-expression patterns of protein pairs. We demonstrate that the pairs highlighted by the proposed framework have high concordance with recent results using a different phenotyping method. This demonstrates that the results are independent of the clustering method used. In addition, the highlighted protein pairs are further analysed via protein interaction pathway databases and by considering the localization of high protein-protein dependence within individual samples. This suggests that the proposed approach could identify potentially functional protein complexes active in cancer progression and cell differentiation.

  2. Modification of gene duplicability during the evolution of protein interaction network.

    Directory of Open Access Journals (Sweden)

    Matteo D'Antonio

    2011-04-01

    Full Text Available Duplications of genes encoding highly connected and essential proteins are selected against in several species but not in human, where duplicated genes encode highly connected proteins. To understand when and how gene duplicability changed in evolution, we compare gene and network properties in four species (Escherichia coli, yeast, fly, and human that are representative of the increase in evolutionary complexity, defined as progressive growth in the number of genes, cells, and cell types. We find that the origin and conservation of a gene significantly correlates with the properties of the encoded protein in the protein-protein interaction network. All four species preserve a core of singleton and central hubs that originated early in evolution, are highly conserved, and accomplish basic biological functions. Another group of hubs appeared in metazoans and duplicated in vertebrates, mostly through vertebrate-specific whole genome duplication. Such recent and duplicated hubs are frequently targets of microRNAs and show tissue-selective expression, suggesting that these are alternative mechanisms to control their dosage. Our study shows how networks modified during evolution and contributes to explaining the occurrence of somatic genetic diseases, such as cancer, in terms of network perturbations.

  3. AtPID: the overall hierarchical functional protein interaction network interface and analytic platform for Arabidopsis.

    Science.gov (United States)

    Li, Peng; Zang, Weidong; Li, Yuhua; Xu, Feng; Wang, Jigang; Shi, Tieliu

    2011-01-01

    Protein interactions are involved in important cellular functions and biological processes that are the fundamentals of all life activities. With improvements in experimental techniques and progress in research, the overall protein interaction network frameworks of several model organisms have been created through data collection and integration. However, most of the networks processed only show simple relationships without boundary, weight or direction, which do not truly reflect the biological reality. In vivo, different types of protein interactions, such as the assembly of protein complexes or phosphorylation, often have their specific functions and qualifications. Ignorance of these features will bring much bias to the network analysis and application. Therefore, we annotate the Arabidopsis proteins in the AtPID database with further information (e.g. functional annotation, subcellular localization, tissue-specific expression, phosphorylation information, SNP phenotype and mutant phenotype, etc.) and interaction qualifications (e.g. transcriptional regulation, complex assembly, functional collaboration, etc.) via further literature text mining and integration of other resources. Meanwhile, the related information is vividly displayed to users through a comprehensive and newly developed display and analytical tools. The system allows the construction of tissue-specific interaction networks with display of canonical pathways. The latest updated AtPID database is available at http://www.megabionet.org/atpid/.

  4. HPIminer: A text mining system for building and visualizing human protein interaction networks and pathways.

    Science.gov (United States)

    Subramani, Suresh; Kalpana, Raja; Monickaraj, Pankaj Moses; Natarajan, Jeyakumar

    2015-04-01

    The knowledge on protein-protein interactions (PPI) and their related pathways are equally important to understand the biological functions of the living cell. Such information on human proteins is highly desirable to understand the mechanism of several diseases such as cancer, diabetes, and Alzheimer's disease. Because much of that information is buried in biomedical literature, an automated text mining system for visualizing human PPI and pathways is highly desirable. In this paper, we present HPIminer, a text mining system for visualizing human protein interactions and pathways from biomedical literature. HPIminer extracts human PPI information and PPI pairs from biomedical literature, and visualize their associated interactions, networks and pathways using two curated databases HPRD and KEGG. To our knowledge, HPIminer is the first system to build interaction networks from literature as well as curated databases. Further, the new interactions mined only from literature and not reported earlier in databases are highlighted as new. A comparative study with other similar tools shows that the resultant network is more informative and provides additional information on interacting proteins and their associated networks. Copyright © 2015 Elsevier Inc. All rights reserved.

  5. Coevolution analysis of Hepatitis C virus genome to identify the structural and functional dependency network of viral proteins

    Science.gov (United States)

    Champeimont, Raphaël; Laine, Elodie; Hu, Shuang-Wei; Penin, Francois; Carbone, Alessandra

    2016-05-01

    A novel computational approach of coevolution analysis allowed us to reconstruct the protein-protein interaction network of the Hepatitis C Virus (HCV) at the residue resolution. For the first time, coevolution analysis of an entire viral genome was realized, based on a limited set of protein sequences with high sequence identity within genotypes. The identified coevolving residues constitute highly relevant predictions of protein-protein interactions for further experimental identification of HCV protein complexes. The method can be used to analyse other viral genomes and to predict the associated protein interaction networks.

  6. Do natural proteins differ from random sequences polypeptides? Natural vs. random proteins classification using an evolutionary neural network.

    Directory of Open Access Journals (Sweden)

    Davide De Lucrezia

    Full Text Available Are extant proteins the exquisite result of natural selection or are they random sequences slightly edited by evolution? This question has puzzled biochemists for long time and several groups have addressed this issue comparing natural protein sequences to completely random ones coming to contradicting conclusions. Previous works in literature focused on the analysis of primary structure in an attempt to identify possible signature of evolutionary editing. Conversely, in this work we compare a set of 762 natural proteins with an average length of 70 amino acids and an equal number of completely random ones of comparable length on the basis of their structural features. We use an ad hoc Evolutionary Neural Network Algorithm (ENNA in order to assess whether and to what extent natural proteins are edited from random polypeptides employing 11 different structure-related variables (i.e. net charge, volume, surface area, coil, alpha helix, beta sheet, percentage of coil, percentage of alpha helix, percentage of beta sheet, percentage of secondary structure and surface hydrophobicity. The ENNA algorithm is capable to correctly distinguish natural proteins from random ones with an accuracy of 94.36%. Furthermore, we study the structural features of 32 random polypeptides misclassified as natural ones to unveil any structural similarity to natural proteins. Results show that random proteins misclassified by the ENNA algorithm exhibit a significant fold similarity to portions or subdomains of extant proteins at atomic resolution. Altogether, our results suggest that natural proteins are significantly edited from random polypeptides and evolutionary editing can be readily detected analyzing structural features. Furthermore, we also show that the ENNA, employing simple structural descriptors, can predict whether a protein chain is natural or random.

  7. Supervised maximum-likelihood weighting of composite protein networks for complex prediction

    Directory of Open Access Journals (Sweden)

    Yong Chern Han

    2012-12-01

    Full Text Available Abstract Background Protein complexes participate in many important cellular functions, so finding the set of existent complexes is essential for understanding the organization and regulation of processes in the cell. With the availability of large amounts of high-throughput protein-protein interaction (PPI data, many algorithms have been proposed to discover protein complexes from PPI networks. However, such approaches are hindered by the high rate of noise in high-throughput PPI data, including spurious and missing interactions. Furthermore, many transient interactions are detected between proteins that are not from the same complex, while not all proteins from the same complex may actually interact. As a result, predicted complexes often do not match true complexes well, and many true complexes go undetected. Results We address these challenges by integrating PPI data with other heterogeneous data sources to construct a composite protein network, and using a supervised maximum-likelihood approach to weight each edge based on its posterior probability of belonging to a complex. We then use six different clustering algorithms, and an aggregative clustering strategy, to discover complexes in the weighted network. We test our method on Saccharomyces cerevisiae and Homo sapiens, and show that complex discovery is improved: compared to previously proposed supervised and unsupervised weighting approaches, our method recalls more known complexes, achieves higher precision at all recall levels, and generates novel complexes of greater functional similarity. Furthermore, our maximum-likelihood approach allows learned parameters to be used to visualize and evaluate the evidence of novel predictions, aiding human judgment of their credibility. Conclusions Our approach integrates multiple data sources with supervised learning to create a weighted composite protein network, and uses six clustering algorithms with an aggregative clustering strategy to

  8. A multilayer protein-protein interaction network analysis of different life stages in Caenorhabditis elegans

    Science.gov (United States)

    Shinde, Pramod; Jalan, Sarika

    2015-12-01

    Molecular networks act as the backbone of cellular activities, providing an excellent opportunity to understand the developmental changes in an organism. While network data usually constitute only stationary network graphs, constructing a multilayer PPI network may provide clues to the particular developmental role at each stage of life and may unravel the importance of these developmental changes. The developmental biology model of Caenorhabditis elegans analyzed here provides a ripe platform to understand the patterns of evolution during the life stages of an organism. In the present study, the widely studied network properties exhibit overall similar statistics for all the PPI layers. Further, the analysis of the degree-degree correlation and spectral properties not only reveals crucial differences in each PPI layer but also indicates the presence of the varying complexity among them. The PPI layer of the nematode life stage exhibits various network properties different to the rest of the PPI layers, indicating the specific role of cellular diversity and developmental transitions at this stage. The framework presented here provides a direction to explore and understand the developmental changes occurring in the different life stages of an organism.

  9. The Oncogenic Palmitoyi-Protein Network in Prostate Cancer

    Science.gov (United States)

    2015-06-01

    SILAC amino acids in parallel. One group of control cells were cultured in “light” medium containing natural lysine (Lys0) and arginine (Arg0), DHHC3...knockdown cells were cultured in “heavy” medium containing 13C6,15N2- lysine (Lys8) and 13C6,15N4- arginine (Arg10), and the other group of control...cells were cultured in “medium” medium containing 4,4,5,5-D4- lysine (Lys4) and 13C6- arginine (Arg6). After six doublings, when cellular proteins were

  10. Stepping motor adaptor actuator for a commercial uhv linear motion feedthrough

    International Nuclear Information System (INIS)

    Iarocci, M.; Oversluizen, T.

    1989-01-01

    An adaptor coupling has been developed that will allow the attachment of a standard stepping motor to a precision commercial (Varian) uhv linear motion feedthrough. The assembly, consisting of the motor, motor adaptor, limit switches, etc. is clamped to the feedthrough body which can be done under vacuum conditions if necessary. With a 500 step/rev. stepping motor the resolution is 1.27 μm per step. We presently use this assembly in a remote location for the precise positioning of a beam sensing monitor. 2 refs., 3 figs

  11. Salt-bridge networks within globular and disordered proteins: characterizing trends for designable interactions.

    Science.gov (United States)

    Basu, Sankar; Mukharjee, Debasish

    2017-07-01

    There has been considerable debate about the contribution of salt bridges to the stabilization of protein folds, in spite of their participation in crucial protein functions. Salt bridges appear to contribute to the activity-stability trade-off within proteins by bringing high-entropy charged amino acids into close contacts during the course of their functions. The current study analyzes the modes of association of salt bridges (in terms of networks) within globular proteins and at protein-protein interfaces. While the most common and trivial type of salt bridge is the isolated salt bridge, bifurcated salt bridge appears to be a distinct salt-bridge motif having a special topology and geometry. Bifurcated salt bridges are found ubiquitously in proteins and interprotein complexes. Interesting and attractive examples presenting different modes of interaction are highlighted. Bifurcated salt bridges appear to function as molecular clips that are used to stitch together large surface contours at interacting protein interfaces. The present work also emphasizes the key role of salt-bridge-mediated interactions in the partial folding of proteins containing long stretches of disordered regions. Salt-bridge-mediated interactions seem to be pivotal to the promotion of "disorder-to-order" transitions in small disordered protein fragments and their stabilization upon binding. The results obtained in this work should help to guide efforts to elucidate the modus operandi of these partially disordered proteins, and to conceptualize how these proteins manage to maintain the required amount of disorder even in their bound forms. This work could also potentially facilitate explorations of geometrically specific designable salt bridges through the characterization of composite salt-bridge networks. Graphical abstract ᅟ.

