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

Phosphotyrosine signaling proteins that drive oncogenesis tend to be highly interconnected.

Science.gov (United States)

Koytiger, Grigoriy; Kaushansky, Alexis; Gordus, Andrew; Rush, John; Sorger, Peter K; MacBeath, Gavin

2013-05-01

Mutation and overexpression of receptor tyrosine kinases or the proteins they regulate serve as oncogenic drivers in diverse cancers. To better understand receptor tyrosine kinase signaling and its link to oncogenesis, we used protein microarrays to systematically and quantitatively measure interactions between virtually every SH2 or PTB domain encoded in the human genome and all known sites of tyrosine phosphorylation on 40 receptor tyrosine kinases and on most of the SH2 and PTB domain-containing adaptor proteins. We found that adaptor proteins, like RTKs, have many high affinity bindings sites for other adaptor proteins. In addition, proteins that drive cancer, including both receptors and adaptor proteins, tend to be much more highly interconnected via networks of SH2 and PTB domain-mediated interactions than nononcogenic proteins. Our results suggest that network topological properties such as connectivity can be used to prioritize new drug targets in this well-studied family of signaling proteins.

Structural basis for the interaction of the adaptor protein grb14 with activated ras.

Directory of Open Access Journals (Sweden)

Rohini Qamra

Full Text Available Grb14, a member of the Grb7-10-14 family of cytoplasmic adaptor proteins, is a tissue-specific negative regulator of insulin signaling. Grb7-10-14 contain several signaling modules, including a Ras-associating (RA domain, a pleckstrin-homology (PH domain, a family-specific BPS (between PH and SH2 region, and a C-terminal Src-homology-2 (SH2 domain. We showed previously that the RA and PH domains, along with the BPS region and SH2 domain, are necessary for downregulation of insulin signaling. Here, we report the crystal structure at 2.4-Å resolution of the Grb14 RA and PH domains in complex with GTP-loaded H-Ras (G12V. The structure reveals that the Grb14 RA and PH domains form an integrated structural unit capable of binding simultaneously to small GTPases and phosphoinositide lipids. The overall mode of binding of the Grb14 RA domain to activated H-Ras is similar to that of the RA domains of RalGDS and Raf1 but with important distinctions. The integrated RA-PH structural unit in Grb7-10-14 is also found in a second adaptor family that includes Rap1-interacting adaptor molecule (RIAM and lamellipodin, proteins involved in actin-cytoskeleton rearrangement. The structure of Grb14 RA-PH in complex with H-Ras represents the first detailed molecular characterization of tandem RA-PH domains bound to a small GTPase and provides insights into the molecular basis for specificity.

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

Regulation and function of the CD3¿ DxxxLL motif: a binding site for adaptor protein-1 and adaptor protein-2 in vitro

DEFF Research Database (Denmark)

Dietrich, J; Kastrup, J; Nielsen, B L

1997-01-01

/CD3gamma chimeras; and in vitro by binding CD3gamma peptides to clathrin-coated vesicle adaptor proteins (APs). We find that the CD3gamma D127xxxLL131/132 sequence represents one united motif for binding of both AP-1 and AP-2, and that this motif functions as an active sorting motif in monomeric CD4...... and for AP binding in vitro. Furthermore, we provide evidence indicating that phosphorylation of CD3gamma S126 in the context of the complete TCR induces a conformational change that exposes the DxxxLL sequence for AP binding. Exposure of the DxxxLL motif causes an increase in the TCR internalization rate...

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.