  12. Integration of relational and hierarchical network information for protein function prediction

    Directory of Open Access Journals (Sweden)

    Jiang Xiaoyu

    2008-08-01

    Full Text Available Abstract Background In the current climate of high-throughput computational biology, the inference of a protein's function from related measurements, such as protein-protein interaction relations, has become a canonical task. Most existing technologies pursue this task as a classification problem, on a term-by-term basis, for each term in a database, such as the Gene Ontology (GO database, a popular rigorous vocabulary for biological functions. However, ontology structures are essentially hierarchies, with certain top to bottom annotation rules which protein function predictions should in principle follow. Currently, the most common approach to imposing these hierarchical constraints on network-based classifiers is through the use of transitive closure to predictions. Results We propose a probabilistic framework to integrate information in relational data, in the form of a protein-protein interaction network, and a hierarchically structured database of terms, in the form of the GO database, for the purpose of protein function prediction. At the heart of our framework is a factorization of local neighborhood information in the protein-protein interaction network across successive ancestral terms in the GO hierarchy. We introduce a classifier within this framework, with computationally efficient implementation, that produces GO-term predictions that naturally obey a hierarchical 'true-path' consistency from root to leaves, without the need for further post-processing. Conclusion A cross-validation study, using data from the yeast Saccharomyces cerevisiae, shows our method offers substantial improvements over both standard 'guilt-by-association' (i.e., Nearest-Neighbor and more refined Markov random field methods, whether in their original form or when post-processed to artificially impose 'true-path' consistency. Further analysis of the results indicates that these improvements are associated with increased predictive capabilities (i.e., increased

  13. SLIDER: A Generic Metaheuristic for the Discovery of Correlated Motifs in Protein-Protein Interaction Networks

    NARCIS (Netherlands)

    Boyen, P.; Dyck, van D.; Neven, F.; Ham, van R.C.H.J.; Dijk, van A.D.J.

    2011-01-01

    Correlated motif mining (CMM) is the problem of finding overrepresented pairs of patterns, called motifs, in sequences of interacting proteins. Algorithmic solutions for CMM thereby provide a computational method for predicting binding sites for protein interaction. In this paper, we adopt a

  14. Genetic Deletion of the Clathrin Adaptor GGA3 Reduces Anxiety and Alters GABAergic Transmission.

    Directory of Open Access Journals (Sweden)

    Kendall R Walker

    Full Text Available Golgi-localized γ-ear-containing ARF binding protein 3 (GGA3 is a monomeric clathrin adaptor that has been shown to regulate the trafficking of the Beta-site APP-cleaving enzyme (BACE1, which is required for production of the Alzheimer's disease (AD-associated amyloid βpeptide. Our previous studies have shown that BACE1 is degraded via the lysosomal pathway and that depletion of GGA3 results in increased BACE1 levels and activity owing to impaired lysosomal trafficking and degradation. We further demonstrated the role of GGA3 in the regulation of BACE1 in vivo by showing that BACE1 levels are increased in the brain of GGA3 null mice. We report here that GGA3 deletion results in novelty-induced hyperactivity and decreased anxiety-like behaviors. Given the pivotal role of GABAergic transmission in the regulation of anxiety-like behaviors, we performed electrophysiological recordings in hippocampal slices and found increased phasic and decreased tonic inhibition in the dentate gyrus granule cells (DGGC. Moreover, we found that the number of inhibitory synapses is increased in the dentate gyrus of GGA3 null mice in further support of the electrophysiological data. Thus, the increased GABAergic transmission is a leading candidate mechanism underlying the reduced anxiety-like behaviors observed in GGA3 null mice. All together these findings suggest that GGA3 plays a key role in GABAergic transmission. Since BACE1 levels are elevated in the brain of GGA3 null mice, it is possible that at least some of these phenotypes are a consequence of increased processing of BACE1 substrates.

  15. Genetic Deletion of the Clathrin Adaptor GGA3 Reduces Anxiety and Alters GABAergic Transmission.

    Science.gov (United States)

    Walker, Kendall R; Modgil, Amit; Albrecht, David; Lomoio, Selene; Haydon, Philip G; Moss, Stephen J; Tesco, Giuseppina

    2016-01-01

    Golgi-localized γ-ear-containing ARF binding protein 3 (GGA3) is a monomeric clathrin adaptor that has been shown to regulate the trafficking of the Beta-site APP-cleaving enzyme (BACE1), which is required for production of the Alzheimer's disease (AD)-associated amyloid βpeptide. Our previous studies have shown that BACE1 is degraded via the lysosomal pathway and that depletion of GGA3 results in increased BACE1 levels and activity owing to impaired lysosomal trafficking and degradation. We further demonstrated the role of GGA3 in the regulation of BACE1 in vivo by showing that BACE1 levels are increased in the brain of GGA3 null mice. We report here that GGA3 deletion results in novelty-induced hyperactivity and decreased anxiety-like behaviors. Given the pivotal role of GABAergic transmission in the regulation of anxiety-like behaviors, we performed electrophysiological recordings in hippocampal slices and found increased phasic and decreased tonic inhibition in the dentate gyrus granule cells (DGGC). Moreover, we found that the number of inhibitory synapses is increased in the dentate gyrus of GGA3 null mice in further support of the electrophysiological data. Thus, the increased GABAergic transmission is a leading candidate mechanism underlying the reduced anxiety-like behaviors observed in GGA3 null mice. All together these findings suggest that GGA3 plays a key role in GABAergic transmission. Since BACE1 levels are elevated in the brain of GGA3 null mice, it is possible that at least some of these phenotypes are a consequence of increased processing of BACE1 substrates.

  16. Global Alignment of Pairwise Protein Interaction Networks for Maximal Common Conserved Patterns

    Directory of Open Access Journals (Sweden)

    Wenhong Tian

    2013-01-01

    Full Text Available A number of tools for the alignment of protein-protein interaction (PPI networks have laid the foundation for PPI network analysis. Most of alignment tools focus on finding conserved interaction regions across the PPI networks through either local or global mapping of similar sequences. Researchers are still trying to improve the speed, scalability, and accuracy of network alignment. In view of this, we introduce a connected-components based fast algorithm, HopeMap, for network alignment. Observing that the size of true orthologs across species is small comparing to the total number of proteins in all species, we take a different approach based on a precompiled list of homologs identified by KO terms. Applying this approach to S. cerevisiae (yeast and D. melanogaster (fly, E. coli K12 and S. typhimurium, E. coli K12 and C. crescenttus, we analyze all clusters identified in the alignment. The results are evaluated through up-to-date known gene annotations, gene ontology (GO, and KEGG ortholog groups (KO. Comparing to existing tools, our approach is fast with linear computational cost, highly accurate in terms of KO and GO terms specificity and sensitivity, and can be extended to multiple alignments easily.

  17. Predicting adverse drug reaction profiles by integrating protein interaction networks with drug structures.

    Science.gov (United States)

    Huang, Liang-Chin; Wu, Xiaogang; Chen, Jake Y

    2013-01-01

    The prediction of adverse drug reactions (ADRs) has become increasingly important, due to the rising concern on serious ADRs that can cause drugs to fail to reach or stay in the market. We proposed a framework for predicting ADR profiles by integrating protein-protein interaction (PPI) networks with drug structures. We compared ADR prediction performances over 18 ADR categories through four feature groups-only drug targets, drug targets with PPI networks, drug structures, and drug targets with PPI networks plus drug structures. The results showed that the integration of PPI networks and drug structures can significantly improve the ADR prediction performance. The median AUC values for the four groups were 0.59, 0.61, 0.65, and 0.70. We used the protein features in the best two models, "Cardiac disorders" (median-AUC: 0.82) and "Psychiatric disorders" (median-AUC: 0.76), to build ADR-specific PPI networks with literature supports. For validation, we examined 30 drugs withdrawn from the U.S. market to see if our approach can predict their ADR profiles and explain why they were withdrawn. Except for three drugs having ADRs in the categories we did not predict, 25 out of 27 withdrawn drugs (92.6%) having severe ADRs were successfully predicted by our approach. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  18. 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.

  19. The effect of oil type on network formation by protein aggregates into oleogels

    NARCIS (Netherlands)

    Vries, de Auke; Lopez Gomez, Yuly; Linden, van der Erik; Scholten, Elke

    2017-01-01

    The aim of this study was to assess the effect of oil type on the network formation of heat-set protein aggregates in liquid oil. The gelling properties of such aggregates to structure oil into so-called ‘oleogels’ are related to both the particle-particle and particle-solvent interactions. To

  20. Salivary Defense Proteins: Their Network and Role in Innate and Acquired Oral Immunity

    Directory of Open Access Journals (Sweden)

    Gábor Fábián

    2012-04-01

    Full Text Available There are numerous defense proteins present in the saliva. Although some of these molecules are present in rather low concentrations, their effects are additive and/or synergistic, resulting in an efficient molecular defense network of the oral cavity. Moreover, local concentrations of these proteins near the mucosal surfaces (mucosal transudate, periodontal sulcus (gingival crevicular fluid and oral wounds and ulcers (transudate may be much greater, and in many cases reinforced by immune and/or inflammatory reactions of the oral mucosa. Some defense proteins, like salivary immunoglobulins and salivary chaperokine HSP70/HSPAs (70 kDa heat shock proteins, are involved in both innate and acquired immunity. Cationic peptides and other defense proteins like lysozyme, bactericidal/permeability increasing protein (BPI, BPI-like proteins, PLUNC (palate lung and nasal epithelial clone proteins, salivary amylase, cystatins, prolin-rich proteins, mucins, peroxidases, statherin and others are primarily responsible for innate immunity. In this paper, this complex system and function of the salivary defense proteins will be reviewed.

  1. A topology-constrained distance network algorithm for protein structure determination from NOESY data.

    Science.gov (United States)

    Huang, Yuanpeng Janet; Tejero, Roberto; Powers, Robert; Montelione, Gaetano T

    2006-03-15

    This article formulates the multidimensional nuclear Overhauser effect spectroscopy (NOESY) interpretation problem using graph theory and presents a novel, bottom-up, topology-constrained distance network analysis algorithm for NOESY cross peak interpretation using assigned resonances. AutoStructure is a software suite that implements this topology-constrained distance network analysis algorithm and iteratively generates structures using the three-dimensional (3D) protein structure calculation programs XPLOR/CNS or DYANA. The minimum input for AutoStructure includes the amino acid sequence, a list of resonance assignments, and lists of 2D, 3D, and/or 4D-NOESY cross peaks. AutoStructure can also analyze homodimeric proteins when X-filtered NOESY experiments are available. The quality of input data and final 3D structures is evaluated using recall, precision, and F-measure (RPF) scores, a statistical measure of goodness of fit with the input data. AutoStructure has been tested on three protein NMR data sets for which high-quality structures have previously been solved by an expert, and yields comparable high-quality distance constraint lists and 3D protein structures in hours. We also compare several protein structures determined using AutoStructure with corresponding homologous proteins determined with other independent methods. The program has been used in more than two dozen protein structure determinations, several of which have already been published. (c) 2005 Wiley-Liss, Inc.

  2. The STRING database in 2017: quality-controlled protein-protein association networks, made broadly accessible.

    Science.gov (United States)

    Szklarczyk, Damian; Morris, John H; Cook, Helen; Kuhn, Michael; Wyder, Stefan; Simonovic, Milan; Santos, Alberto; Doncheva, Nadezhda T; Roth, Alexander; Bork, Peer; Jensen, Lars J; von Mering, Christian

    2017-01-04

    A system-wide understanding of cellular function requires knowledge of all functional interactions between the expressed proteins. The STRING database aims to collect and integrate this information, by consolidating known and predicted protein-protein association data for a large number of organisms. The associations in STRING include direct (physical) interactions, as well as indirect (functional) interactions, as long as both are specific and biologically meaningful. Apart from collecting and reassessing available experimental data on protein-protein interactions, and importing known pathways and protein complexes from curated databases, interaction predictions are derived from the following sources: (i) systematic co-expression analysis, (ii) detection of shared selective signals across genomes, (iii) automated text-mining of the scientific literature and (iv) computational transfer of interaction knowledge between organisms based on gene orthology. In the latest version 10.5 of STRING, the biggest changes are concerned with data dissemination: the web frontend has been completely redesigned to reduce dependency on outdated browser technologies, and the database can now also be queried from inside the popular Cytoscape software framework. Further improvements include automated background analysis of user inputs for functional enrichments, and streamlined download options. The STRING resource is available online, at http://string-db.org/. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

  3. Isotachophoresis of proteins in a networked microfluidic chip: experiment and 2-D simulation.

    Science.gov (United States)

    Cui, Huanchun; Dutta, Prashanta; Ivory, Cornelius F

    2007-04-01

    This paper reports both the experimental application and 2-D simulation of ITP of proteins in a networked microfluidic chip. Experiments demonstrate that a mixture of three fluorescent proteins can be concentrated and stacked into adjacent zones of pure protein under a constant voltage of 100 V over a 2 cm long microchannel. Measurements of the isotachophoretic velocity of the moving zones demonstrates that, during ITP under a constant voltage, the zone velocity decreases as more of the channel is occupied by the terminating electrolyte. A 2-D ITP model based on the Nernst-Planck equations illustrates the stacking and separation features of ITP using simulations of three virtual proteins. The self-sharpening behavior of ITP zones dispersed by a T-junction is clearly demonstrated both by experiment and by simulation. Comparison of 2-D simulations of ITP and zone electrophoresis (ZE) confirms that ZE lacks the ability to resharpen protein zones after they pass through a T-junction.

  4. Transport Vesicle Tethering at the Trans Golgi Network: Coiled Coil Proteins in Action.

    Science.gov (United States)

    Cheung, Pak-Yan P; Pfeffer, Suzanne R

    2016-01-01

    The Golgi complex is decorated with so-called Golgin proteins that share a common feature: a large proportion of their amino acid sequences are predicted to form coiled-coil structures. The possible presence of extensive coiled coils implies that these proteins are highly elongated molecules that can extend a significant distance from the Golgi surface. This property would help them to capture or trap inbound transport vesicles and to tether Golgi mini-stacks together. This review will summarize our current understanding of coiled coil tethers that are needed for the receipt of transport vesicles at the trans Golgi network (TGN). How do long tethering proteins actually catch vesicles? Golgi-associated, coiled coil tethers contain numerous binding sites for small GTPases, SNARE proteins, and vesicle coat proteins. How are these interactions coordinated and are any or all of them important for the tethering process? Progress toward understanding these questions and remaining, unresolved mysteries will be discussed.

  5. Generating functional analysis of complex formation and dissociation in large protein interaction networks

    International Nuclear Information System (INIS)

    Coolen, A C C; Rabello, S

    2009-01-01

    We analyze large systems of interacting proteins, using techniques from the non-equilibrium statistical mechanics of disordered many-particle systems. Apart from protein production and removal, the most relevant microscopic processes in the proteome are complex formation and dissociation, and the microscopic degrees of freedom are the evolving concentrations of unbound proteins (in multiple post-translational states) and of protein complexes. Here we only include dimer-complexes, for mathematical simplicity, and we draw the network that describes which proteins are reaction partners from an ensemble of random graphs with an arbitrary degree distribution. We show how generating functional analysis methods can be used successfully to derive closed equations for dynamical order parameters, representing an exact macroscopic description of the complex formation and dissociation dynamics in the infinite system limit. We end this paper with a discussion of the possible routes towards solving the nontrivial order parameter equations, either exactly (in specific limits) or approximately.

  6. Maximum flow approach to prioritize potential drug targets of Mycobacterium tuberculosis H37Rv from protein-protein interaction network.

    Science.gov (United States)

    Melak, Tilahun; Gakkhar, Sunita

    2015-12-01

    In spite of the implementations of several strategies, tuberculosis (TB) is overwhelmingly a serious global public health problem causing millions of infections and deaths every year. This is mainly due to the emergence of drug-resistance varieties of TB. The current treatment strategies for the drug-resistance TB are of longer duration, more expensive and have side effects. This highlights the importance of identification and prioritization of targets for new drugs. This study has been carried out to prioritize potential drug targets of Mycobacterium tuberculosis H37Rv based on their flow to resistance genes. The weighted proteome interaction network of the pathogen was constructed using a dataset from STRING database. Only a subset of the dataset with interactions that have a combined score value ≥770 was considered. Maximum flow approach has been used to prioritize potential drug targets. The potential drug targets were obtained through comparative genome and network centrality analysis. The curated set of resistance genes was retrieved from literatures. Detail literature review and additional assessment of the method were also carried out for validation. A list of 537 proteins which are essential to the pathogen and non-homologous with human was obtained from the comparative genome analysis. Through network centrality measures, 131 of them were found within the close neighborhood of the centre of gravity of the proteome network. These proteins were further prioritized based on their maximum flow value to resistance genes and they are proposed as reliable drug targets of the pathogen. Proteins which interact with the host were also identified in order to understand the infection mechanism. Potential drug targets of Mycobacterium tuberculosis H37Rv were successfully prioritized based on their flow to resistance genes of existing drugs which is believed to increase the druggability of the targets since inhibition of a protein that has a maximum flow to

  7. 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

  8. The G protein-coupled receptor heterodimer network (GPCR-HetNet) and its hub components.

    Science.gov (United States)

    Borroto-Escuela, Dasiel O; Brito, Ismel; Romero-Fernandez, Wilber; Di Palma, Michael; Oflijan, Julia; Skieterska, Kamila; Duchou, Jolien; Van Craenenbroeck, Kathleen; Suárez-Boomgaard, Diana; Rivera, Alicia; Guidolin, Diego; Agnati, Luigi F; Fuxe, Kjell

    2014-05-14

    G protein-coupled receptors (GPCRs) oligomerization has emerged as a vital characteristic of receptor structure. Substantial experimental evidence supports the existence of GPCR-GPCR interactions in a coordinated and cooperative manner. However, despite the current development of experimental techniques for large-scale detection of GPCR heteromers, in order to understand their connectivity it is necessary to develop novel tools to study the global heteroreceptor networks. To provide insight into the overall topology of the GPCR heteromers and identify key players, a collective interaction network was constructed. Experimental interaction data for each of the individual human GPCR protomers was obtained manually from the STRING and SCOPUS databases. The interaction data were used to build and analyze the network using Cytoscape software. The network was treated as undirected throughout the study. It is comprised of 156 nodes, 260 edges and has a scale-free topology. Connectivity analysis reveals a significant dominance of intrafamily versus interfamily connections. Most of the receptors within the network are linked to each other by a small number of edges. DRD2, OPRM, ADRB2, AA2AR, AA1R, OPRK, OPRD and GHSR are identified as hubs. In a network representation 10 modules/clusters also appear as a highly interconnected group of nodes. Information on this GPCR network can improve our understanding of molecular integration. GPCR-HetNet has been implemented in Java and is freely available at http://www.iiia.csic.es/~ismel/GPCR-Nets/index.html.

  9. IsoBase: a database of functionally related proteins across PPI networks.

    Science.gov (United States)

    Park, Daniel; Singh, Rohit; Baym, Michael; Liao, Chung-Shou; Berger, Bonnie

    2011-01-01

    We describe IsoBase, a database identifying functionally related proteins, across five major eukaryotic model organisms: Saccharomyces cerevisiae, Drosophila melanogaster, Caenorhabditis elegans, Mus musculus and Homo Sapiens. Nearly all existing algorithms for orthology detection are based on sequence comparison. Although these have been successful in orthology prediction to some extent, we seek to go beyond these methods by the integration of sequence data and protein-protein interaction (PPI) networks to help in identifying true functionally related proteins. With that motivation, we introduce IsoBase, the first publicly available ortholog database that focuses on functionally related proteins. The groupings were computed using the IsoRankN algorithm that uses spectral methods to combine sequence and PPI data and produce clusters of functionally related proteins. These clusters compare favorably with those from existing approaches: proteins within an IsoBase cluster are more likely to share similar Gene Ontology (GO) annotation. A total of 48,120 proteins were clustered into 12,693 functionally related groups. The IsoBase database may be browsed for functionally related proteins across two or more species and may also be queried by accession numbers, species-specific identifiers, gene name or keyword. The database is freely available for download at http://isobase.csail.mit.edu/.

  10. Improving protein disorder prediction by deep bidirectional long short-term memory recurrent neural networks.

    Science.gov (United States)

    Hanson, Jack; Yang, Yuedong; Paliwal, Kuldip; Zhou, Yaoqi

    2017-03-01

    Capturing long-range interactions between structural but not sequence neighbors of proteins is a long-standing challenging problem in bioinformatics. Recently, long short-term memory (LSTM) networks have significantly improved the accuracy of speech and image classification problems by remembering useful past information in long sequential events. Here, we have implemented deep bidirectional LSTM recurrent neural networks in the problem of protein intrinsic disorder prediction. The new method, named SPOT-Disorder, has steadily improved over a similar method using a traditional, window-based neural network (SPINE-D) in all datasets tested without separate training on short and long disordered regions. Independent tests on four other datasets including the datasets from critical assessment of structure prediction (CASP) techniques and >10 000 annotated proteins from MobiDB, confirmed SPOT-Disorder as one of the best methods in disorder prediction. Moreover, initial studies indicate that the method is more accurate in predicting functional sites in disordered regions. These results highlight the usefulness combining LSTM with deep bidirectional recurrent neural networks in capturing non-local, long-range interactions for bioinformatics applications. SPOT-disorder is available as a web server and as a standalone program at: http://sparks-lab.org/server/SPOT-disorder/index.php . j.hanson@griffith.edu.au or yuedong.yang@griffith.edu.au or yaoqi.zhou@griffith.edu.au. Supplementary data is available at Bioinformatics online.

  11. The Prediction of Key Cytoskeleton Components Involved in Glomerular Diseases Based on a Protein-Protein Interaction Network

    Science.gov (United States)

    Ju, Wenjun; Li, Xuejuan; Li, Shao; Ding, Jie

    2016-01-01

    Maintenance of the physiological morphologies of different types of cells and tissues is essential for the normal functioning of each system in the human body. Dynamic variations in cell and tissue morphologies depend on accurate adjustments of the cytoskeletal system. The cytoskeletal system in the glomerulus plays a key role in the normal process of kidney filtration. To enhance the understanding of the possible roles of the cytoskeleton in glomerular diseases, we constructed the Glomerular Cytoskeleton Network (GCNet), which shows the protein-protein interaction network in the glomerulus, and identified several possible key cytoskeletal components involved in glomerular diseases. In this study, genes/proteins annotated to the cytoskeleton were detected by Gene Ontology analysis, and glomerulus-enriched genes were selected from nine available glomerular expression datasets. Then, the GCNet was generated by combining these two sets of information. To predict the possible key cytoskeleton components in glomerular diseases, we then examined the common regulation of the genes in GCNet in the context of five glomerular diseases based on their transcriptomic data. As a result, twenty-one cytoskeleton components as potential candidate were highlighted for consistently down- or up-regulating in all five glomerular diseases. And then, these candidates were examined in relation to existing known glomerular diseases and genes to determine their possible functions and interactions. In addition, the mRNA levels of these candidates were also validated in a puromycin aminonucleoside(PAN) induced rat nephropathy model and were also matched with existing Diabetic Nephropathy (DN) transcriptomic data. As a result, there are 15 of 21 candidates in PAN induced nephropathy model were consistent with our predication and also 12 of 21 candidates were matched with differentially expressed genes in the DN transcriptomic data. By providing a novel interaction network and prediction, GCNet

  12. The Prediction of Key Cytoskeleton Components Involved in Glomerular Diseases Based on a Protein-Protein Interaction Network.

    Science.gov (United States)

    Ding, Fangrui; Tan, Aidi; Ju, Wenjun; Li, Xuejuan; Li, Shao; Ding, Jie

    2016-01-01

    Maintenance of the physiological morphologies of different types of cells and tissues is essential for the normal functioning of each system in the human body. Dynamic variations in cell and tissue morphologies depend on accurate adjustments of the cytoskeletal system. The cytoskeletal system in the glomerulus plays a key role in the normal process of kidney filtration. To enhance the understanding of the possible roles of the cytoskeleton in glomerular diseases, we constructed the Glomerular Cytoskeleton Network (GCNet), which shows the protein-protein interaction network in the glomerulus, and identified several possible key cytoskeletal components involved in glomerular diseases. In this study, genes/proteins annotated to the cytoskeleton were detected by Gene Ontology analysis, and glomerulus-enriched genes were selected from nine available glomerular expression datasets. Then, the GCNet was generated by combining these two sets of information. To predict the possible key cytoskeleton components in glomerular diseases, we then examined the common regulation of the genes in GCNet in the context of five glomerular diseases based on their transcriptomic data. As a result, twenty-one cytoskeleton components as potential candidate were highlighted for consistently down- or up-regulating in all five glomerular diseases. And then, these candidates were examined in relation to existing known glomerular diseases and genes to determine their possible functions and interactions. In addition, the mRNA levels of these candidates were also validated in a puromycin aminonucleoside(PAN) induced rat nephropathy model and were also matched with existing Diabetic Nephropathy (DN) transcriptomic data. As a result, there are 15 of 21 candidates in PAN induced nephropathy model were consistent with our predication and also 12 of 21 candidates were matched with differentially expressed genes in the DN transcriptomic data. By providing a novel interaction network and prediction, GCNet

  13. Protein network analysis - A new approach for quantifying wheat dough microstructure.

    Science.gov (United States)

    Bernklau, Isabelle; Lucas, Lars; Jekle, Mario; Becker, Thomas

    2016-11-01

    Clarification of wheat dough functionalities by visualizing the protein microstructure demands a precise image analysis, which is still challenging. Thus, a novel method for quantifying dough microstructure called protein network analysis (PNA) was established in this study. Hereby, absolute morphological attributes such as junctions' density, branching rate, end-point rate, and lacunarity quantify and characterize the strength of a network. The method was validated in a large range of varying microstructural shapes by increasing the bulk water concentration. In addition, the effect of two different magnifications (objectives with various numerical apparatus) was studied. Resulting values of the branching rate showed a significant linear decrease (R 2 =0.97) by ~40% for both magnifications indicating a decrease in connectivity and cohesion within the network. Rheological measurements, used as reference methods confirmed the loss of a network structure with increasing water addition (e.g. G* decreased by 89%). Additionally, significant correlations between both methods validated the innovative image analysis PNA. With this new approach of image analysis, effects of additives, varying dough ingredients or changing process conditions on gluten network - the most structure-relevant component in wheat dough - can be quantitatively identified, and targeted functionalities can be controlled. Copyright © 2016 Elsevier Ltd. All rights reserved.

  14. Increased signaling entropy in cancer requires the scale-free property of protein interaction networks

    Science.gov (United States)

    Teschendorff, Andrew E.; Banerji, Christopher R. S.; Severini, Simone; Kuehn, Reimer; Sollich, Peter

    2015-01-01

    One of the key characteristics of cancer cells is an increased phenotypic plasticity, driven by underlying genetic and epigenetic perturbations. However, at a systems-level it is unclear how these perturbations give rise to the observed increased plasticity. Elucidating such systems-level principles is key for an improved understanding of cancer. Recently, it has been shown that signaling entropy, an overall measure of signaling pathway promiscuity, and computable from integrating a sample's gene expression profile with a protein interaction network, correlates with phenotypic plasticity and is increased in cancer compared to normal tissue. Here we develop a computational framework for studying the effects of network perturbations on signaling entropy. We demonstrate that the increased signaling entropy of cancer is driven by two factors: (i) the scale-free (or near scale-free) topology of the interaction network, and (ii) a subtle positive correlation between differential gene expression and node connectivity. Indeed, we show that if protein interaction networks were random graphs, described by Poisson degree distributions, that cancer would generally not exhibit an increased signaling entropy. In summary, this work exposes a deep connection between cancer, signaling entropy and interaction network topology. PMID:25919796

  15. Protein functional properties prediction in sparsely-label PPI networks through regularized non-negative matrix factorization.

    Science.gov (United States)

    Wu, Qingyao; Wang, Zhenyu; Li, Chunshan; Ye, Yunming; Li, Yueping; Sun, Ning

    2015-01-01

    Predicting functional properties of proteins in protein-protein interaction (PPI) networks presents a challenging problem and has important implication in computational biology. Collective classification (CC) that utilizes both attribute features and relational information to jointly classify related proteins in PPI networks has been shown to be a powerful computational method for this problem setting. Enabling CC usually increases accuracy when given a fully-labeled PPI network with a large amount of labeled data. However, such labels can be difficult to obtain in many real-world PPI networks in which there are usually only a limited number of labeled proteins and there are a large amount of unlabeled proteins. In this case, most of the unlabeled proteins may not connected to the labeled ones, the supervision knowledge cannot be obtained effectively from local network connections. As a consequence, learning a CC model in sparsely-labeled PPI networks can lead to poor performance. We investigate a latent graph approach for finding an integration latent graph by exploiting various latent linkages and judiciously integrate the investigated linkages to link (separate) the proteins with similar (different) functions. We develop a regularized non-negative matrix factorization (RNMF) algorithm for CC to make protein functional properties prediction by utilizing various data sources that are available in this problem setting, including attribute features, latent graph, and unlabeled data information. In RNMF, a label matrix factorization term and a network regularization term are incorporated into the non-negative matrix factorization (NMF) objective function to seek a matrix factorization that respects the network structure and label information for classification prediction. Experimental results on KDD Cup tasks predicting the localization and functions of proteins to yeast genes demonstrate the effectiveness of the proposed RNMF method for predicting the protein

  16. A mathematical model for generating bipartite graphs and its application to protein networks

    International Nuclear Information System (INIS)

    Nacher, J C; Ochiai, T; Hayashida, M; Akutsu, T

    2009-01-01

    Complex systems arise in many different contexts from large communication systems and transportation infrastructures to molecular biology. Most of these systems can be organized into networks composed of nodes and interacting edges. Here, we present a theoretical model that constructs bipartite networks with the particular feature that the degree distribution can be tuned depending on the probability rate of fundamental processes. We then use this model to investigate protein-domain networks. A protein can be composed of up to hundreds of domains. Each domain represents a conserved sequence segment with specific functional tasks. We analyze the distribution of domains in Homo sapiens and Arabidopsis thaliana organisms and the statistical analysis shows that while (a) the number of domain types shared by k proteins exhibits a power-law distribution, (b) the number of proteins composed of k types of domains decays as an exponential distribution. The proposed mathematical model generates bipartite graphs and predicts the emergence of this mixing of (a) power-law and (b) exponential distributions. Our theoretical and computational results show that this model requires (1) growth process and (2) copy mechanism.

  17. A mathematical model for generating bipartite graphs and its application to protein networks

    Energy Technology Data Exchange (ETDEWEB)

    Nacher, J C [Department of Complex Systems, Future University-Hakodate (Japan); Ochiai, T [Faculty of Engineering, Toyama Prefectural University (Japan); Hayashida, M; Akutsu, T [Bioinformatics Center, Institute for Chemical Research, Kyoto University (Japan)

    2009-12-04

    Complex systems arise in many different contexts from large communication systems and transportation infrastructures to molecular biology. Most of these systems can be organized into networks composed of nodes and interacting edges. Here, we present a theoretical model that constructs bipartite networks with the particular feature that the degree distribution can be tuned depending on the probability rate of fundamental processes. We then use this model to investigate protein-domain networks. A protein can be composed of up to hundreds of domains. Each domain represents a conserved sequence segment with specific functional tasks. We analyze the distribution of domains in Homo sapiens and Arabidopsis thaliana organisms and the statistical analysis shows that while (a) the number of domain types shared by k proteins exhibits a power-law distribution, (b) the number of proteins composed of k types of domains decays as an exponential distribution. The proposed mathematical model generates bipartite graphs and predicts the emergence of this mixing of (a) power-law and (b) exponential distributions. Our theoretical and computational results show that this model requires (1) growth process and (2) copy mechanism.

  18. Distinct configurations of protein complexes and biochemical pathways revealed by epistatic interaction network motifs

    LENUS (Irish Health Repository)

    Casey, Fergal

    2011-08-22

    Abstract Background Gene and protein interactions are commonly represented as networks, with the genes or proteins comprising the nodes and the relationship between them as edges. Motifs, or small local configurations of edges and nodes that arise repeatedly, can be used to simplify the interpretation of networks. Results We examined triplet motifs in a network of quantitative epistatic genetic relationships, and found a non-random distribution of particular motif classes. Individual motif classes were found to be associated with different functional properties, suggestive of an underlying biological significance. These associations were apparent not only for motif classes, but for individual positions within the motifs. As expected, NNN (all negative) motifs were strongly associated with previously reported genetic (i.e. synthetic lethal) interactions, while PPP (all positive) motifs were associated with protein complexes. The two other motif classes (NNP: a positive interaction spanned by two negative interactions, and NPP: a negative spanned by two positives) showed very distinct functional associations, with physical interactions dominating for the former but alternative enrichments, typical of biochemical pathways, dominating for the latter. Conclusion We present a model showing how NNP motifs can be used to recognize supportive relationships between protein complexes, while NPP motifs often identify opposing or regulatory behaviour between a gene and an associated pathway. The ability to use motifs to point toward underlying biological organizational themes is likely to be increasingly important as more extensive epistasis mapping projects in higher organisms begin.

  19. EAT-2, a SAP-like adaptor, controls NK cell activation through phospholipase Cγ, Ca++, and Erk, leading to granule polarization.

    Science.gov (United States)

    Pérez-Quintero, Luis-Alberto; Roncagalli, Romain; Guo, Huaijian; Latour, Sylvain; Davidson, Dominique; Veillette, André

    2014-04-07

    Ewing's sarcoma-associated transcript 2 (EAT-2) is an Src homology 2 domain-containing intracellular adaptor related to signaling lymphocytic activation molecule (SLAM)-associated protein (SAP), the X-linked lymphoproliferative gene product. Both EAT-2 and SAP are expressed in natural killer (NK) cells, and their combined expression is essential for NK cells to kill abnormal hematopoietic cells. SAP mediates this function by coupling SLAM family receptors to the protein tyrosine kinase Fyn and the exchange factor Vav, thereby promoting conjugate formation between NK cells and target cells. We used a variety of genetic, biochemical, and imaging approaches to define the molecular and cellular mechanisms by which EAT-2 controls NK cell activation. We found that EAT-2 mediates its effects in NK cells by linking SLAM family receptors to phospholipase Cγ, calcium fluxes, and Erk kinase. These signals are triggered by one or two tyrosines located in the carboxyl-terminal tail of EAT-2 but not found in SAP. Unlike SAP, EAT-2 does not enhance conjugate formation. Rather, it accelerates polarization and exocytosis of cytotoxic granules toward hematopoietic target cells. Hence, EAT-2 promotes NK cell activation by molecular and cellular mechanisms distinct from those of SAP. These findings explain the cooperative and essential function of these two adaptors in NK cell activation.

  20. A novel conserved phosphotyrosine motif in the Drosophila fibroblast growth factor signaling adaptor Dof with a redundant role in signal transmission.

    Science.gov (United States)

    Csiszar, Agnes; Vogelsang, Elisabeth; Beug, Hartmut; Leptin, Maria

    2010-04-01

    The fibroblast growth factor receptor (FGFR) signals through adaptors constitutively associated with the receptor. In Drosophila melanogaster, the FGFR-specific adaptor protein Downstream-of-FGFR (Dof) becomes phosphorylated upon receptor activation at several tyrosine residues, one of which recruits Corkscrew (Csw), the Drosophila homolog of SHP2, which provides a molecular link to mitogen-activated protein kinase (MAPK) activation. However, the Csw pathway is not the only link from Dof to MAPK. In this study, we identify a novel phosphotyrosine motif present in four copies in Dof and also found in other insect and vertebrate signaling molecules. We show that these motifs are phosphorylated and contribute to FGF signal transduction. They constitute one of three sets of phosphotyrosines that act redundantly in signal transmission: (i) a Csw binding site, (ii) four consensus Grb2 recognition sites, and (iii) four novel tyrosine motifs. We show that Src64B binds to Dof and that Src kinases contribute to FGFR-dependent MAPK activation. Phosphorylation of the novel tyrosine motifs is required for the interaction of Dof with Src64B. Thus, Src64B recruitment to Dof through the novel phosphosites can provide a new link to MAPK activation and other cellular responses. This may give a molecular explanation for the involvement of Src kinases in FGF-dependent developmental events.

  1. Perturbed human sub-networks by Fusobacterium nucleatum candidate virulence proteins.

    Science.gov (United States)

    Zanzoni, Andreas; Spinelli, Lionel; Braham, Shérazade; Brun, Christine

    2017-08-10

    Fusobacterium nucleatum is a gram-negative anaerobic species residing in the oral cavity and implicated in several inflammatory processes in the human body. Although F. nucleatum abundance is increased in inflammatory bowel disease subjects and is prevalent in colorectal cancer patients, the causal role of the bacterium in gastrointestinal disorders and the mechanistic details of host cell functions subversion are not fully understood. We devised a computational strategy to identify putative secreted F. nucleatum proteins (FusoSecretome) and to infer their interactions with human proteins based on the presence of host molecular mimicry elements. FusoSecretome proteins share similar features with known bacterial virulence factors thereby highlighting their pathogenic potential. We show that they interact with human proteins that participate in infection-related cellular processes and localize in established cellular districts of the host-pathogen interface. Our network-based analysis identified 31 functional modules in the human interactome preferentially targeted by 138 FusoSecretome proteins, among which we selected 26 as main candidate virulence proteins, representing both putative and known virulence proteins. Finally, six of the preferentially targeted functional modules are implicated in the onset and progression of inflammatory bowel diseases and colorectal cancer. Overall, our computational analysis identified candidate virulence proteins potentially involved in the F. nucleatum-human cross-talk in the context of gastrointestinal diseases.

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

    Directory of Open Access Journals (Sweden)

    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

  3. Functional equivalency inferred from "authoritative sources" in networks of homologous proteins.

    Science.gov (United States)

    Natarajan, Shreedhar; Jakobsson, Eric

    2009-06-12

    A one-on-one mapping of protein functionality across different species is a critical component of comparative analysis. This paper presents a heuristic algorithm for discovering the Most Likely Functional Counterparts (MoLFunCs) of a protein, based on simple concepts from network theory. A key feature of our algorithm is utilization of the user's knowledge to assign high confidence to selected functional identification. We show use of the algorithm to retrieve functional equivalents for 7 membrane proteins, from an exploration of almost 40 genomes form multiple online resources. We verify the functional equivalency of our dataset through a series of tests that include sequence, structure and function comparisons. Comparison is made to the OMA methodology, which also identifies one-on-one mapping between proteins from different species. Based on that comparison, we believe that incorporation of user's knowledge as a key aspect of the technique adds value to purely statistical formal methods.

  4. Predicting Essential Genes and Proteins Based on Machine Learning and Network Topological Features: A Comprehensive Review

    Science.gov (United States)

    Zhang, Xue; Acencio, Marcio Luis; Lemke, Ney

    2016-01-01

    Essential proteins/genes are indispensable to the survival or reproduction of an organism, and the deletion of such essential proteins will result in lethality or infertility. The identification of essential genes is very important not only for understanding the minimal requirements for survival of an organism, but also for finding human disease genes and new drug targets. Experimental methods for identifying essential genes are costly, time-consuming, and laborious. With the accumulation of sequenced genomes data and high-throughput experimental data, many computational methods for identifying essential proteins are proposed, which are useful complements to experimental methods. In this review, we show the state-of-the-art methods for identifying essential genes and proteins based on machine learning and network topological features, point out the progress and limitations of current methods, and discuss the challenges and directions for further research. PMID:27014079

  5. The membrane stress response buffers lethal effects of lipid disequilibrium by reprogramming the protein homeostasis network.

    Science.gov (United States)

    Thibault, Guillaume; Shui, Guanghou; Kim, Woong; McAlister, Graeme C; Ismail, Nurzian; Gygi, Steven P; Wenk, Markus R; Ng, Davis T W

    2012-10-12

    Lipid composition can differ widely among organelles and even between leaflets of a membrane. Lipid homeostasis is critical because disequilibrium can have disease outcomes. Despite their importance, mechanisms maintaining lipid homeostasis remain poorly understood. Here, we establish a model system to study the global effects of lipid imbalance. Quantitative lipid profiling was integral to monitor changes to lipid composition and for system validation. Applying global transcriptional and proteomic analyses, a dramatically altered biochemical landscape was revealed from adaptive cells. The resulting composite regulation we term the "membrane stress response" (MSR) confers compensation, not through restoration of lipid composition, but by remodeling the protein homeostasis network. To validate its physiological significance, we analyzed the unfolded protein response (UPR), one facet of the MSR and a key regulator of protein homeostasis. We demonstrate that the UPR maintains protein biogenesis, quality control, and membrane integrity-functions otherwise lethally compromised in lipid dysregulated cells. Copyright © 2012 Elsevier Inc. All rights reserved.

  6. Identification of phosphorylation sites in protein kinase A substrates using artificial neural networks and mass spectrometry

    DEFF Research Database (Denmark)

    Hjerrild, M.; Stensballe, A.; Rasmussen, T.E.

    2004-01-01

    kinase A (PKA) phosphorylation sites. The neural network was trained with a positive set of 258 experimentally verified PKA phosphorylation sites. The predictions by NetPhosK were! validated using four novel PKA substrates: Necdin, RFX5, En-2, and Wee 1. The four proteins were phosphorylated by PKA...... in vitro and 13 PKA phosphorylation sites were identified by mass spectrometry. NetPhosK was 100% sensitive and 41% specific in predicting PKA sites in the four proteins. These results demonstrate the potential of using integrated computational and experimental methods for detailed investigations...

  7. K-core decomposition of a protein domain co-occurrence network reveals lower cancer mutation rates for interior cores.

    Science.gov (United States)

    Emerson, Arnold I; Andrews, Simeon; Ahmed, Ikhlak; Azis, Thasni Ka; Malek, Joel A

    2015-01-01

    Network biology currently focuses primarily on metabolic pathways, gene regulatory, and protein-protein interaction networks. While these approaches have yielded critical information, alternative methods to network analysis will offer new perspectives on biological information. A little explored area is the interactions between domains that can be captured using domain co-occurrence networks (DCN). A DCN can be used to study the function and interaction of proteins by representing protein domains and their co-existence in genes and by mapping cancer mutations to the individual protein domains to identify signals. The domain co-occurrence network was constructed for the human proteome based on PFAM domains in proteins. Highly connected domains in the central cores were identified using the k-core decomposition technique. Here we show that these domains were found to be more evolutionarily conserved than the peripheral domains. The somatic mutations for ovarian, breast and prostate cancer diseases were obtained from the TCGA database. We mapped the somatic mutations to the individual protein domains and the local false discovery rate was used to identify significantly mutated domains in each cancer type. Significantly mutated domains were found to be enriched in cancer disease pathways. However, we found that the inner cores of the DCN did not contain any of the significantly mutated domains. We observed that the inner core protein domains are highly conserved and these domains co-exist in large numbers with other protein domains. Mutations and domain co-occurrence networks provide a framework for understanding hierarchal designs in protein function from a network perspective. This study provides evidence that a majority of protein domains in the inner core of the DCN have a lower mutation frequency and that protein domains present in the peripheral regions of the k-core contribute more heavily to the disease. These findings may contribute further to drug development.

  8. Characterizing genes with distinct methylation patterns in the context of protein-protein interaction network: application to human brain tissues.

    Science.gov (United States)

    Li, Yongsheng; Xu, Juan; Chen, Hong; Zhao, Zheng; Li, Shengli; Bai, Jing; Wu, Aiwei; Jiang, Chunjie; Wang, Yuan; Su, Bin; Li, Xia

    2013-01-01

    DNA methylation is an essential epigenetic mechanism involved in transcriptional control. However, how genes with different methylation patterns are assembled in the protein-protein interaction network (PPIN) remains a mystery. In the present study, we systematically dissected the characterization of genes with different methylation patterns in the PPIN. A negative association was detected between the methylation levels in the brain tissues and topological centralities. By focusing on two classes of genes with considerably different methylation levels in the brain tissues, namely the low methylated genes (LMGs) and high methylated genes (HMGs), we found that their organizing principles in the PPIN are distinct. The LMGs tend to be the center of the PPIN, and attacking them causes a more deleterious effect on the network integrity. Furthermore, the LMGs express their functions in a modular pattern and substantial differences in functions are observed between the two types of genes. The LMGs are enriched in the basic biological functions, such as binding activity and regulation of transcription. More importantly, cancer genes, especially recessive cancer genes, essential genes, and aging-related genes were all found more often in the LMGs. Additionally, our analysis presented that the intra-classes communications are enhanced, but inter-classes communications are repressed. Finally, a functional complementation was revealed between methylation and miRNA regulation in the human genome. We have elucidated the assembling principles of genes with different methylation levels in the context of the PPIN, providing key insights into the complex epigenetic regulation mechanisms.

  9. Protein backbone and sidechain torsion angles predicted from NMR chemical shifts using artificial neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Shen Yang; Bax, Ad, E-mail: bax@nih.gov [National Institutes of Health, Laboratory of Chemical Physics, National Institute of Diabetes and Digestive and Kidney Diseases (United States)

    2013-07-15

    A new program, TALOS-N, is introduced for predicting protein backbone torsion angles from NMR chemical shifts. The program relies far more extensively on the use of trained artificial neural networks than its predecessor, TALOS+. Validation on an independent set of proteins indicates that backbone torsion angles can be predicted for a larger, {>=}90 % fraction of the residues, with an error rate smaller than ca 3.5 %, using an acceptance criterion that is nearly two-fold tighter than that used previously, and a root mean square difference between predicted and crystallographically observed ({phi}, {psi}) torsion angles of ca 12 Masculine-Ordinal-Indicator . TALOS-N also reports sidechain {chi}{sup 1} rotameric states for about 50 % of the residues, and a consistency with reference structures of 89 %. The program includes a neural network trained to identify secondary structure from residue sequence and chemical shifts.

  10. Protein backbone and sidechain torsion angles predicted from NMR chemical shifts using artificial neural networks

    International Nuclear Information System (INIS)

    Shen Yang; Bax, Ad

    2013-01-01

    A new program, TALOS-N, is introduced for predicting protein backbone torsion angles from NMR chemical shifts. The program relies far more extensively on the use of trained artificial neural networks than its predecessor, TALOS+. Validation on an independent set of proteins indicates that backbone torsion angles can be predicted for a larger, ≥90 % fraction of the residues, with an error rate smaller than ca 3.5 %, using an acceptance criterion that is nearly two-fold tighter than that used previously, and a root mean square difference between predicted and crystallographically observed (φ, ψ) torsion angles of ca 12º. TALOS-N also reports sidechain χ 1 rotameric states for about 50 % of the residues, and a consistency with reference structures of 89 %. The program includes a neural network trained to identify secondary structure from residue sequence and chemical shifts

  11. STITCH 2: an interaction network database for small molecules and proteins

    DEFF Research Database (Denmark)

    Kuhn, Michael; Szklarczyk, Damian; Franceschini, Andrea

    2010-01-01

    Over the last years, the publicly available knowledge on interactions between small molecules and proteins has been steadily increasing. To create a network of interactions, STITCH aims to integrate the data dispersed over the literature and various databases of biological pathways, drug......-target relationships and binding affinities. In STITCH 2, the number of relevant interactions is increased by incorporation of BindingDB, PharmGKB and the Comparative Toxicogenomics Database. The resulting network can be explored interactively or used as the basis for large-scale analyses. To facilitate links to other...... chemical databases, we adopt InChIKeys that allow identification of chemicals with a short, checksum-like string. STITCH 2.0 connects proteins from 630 organisms to over 74,000 different chemicals, including 2200 drugs. STITCH can be accessed at http://stitch.embl.de/....

  12. Dissecting spatio-temporal protein networks driving human heart development and related disorders

    DEFF Research Database (Denmark)

    Hansen, Kasper Lage; Mølgård, Kjeld; Greenway, Steven

    2010-01-01

    development, we combined detailed phenotype information from deleterious mutations in 255 genes with high-confidence experimental interactome data, and coupled the results to thorough experimental validation. Hereby, we made the first systematic analysis of spatio-temporal protein networks driving many stages......Aberrant organ development is associated with a wide spectrum of disorders, from schizophrenia to congenital heart disease, but systems-level insight into the underlying processes is very limited. Using heart morphogenesis as general model for dissecting the functional architecture of organ...... of a developing organ identifying several novel signaling modules. Our results show that organ development relies on surprisingly few, extensively recycled, protein modules that integrate into complex higher-order networks. This design allows the formation of a complicated organ using simple building blocks...

  13. Bayesian network model for identification of pathways by integrating protein interaction with genetic interaction data.

    Science.gov (United States)

    Fu, Changhe; Deng, Su; Jin, Guangxu; Wang, Xinxin; Yu, Zu-Guo

    2017-09-21

    Molecular interaction data at proteomic and genetic levels provide physical and functional insights into a molecular biosystem and are helpful for the construction of pathway structures complementarily. Despite advances in inferring biological pathways using genetic interaction data, there still exists weakness in developed models, such as, activity pathway networks (APN), when integrating the data from proteomic and genetic levels. It is necessary to develop new methods to infer pathway structure by both of interaction data. We utilized probabilistic graphical model to develop a new method that integrates genetic interaction and protein interaction data and infers exquisitely detailed pathway structure. We modeled the pathway network as Bayesian network and applied this model to infer pathways for the coherent subsets of the global genetic interaction profiles, and the available data set of endoplasmic reticulum genes. The protein interaction data were derived from the BioGRID database. Our method can accurately reconstruct known cellular pathway structures, including SWR complex, ER-Associated Degradation (ERAD) pathway, N-Glycan biosynthesis pathway, Elongator complex, Retromer complex, and Urmylation pathway. By comparing N-Glycan biosynthesis pathway and Urmylation pathway identified from our approach with that from APN, we found that our method is able to overcome its weakness (certain edges are inexplicable). According to underlying protein interaction network, we defined a simple scoring function that only adopts genetic interaction information to avoid the balance difficulty in the APN. Using the effective stochastic simulation algorithm, the performance of our proposed method is significantly high. We developed a new method based on Bayesian network to infer detailed pathway structures from interaction data at proteomic and genetic levels. The results indicate that the developed method performs better in predicting signaling pathways than previously

  14. The driving regulators of the connectivity protein network of brain malignancies

    Science.gov (United States)

    Tahmassebi, Amirhessam; Pinker-Domenig, Katja; Wengert, Georg; Lobbes, Marc; Stadlbauer, Andreas; Wildburger, Norelle C.; Romero, Francisco J.; Morales, Diego P.; Castillo, Encarnacion; Garcia, Antonio; Botella, Guillermo; Meyer-Bäse, Anke

    2017-05-01

    An important problem in modern therapeutics at the proteomic level remains to identify therapeutic targets in a plentitude of high-throughput data from experiments relevant to a variety of diseases. This paper presents the application of novel modern control concepts, such as pinning controllability and observability applied to the glioma cancer stem cells (GSCs) protein graph network with known and novel association to glioblastoma (GBM). The theoretical frameworks provides us with the minimal number of "driver nodes", which are necessary, and their location to determine the full control over the obtained graph network in order to provide a change in the network's dynamics from an initial state (disease) to a desired state (non-disease). The achieved results will provide biochemists with techniques to identify more metabolic regions and biological pathways for complex diseases, to design and test novel therapeutic solutions.

  15. Annotating gene sets by mining large literature collections with protein networks.

    Science.gov (United States)

    Wang, Sheng; Ma, Jianzhu; Yu, Michael Ku; Zheng, Fan; Huang, Edward W; Han, Jiawei; Peng, Jian; Ideker, Trey

    2018-01-01

    Analysis of patient genomes and transcriptomes routinely recognizes new gene sets associated with human disease. Here we present an integrative natural language processing system which infers common functions for a gene set through automatic mining of the scientific literature with biological networks. This system links genes with associated literature phrases and combines these links with protein interactions in a single heterogeneous network. Multiscale functional annotations are inferred based on network distances between phrases and genes and then visualized as an ontology of biological concepts. To evaluate this system, we predict functions for gene sets representing known pathways and find that our approach achieves substantial improvement over the conventional text-mining baseline method. Moreover, our system discovers novel annotations for gene sets or pathways without previously known functions. Two case studies demonstrate how the system is used in discovery of new cancer-related pathways with ontological annotations.

  16. Hybridization characteristics of biomolecular adaptors, covalent DNA streptavidin conjugates

    NARCIS (Netherlands)

    Niemeyer, CM; Burger, W; Hoedemakers, RMJ

    1998-01-01

    Semisynthetic, covalent streptavidin-DNA adducts are versatile molecular connectors for the fabrication of both nano-and microstructured protein arrays by use of DNA hybridization. In this study, the hybridization characteristics of six adduct species, each containing a different DNA sequence of 21

  17. A network model to correlate conformational change and the impedance spectrum of single proteins

    Science.gov (United States)

    Alfinito, Eleonora; Pennetta, Cecilia; Reggiani, Lino

    2008-02-01

    Integrated nanodevices based on proteins or biomolecules are attracting increasing interest in today's research. In fact, it has been shown that proteins such as azurin and bacteriorhodopsin manifest some electrical properties that are promising for the development of active components of molecular electronic devices. Here we focus on two relevant kinds of protein: bovine rhodopsin, prototype of G-protein-coupled-receptor (GPCR) proteins, and the enzyme acetylcholinesterase (AChE), whose inhibition is one of the most qualified treatments of Alzheimer's disease. Both these proteins exert their function starting with a conformational change of their native structure. Our guess is that such a change should be accompanied with a detectable variation of their electrical properties. To investigate this conjecture, we present an impedance network model of proteins, able to estimate the different impedance spectra associated with the different configurations. The distinct types of conformational change of rhodopsin and AChE agree with their dissimilar electrical responses. In particular, for rhodopsin the model predicts variations of the impedance spectra up to about 30%, while for AChE the same variations are limited to about 10%, which supports the existence of a dynamical equilibrium between its native and complexed states.

  18. Revealing the potential pathogenesis of glioma by utilizing a glioma associated protein-protein interaction network.

    Science.gov (United States)

    Pan, Weiran; Li, Gang; Yang, Xiaoxiao; Miao, Jinming

    2015-04-01

    This study aims to explore the potential mechanism of glioma through bioinformatic approaches. The gene expression profile (GSE4290) of glioma tumor and non-tumor samples was downloaded from Gene Expression Omnibus database. A total of 180 samples were available, including 23 non-tumor and 157 tumor samples. Then the raw data were preprocessed using robust multiarray analysis, and 8,890 differentially expressed genes (DEGs) were identified by using t-test (false discovery rate What' more, for the top 10 sub-networks, Gene Ontology (GO) enrichment analysis (p value tissue-specific genes were calculated (p value = 1.0, 1.0, and 0.00014, respectively) and visualized by Venn Diagram package in R. About 61% of human tissue-specific genes were DEGs as well. This research shed new light on the pathogenesis of glioma based on DEGs and GAPN, and our findings might provide potential targets for clinical glioma treatment.

  19. GH32 family activity: a topological approach through protein contact networks.

    Science.gov (United States)

    Cimini, Sara; Di Paola, Luisa; Giuliani, Alessandro; Ridolfi, Alessandra; De Gara, Laura

    2016-11-01

    The application of Protein Contact Networks methodology allowed to highlight a novel response of border region between the two domains to substrate binding. Glycoside hydrolases (GH) are enzymes that mainly hydrolyze the glycosidic bond between two carbohydrates or a carbohydrate and a non-carbohydrate moiety. These enzymes are involved in many fundamental and diverse biological processes in plants. We have focused on the GH32 family, including enzymes very similar in both sequence and structure, each having however clear specificities of substrate preferences and kinetic properties. Structural and topological differences among proteins of the GH32 family have been here identified by means of an emerging approach (Protein Contact network, PCN) based on the formalization of 3D structures as contact networks among amino-acid residues. The PCN approach proved successful in both reconstructing the already known functional domains and in identifying the structural counterpart of the properties of GH32 enzymes, which remain uncertain, like their allosteric character. The main outcome of the study was the discovery of the activation upon binding of the border (cleft) region between the two domains. This reveals the allosteric nature of the enzymatic activity for all the analyzed forms in the GH32 family, a character yet to be highlighted in biochemical studies. Furthermore, we have been able to recognize a topological signature (graph energy) of the different affinity of the enzymes towards small and large substrates.

  20. Features analysis for identification of date and party hubs in protein interaction network of Saccharomyces Cerevisiae.

    Science.gov (United States)

    Mirzarezaee, Mitra; Araabi, Babak N; Sadeghi, Mehdi

    2010-12-19

    It has been understood that biological networks have modular organizations which are the sources of their observed complexity. Analysis of networks and motifs has shown that two types of hubs, party hubs and date hubs, are responsible for this complexity. Party hubs are local coordinators because of their high co-expressions with their partners, whereas date hubs display low co-expressions and are assumed as global connectors. However there is no mutual agreement on these concepts in related literature with different studies reporting their results on different data sets. We investigated whether there is a relation between the biological features of Saccharomyces Cerevisiae's proteins and their roles as non-hubs, intermediately connected, party hubs, and date hubs. We propose a classifier that separates these four classes. We extracted different biological characteristics including amino acid sequences, domain contents, repeated domains, functional categories, biological processes, cellular compartments, disordered regions, and position specific scoring matrix from various sources. Several classifiers are examined and the best feature-sets based on average correct classification rate and correlation coefficients of the results are selected. We show that fusion of five feature-sets including domains, Position Specific Scoring Matrix-400, cellular compartments level one, and composition pairs with two and one gaps provide the best discrimination with an average correct classification rate of 77%. We study a variety of known biological feature-sets of the proteins and show that there is a relation between domains, Position Specific Scoring Matrix-400, cellular compartments level one, composition pairs with two and one gaps of Saccharomyces Cerevisiae's proteins, and their roles in the protein interaction network as non-hubs, intermediately connected, party hubs and date hubs. This study also confirms the possibility of predicting non-hubs, party hubs and date hubs

  1. Network reconstruction based on proteomic data and prior knowledge of protein connectivity using graph theory.

    Directory of Open Access Journals (Sweden)

    Vassilis Stavrakas

    Full Text Available Modeling of signal transduction pathways is instrumental for understanding cells' function. People have been tackling modeling of signaling pathways in order to accurately represent the signaling events inside cells' biochemical microenvironment in a way meaningful for scientists in a biological field. In this article, we propose a method to interrogate such pathways in order to produce cell-specific signaling models. We integrate available prior knowledge of protein connectivity, in a form of a Prior Knowledge Network (PKN with phosphoproteomic data to construct predictive models of the protein connectivity of the interrogated cell type. Several computational methodologies focusing on pathways' logic modeling using optimization formulations or machine learning algorithms have been published on this front over the past few years. Here, we introduce a light and fast approach that uses a breadth-first traversal of the graph to identify the shortest pathways and score proteins in the PKN, fitting the dependencies extracted from the experimental design. The pathways are then combined through a heuristic formulation to produce a final topology handling inconsistencies between the PKN and the experimental scenarios. Our results show that the algorithm we developed is efficient and accurate for the construction of medium and large scale signaling networks. We demonstrate the applicability of the proposed approach by interrogating a manually curated interaction graph model of EGF/TNFA stimulation against made up experimental data. To avoid the possibility of erroneous predictions, we performed a cross-validation analysis. Finally, we validate that the introduced approach generates predictive topologies, comparable to the ILP formulation. Overall, an efficient approach based on graph theory is presented herein to interrogate protein-protein interaction networks and to provide meaningful biological insights.

  2. Resemblance of actin-binding protein/actin gels to covalently crosslinked networks

    Science.gov (United States)

    Janmey, Paul A.; Hvidt, Søren; Lamb, Jennifer; Stossel, Thomas P.

    1990-05-01

    THE maintainance of the shape of cells is often due to their surface elasticity, which arises mainly from an actin-rich cytoplasmic cortex1,2. On locomotion, phagocytosis or fission, however, these cells become partially fluid-like. The finding of proteins that can bind to actin and control the assembly of, or crosslink, actin filaments, and of intracellular messages that regulate the activities of some of these actin-binding proteins, indicates that such 'gel sol' transformations result from the rearrangement of cortical actin-rich networks3. Alternatively, on the basis of a study of the mechanical properties of mixtures of actin filaments and an Acanthamoeba actin-binding protein, α-actinin, it has been proposed that these transformations can be accounted for by rapid exchange of crosslinks between actin filaments4: the cortical network would be solid when the deformation rate is greater than the rate of crosslink exchange, but would deform or 'creep' when deformation is slow enough to permit crosslinker molecules to rearrange. Here we report, however, that mixtures of actin filaments and actin-binding protein (ABP), an actin crosslinking protein of many higher eukaryotes, form gels Theologically equivalent to covalently crosslinked networks. These gels do not creep in response to applied stress on a time scale compatible with most cell-surface movements. These findings support a more complex and controlled mechanism underlying the dynamic mechanical properties of cortical cytoplasm, and can explain why cells do not collapse under the constant shear forces that often exist in tissues.

  3. Knowledge base and neural network approach for protein secondary structure prediction.

    Science.gov (United States)

    Patel, Maulika S; Mazumdar, Himanshu S

    2014-11-21

    Protein structure prediction is of great relevance given the abundant genomic and proteomic data generated by the genome sequencing projects. Protein secondary structure prediction is addressed as a sub task in determining the protein tertiary structure and function. In this paper, a novel algorithm, KB-PROSSP-NN, which is a combination of knowledge base and modeling of the exceptions in the knowledge base using neural networks for protein secondary structure prediction (PSSP), is proposed. The knowledge base is derived from a proteomic sequence-structure database and consists of the statistics of association between the 5-residue words and corresponding secondary structure. The predicted results obtained using knowledge base are refined with a Backpropogation neural network algorithm. Neural net models the exceptions of the knowledge base. The Q3 accuracy of 90% and 82% is achieved on the RS126 and CB396 test sets respectively which suggest improvement over existing state of art methods. Copyright © 2014 Elsevier Ltd. All rights reserved.

  4. Uncovering the protein lysine and arginine methylation network in Arabidopsis chloroplasts.

    Science.gov (United States)

    Alban, Claude; Tardif, Marianne; Mininno, Morgane; Brugière, Sabine; Gilgen, Annabelle; Ma, Sheng; Mazzoleni, Meryl; Gigarel, Océane; Martin-Laffon, Jacqueline; Ferro, Myriam; Ravanel, Stéphane

    2014-01-01

    Post-translational modification of proteins by the addition of methyl groups to the side chains of Lys and Arg residues is proposed to play important roles in many cellular processes. In plants, identification of non-histone methylproteins at a cellular or subcellular scale is still missing. To gain insights into the extent of this modification in chloroplasts we used a bioinformatics approach to identify protein methyltransferases targeted to plastids and set up a workflow to specifically identify Lys and Arg methylated proteins from proteomic data used to produce the Arabidopsis chloroplast proteome. With this approach we could identify 31 high-confidence Lys and Arg methylation sites from 23 chloroplastic proteins, of which only two were previously known to be methylated. These methylproteins are split between the stroma, thylakoids and envelope sub-compartments. They belong to essential metabolic processes, including photosynthesis, and to the chloroplast biogenesis and maintenance machinery (translation, protein import, division). Also, the in silico identification of nine protein methyltransferases that are known or predicted to be targeted to plastids provided a foundation to build the enzymes/substrates relationships that govern methylation in chloroplasts. Thereby, using in vitro methylation assays with chloroplast stroma as a source of methyltransferases we confirmed the methylation sites of two targets, plastid ribosomal protein L11 and the β-subunit of ATP synthase. Furthermore, a biochemical screening of recombinant chloroplastic protein Lys methyltransferases allowed us to identify the enzymes involved in the modification of these substrates. The present study provides a useful resource to build the methyltransferases/methylproteins network and to elucidate the role of protein methylation in chloroplast biology.

  5. Uncovering the protein lysine and arginine methylation network in Arabidopsis chloroplasts.

    Directory of Open Access Journals (Sweden)

    Claude Alban

    Full Text Available Post-translational modification of proteins by the addition of methyl groups to the side chains of Lys and Arg residues is proposed to play important roles in many cellular processes. In plants, identification of non-histone methylproteins at a cellular or subcellular scale is still missing. To gain insights into the extent of this modification in chloroplasts we used a bioinformatics approach to identify protein methyltransferases targeted to plastids and set up a workflow to specifically identify Lys and Arg methylated proteins from proteomic data used to produce the Arabidopsis chloroplast proteome. With this approach we could identify 31 high-confidence Lys and Arg methylation sites from 23 chloroplastic proteins, of which only two were previously known to be methylated. These methylproteins are split between the stroma, thylakoids and envelope sub-compartments. They belong to essential metabolic processes, including photosynthesis, and to the chloroplast biogenesis and maintenance machinery (translation, protein import, division. Also, the in silico identification of nine protein methyltransferases that are known or predicted to be targeted to plastids provided a foundation to build the enzymes/substrates relationships that govern methylation in chloroplasts. Thereby, using in vitro methylation assays with chloroplast stroma as a source of methyltransferases we confirmed the methylation sites of two targets, plastid ribosomal protein L11 and the β-subunit of ATP synthase. Furthermore, a biochemical screening of recombinant chloroplastic protein Lys methyltransferases allowed us to identify the enzymes involved in the modification of these substrates. The present study provides a useful resource to build the methyltransferases/methylproteins network and to elucidate the role of protein methylation in chloroplast biology.

  6. Signaling by Small GTPases at Cell-Cell junctions: Protein Interactions Building Control and Networks.

    Science.gov (United States)

    Braga, Vania

    2017-09-11

    A number of interesting reports highlight the intricate network of signaling proteins that coordinate formation and maintenance of cell-cell contacts. We have much yet to learn about how the in vitro binding data is translated into protein association inside the cells and whether such interaction modulates the signaling properties of the protein. What emerges from recent studies is the importance to carefully consider small GTPase activation in the context of where its activation occurs, which upstream regulators are involved in the activation/inactivation cycle and the GTPase interacting partners that determine the intracellular niche and extent of signaling. Data discussed here unravel unparalleled cooperation and coordination of functions among GTPases and their regulators in supporting strong adhesion between cells. Copyright © 2017 Cold Spring Harbor Laboratory Press; all rights reserved.

  7. Simplified Swarm Optimization-Based Function Module Detection in Protein–Protein Interaction Networks

    Directory of Open Access Journals (Sweden)

    Xianghan Zheng

    2017-04-01

    Full Text Available Proteomics research has become one of the most important topics in the field of life science and natural science. At present, research on protein–protein interaction networks (PPIN mainly focuses on detecting protein complexes or function modules. However, existing approaches are either ineffective or incomplete. In this paper, we investigate detection mechanisms of functional modules in PPIN, including open database, existing detection algorithms, and recent solutions. After that, we describe the proposed approach based on the simplified swarm optimization (SSO algorithm and the knowledge of Gene Ontology (GO. The proposed solution implements the SSO algorithm for clustering proteins with similar function, and imports biological gene ontology knowledge for further identifying function complexes and improving detection accuracy. Furthermore, we use four different categories of species datasets for experiment: fruitfly, mouse, scere, and human. The testing and analysis result show that the proposed solution is feasible, efficient, and could achieve a higher accuracy of prediction than existing approaches.

  8. Evolutionary Conservation and Emerging Functional Diversity of the Cytosolic Hsp70:J Protein Chaperone Network of Arabidopsis thaliana.

    Science.gov (United States)

    Verma, Amit K; Diwan, Danish; Raut, Sandeep; Dobriyal, Neha; Brown, Rebecca E; Gowda, Vinita; Hines, Justin K; Sahi, Chandan

    2017-06-07

    Heat shock proteins of 70 kDa (Hsp70s) partner with structurally diverse Hsp40s (J proteins), generating distinct chaperone networks in various cellular compartments that perform myriad housekeeping and stress-associated functions in all organisms. Plants, being sessile, need to constantly maintain their cellular proteostasis in response to external environmental cues. In these situations, the Hsp70:J protein machines may play an important role in fine-tuning cellular protein quality control. Although ubiquitous, the functional specificity and complexity of the plant Hsp70:J protein network has not been studied. Here, we analyzed the J protein network in the cytosol of Arabidopsis thaliana and, using yeast genetics, show that the functional specificities of most plant J proteins in fundamental chaperone functions are conserved across long evolutionary timescales. Detailed phylogenetic and functional analysis revealed that increased number, regulatory differences, and neofunctionalization in J proteins together contribute to the emerging functional diversity and complexity in the Hsp70:J protein network in higher plants. Based on the data presented, we propose that higher plants have orchestrated their "chaperome," especially their J protein complement, according to their specialized cellular and physiological stipulations. Copyright © 2017 Verma et al.

  9. Nuclear adaptor Ldb1 regulates a transcriptional program essential for the maintenance of hematopoietic stem cells.

    Science.gov (United States)

    Li, LiQi; Jothi, Raja; Cui, Kairong; Lee, Jan Y; Cohen, Tsadok; Gorivodsky, Marat; Tzchori, Itai; Zhao, Yangu; Hayes, Sandra M; Bresnick, Emery H; Zhao, Keji; Westphal, Heiner; Love, Paul E

    2011-02-01

    The nuclear adaptor Ldb1 functions as a core component of multiprotein transcription complexes that regulate differentiation in diverse cell types. In the hematopoietic lineage, Ldb1 forms a complex with the non-DNA-binding adaptor Lmo2 and the transcription factors E2A, Scl and GATA-1 (or GATA-2). Here we demonstrate a critical and continuous requirement for Ldb1 in the maintenance of both fetal and adult mouse hematopoietic stem cells (HSCs). Deletion of Ldb1 in hematopoietic progenitors resulted in the downregulation of many transcripts required for HSC maintenance. Genome-wide profiling by chromatin immunoprecipitation followed by sequencing (ChIP-Seq) identified Ldb1 complex-binding sites at highly conserved regions in the promoters of genes involved in HSC maintenance. Our results identify a central role for Ldb1 in regulating the transcriptional program responsible for the maintenance of HSCs.

  10. Understanding gene essentiality by finely characterizing hubs in the yeast protein interaction network.

    Science.gov (United States)

    Pang, Kaifang; Sheng, Huanye; Ma, Xiaotu

    2010-10-08

    The centrality-lethality rule, i.e., high-degree proteins or hubs tend to be more essential than low-degree proteins in the yeast protein interaction network, reveals that a protein's central position indicates its important function, but whether and why hubs tend to be more essential have been heavily debated. Here, we integrated gene expression and functional module data to classify hubs into four types: non-co-expressed non-co-cluster hubs, non-co-expressed co-cluster hubs, co-expressed non-co-cluster hubs and co-expressed co-cluster hubs. We found that all the four hub types are more essential than non-hubs, but they also show different enrichments in essential proteins. Non-co-expressed non-co-cluster hubs play key role in organizing different modules formed by the other three hub types, but they are less important to the survival of the yeast cell. Among the four hub types, co-expressed co-cluster hubs, which likely correspond to the core components of stable protein complexes, are the most essential. These results demonstrated that our classification of hubs into four types could better improve the understanding of gene essentiality. Copyright © 2010 Elsevier Inc. All rights reserved.

  11. Amino Acid Flux from Metabolic Network Benefits Protein Translation: the Role of Resource Availability.

    Science.gov (United States)

    Hu, Xiao-Pan; Yang, Yi; Ma, Bin-Guang

    2015-06-09

    Protein translation is a central step in gene expression and affected by many factors such as codon usage bias, mRNA folding energy and tRNA abundance. Despite intensive previous studies, how metabolic amino acid supply correlates with protein translation efficiency remains unknown. In this work, we estimated the amino acid flux from metabolic network for each protein in Escherichia coli and Saccharomyces cerevisiae by using Flux Balance Analysis. Integrated with the mRNA expression level, protein abundance and ribosome profiling data, we provided a detailed description of the role of amino acid supply in protein translation. Our results showed that amino acid supply positively correlates with translation efficiency and ribosome density. Moreover, with the rank-based regression model, we found that metabolic amino acid supply facilitates ribosome utilization. Based on the fact that the ribosome density change of well-amino-acid-supplied genes is smaller than poorly-amino-acid-supply genes under amino acid starvation, we reached the conclusion that amino acid supply may buffer ribosome density change against amino acid starvation and benefit maintaining a relatively stable translation environment. Our work provided new insights into the connection between metabolic amino acid supply and protein translation process by revealing a new regulation strategy that is dependent on resource availability.

  12. Prediction of protein function using a deep convolutional neural network ensemble

    Directory of Open Access Journals (Sweden)

    Evangelia I. Zacharaki

    2017-07-01

    Full Text Available Background The availability of large databases containing high resolution three-dimensional (3D models of proteins in conjunction with functional annotation allows the exploitation of advanced supervised machine learning techniques for automatic protein function prediction. Methods In this work, novel shape features are extracted representing protein structure in the form of local (per amino acid distribution of angles and amino acid distances, respectively. Each of the multi-channel feature maps is introduced into a deep convolutional neural network (CNN for function prediction and the outputs are fused through support vector machines or a correlation-based k-nearest neighbor classifier. Two different architectures are investigated employing either one CNN per multi-channel feature set, or one CNN per image channel. Results Cross validation experiments on single-functional enzymes (n = 44,661 from the PDB database achieved 90.1% correct classification, demonstrating an improvement over previous results on the same dataset when sequence similarity was not considered. Discussion The automatic prediction of protein function can provide quick annotations on extensive datasets opening the path for relevant applications, such as pharmacological target identification. The proposed method shows promise for structure-based protein function prediction, but sufficient data may not yet be available to properly assess the method’s performance on non-homologous proteins and thus reduce the confounding factor of evolutionary relationships.

  13. Atomic interaction networks in the core of protein domains and their native folds.

    Science.gov (United States)

    Soundararajan, Venkataramanan; Raman, Rahul; Raguram, S; Sasisekharan, V; Sasisekharan, Ram

    2010-02-23

    Vastly divergent sequences populate a majority of protein folds. In the quest to identify features that are conserved within protein domains belonging to the same fold, we set out to examine the entire protein universe on a fold-by-fold basis. We report that the atomic interaction network in the solvent-unexposed core of protein domains are fold-conserved, extraordinary sequence divergence notwithstanding. Further, we find that this feature, termed protein core atomic interaction network (or PCAIN) is significantly distinguishable across different folds, thus appearing to be "signature" of a domain's native fold. As part of this study, we computed the PCAINs for 8698 representative protein domains from families across the 1018 known protein folds to construct our seed database and an automated framework was developed for PCAIN-based characterization of the protein fold universe. A test set of randomly selected domains that are not in the seed database was classified with over 97% accuracy, independent of sequence divergence. As an application of this novel fold signature, a PCAIN-based scoring scheme was developed for comparative (homology-based) structure prediction, with 1-2 angstroms (mean 1.61A) C(alpha) RMSD generally observed between computed structures and reference crystal structures. Our results are consistent across the full spectrum of test domains including those from recent CASP experiments and most notably in the 'twilight' and 'midnight' zones wherein <30% and <10% target-template sequence identity prevails (mean twilight RMSD of 1.69A). We further demonstrate the utility of the PCAIN protocol to derive biological insight into protein structure-function relationships, by modeling the structure of the YopM effector novel E3 ligase (NEL) domain from plague-causative bacterium Yersinia Pestis and discussing its implications for host adaptive and innate immune modulation by the pathogen. Considering the several high-throughput, sequence

  14. Enhanced Toll-like receptor responses in the absence of signaling adaptor DAP12.

    OpenAIRE

    Hamerman, Jessica A; Tchao, Nadia K; Lowell, Clifford A; Lanier, Lewis L

    2005-01-01

    DAP12 is a signaling adaptor containing an immunoreceptor tyrosine-based activation motif (ITAM) that pairs with receptors on myeloid cells and natural killer cells. We examine here the responses of mice lacking DAP12 to stimulation through Toll-like receptors (TLRs). Unexpectedly, DAP12-deficient macrophages produced higher concentrations of inflammatory cytokines in response to a variety of pathogenic stimuli. Additionally, macrophages deficient in spleen tyrosine kinase (Syk), which signal...

  15. An assessment of machine and statistical learning approaches to inferring networks of protein-protein interactions

    Directory of Open Access Journals (Sweden)

    Browne Fiona

    2006-12-01

    Full Text Available Protein-protein interactions (PPI play a key role in many biological systems. Over the past few years, an explosion in availability of functional biological data obtained from high-throughput technologies to infer PPI has been observed. However, results obtained from such experiments show high rates of false positives and false negatives predictions as well as systematic predictive bias. Recent research has revealed that several machine and statistical learning methods applied to integrate relatively weak, diverse sources of large-scale functional data may provide improved predictive accuracy and coverage of PPI. In this paper we describe the effects of applying different computational, integrative methods to predict PPI in Saccharomyces cerevisiae. We investigated the predictive ability of combining different sets of relatively strong and weak predictive datasets. We analysed several genomic datasets ranging from mRNA co-expression to marginal essentiality. Moreover, we expanded an existing multi-source dataset from S. cerevisiae by constructing a new set of putative interactions extracted from Gene Ontology (GO- driven annotations in the Saccharomyces Genome Database. Different classification techniques: Simple Naive Bayesian (SNB, Multilayer Perceptron (MLP and K-Nearest Neighbors (KNN were evaluated. Relatively simple classification methods (i.e. less computing intensive and mathematically complex, such as SNB, have been proven to be proficient at predicting PPI. SNB produced the “highest” predictive quality obtaining an area under Receiver Operating Characteristic (ROC curve (AUC value of 0.99. The lowest AUC value of 0.90 was obtained by the KNN classifier. This assessment also demonstrates the strong predictive power of GO-driven models, which offered predictive performance above 0.90 using the different machine learning and statistical techniques. As the predictive power of single-source datasets became weaker MLP and SNB performed

  16. Using likelihood-free inference to compare evolutionary dynamics of the protein networks of H. pylori and P. falciparum.

    Directory of Open Access Journals (Sweden)

    Oliver Ratmann

    2007-11-01

    Full Text Available Gene duplication with subsequent interaction divergence is one of the primary driving forces in the evolution of genetic systems. Yet little is known about the precise mechanisms and the role of duplication divergence in the evolution of protein networks from the prokaryote and eukaryote domains. We developed a novel, model-based approach for Bayesian inference on biological network data that centres on approximate Bayesian computation, or likelihood-free inference. Instead of computing the intractable likelihood of the protein network topology, our method summarizes key features of the network and, based on these, uses a MCMC algorithm to approximate the posterior distribution of the model parameters. This allowed us to reliably fit a flexible mixture model that captures hallmarks of evolution by gene duplication and subfunctionalization to protein interaction network data of Helicobacter pylori and Plasmodium falciparum. The 80% credible intervals for the duplication-divergence component are [0.64, 0.98] for H. pylori and [0.87, 0.99] for P. falciparum. The remaining parameter estimates are not inconsistent with sequence data. An extensive sensitivity analysis showed that incompleteness of PIN data does not largely affect the analysis of models of protein network evolution, and that the degree sequence alone barely captures the evolutionary footprints of protein networks relative to other statistics. Our likelihood-free inference approach enables a fully Bayesian analysis of a complex and highly stochastic system that is otherwise intractable at present. Modelling the evolutionary history of PIN data, it transpires that only the simultaneous analysis of several global aspects of protein networks enables credible and consistent inference to be made from available datasets. Our results indicate that gene duplication has played a larger part in the network evolution of the eukaryote than in the prokaryote, and suggests that single gene

  17. Gene promoter evolution targets the center of the human protein interaction network.

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    Jordi Planas

    Full Text Available Assessing the contribution of promoters and coding sequences to gene evolution is an important step toward discovering the major genetic determinants of human evolution. Many specific examples have revealed the evolutionary importance of cis-regulatory regions. However, the relative contribution of regulatory and coding regions to the evolutionary process and whether systemic factors differentially influence their evolution remains unclear. To address these questions, we carried out an analysis at the genome scale to identify signatures of positive selection in human proximal promoters. Next, we examined whether genes with positively selected promoters (Prom+ genes show systemic differences with respect to a set of genes with positively selected protein-coding regions (Cod+ genes. We found that the number of genes in each set was not significantly different (8.1% and 8.5%, respectively. Furthermore, a functional analysis showed that, in both cases, positive selection affects almost all biological processes and only a few genes of each group are located in enriched categories, indicating that promoters and coding regions are not evolutionarily specialized with respect to gene function. On the other hand, we show that the topology of the human protein network has a different influence on the molecular evolution of proximal promoters and coding regions. Notably, Prom+ genes have an unexpectedly high centrality when compared with a reference distribution (P=0.008, for Eigenvalue centrality. Moreover, the frequency of Prom+ genes increases from the periphery to the center of the protein network (P=0.02, for the logistic regression coefficient. This means that gene centrality does not constrain the evolution of proximal promoters, unlike the case with coding regions, and further indicates that the evolution of proximal promoters is more efficient in the center of the protein network than in the periphery. These results show that proximal promoters

  18. Bias in ligation-based small RNA sequencing library construction is determined by adaptor and RNA structure.

    Directory of Open Access Journals (Sweden)

    Ryan T Fuchs

    Full Text Available High-throughput sequencing (HTS has become a powerful tool for the detection of and sequence characterization of microRNAs (miRNA and other small RNAs (sRNA. Unfortunately, the use of HTS data to determine the relative quantity of different miRNAs in a sample has been shown to be inconsistent with quantitative PCR and Northern Blot results. Several recent studies have concluded that the major contributor to this inconsistency is bias introduced during the construction of sRNA libraries for HTS and that the bias is primarily derived from the adaptor ligation steps, specifically where single stranded adaptors are sequentially ligated to the 3' and 5'-end of sRNAs using T4 RNA ligases. In this study we investigated the effects of ligation bias by using a pool of randomized ligation substrates, defined mixtures of miRNA sequences and several combinations of adaptors in HTS library construction. We