Synthetic protein scaffolds based on peptide motifs and cognate adaptor domains for improving metabolic productivity

Directory of Open Access Journals (Sweden)

Anselm H.C. Horn

2015-11-01

Full Text Available The efficiency of many cellular processes relies on the defined interaction among different proteins within the same metabolic or signaling pathway. Consequently, a spatial colocalization of functionally interacting proteins has frequently emerged during evolution. This concept has been adapted within the synthetic biology community for the purpose of creating artificial scaffolds. A recent advancement of this concept is the use of peptide motifs and their cognate adaptor domains. SH2, SH3, GBD, and PDZ domains have been used most often in research studies to date. The approach has been successfully applied to the synthesis of a variety of target molecules including catechin, D-glucaric acid, H2, hydrochinone, resveratrol, butyrate, gamma-aminobutyric acid, and mevalonate. Increased production levels of up to 77-fold have been observed compared to non-scaffolded systems. A recent extension of this concept is the creation of a covalent linkage between peptide motifs and adaptor domains, which leads to a more stable association of the scaffolded systems and thus bears the potential to further enhance metabolic productivity.

The adaptor protein CIKS/Act1 is essential for IL-25-mediated allergic airway inflammation.

Science.gov (United States)

Claudio, Estefania; Sønder, Søren Ulrik; Saret, Sun; Carvalho, Gabrielle; Ramalingam, Thirumalai R; Wynn, Thomas A; Chariot, Alain; Garcia-Perganeda, Antonio; Leonardi, Antonio; Paun, Andrea; Chen, Amy; Ren, Nina Y; Wang, Hongshan; Siebenlist, Ulrich

2009-02-01

IL-17 is the signature cytokine of recently discovered Th type 17 (Th17) cells, which are prominent in defense against extracellular bacteria and fungi as well as in autoimmune diseases, such as rheumatoid arthritis and experimental autoimmune encephalomyelitis in animal models. IL-25 is a member of the IL-17 family of cytokines, but has been associated with Th2 responses instead and may negatively cross-regulate Th17/IL-17 responses. IL-25 can initiate an allergic asthma-like inflammation in the airways, which includes recruitment of eosinophils, mucus hypersecretion, Th2 cytokine production, and airways hyperreactivity. We demonstrate that these effects of IL-25 are entirely dependent on the adaptor protein CIKS (also known as Act1). Surprisingly, this adaptor is necessary to transmit IL-17 signals as well, despite the very distinct biologic responses that these two cytokines elicit. We identify CD11c(+) macrophage-like lung cells as physiologic relevant targets of IL-25 in vivo.

Adaptor protein complex 2-mediated, clathrin-dependent endocytosis, and related gene activities, are a prominent feature during maturation stage amelogenesis.

Science.gov (United States)

Lacruz, Rodrigo S; Brookes, Steven J; Wen, Xin; Jimenez, Jaime M; Vikman, Susanna; Hu, Ping; White, Shane N; Lyngstadaas, S Petter; Okamoto, Curtis T; Smith, Charles E; Paine, Michael L

2013-03-01

Molecular events defining enamel matrix removal during amelogenesis are poorly understood. Early reports have suggested that adaptor proteins (AP) participate in ameloblast-mediated endocytosis. Enamel formation involves the secretory and maturation stages, with an increase in resorptive function during the latter. Here, using real-time PCR, we show that the expression of clathrin and adaptor protein subunits are upregulated in maturation stage rodent enamel organ cells. AP complex 2 (AP-2) is the most upregulated of the four distinct adaptor protein complexes. Immunolocalization confirms the presence of AP-2 and clathrin in ameloblasts, with strongest reactivity at the apical pole. These data suggest that the resorptive functions of enamel cells involve AP-2 mediated, clathrin-dependent endocytosis, thus implying the likelihood of specific membrane-bound receptor(s) of enamel matrix protein debris. The mRNA expression of other endocytosis-related gene products is also upregulated during maturation including: lysosomal-associated membrane protein 1 (Lamp1); cluster of differentiation 63 and 68 (Cd63 and Cd68); ATPase, H(+) transporting, lysosomal V0 subunit D2 (Atp6v0d2); ATPase, H(+) transporting, lysosomal V1 subunit B2 (Atp6v1b2); chloride channel, voltage-sensitive 7 (Clcn7); and cathepsin K (Ctsk). Immunohistologic data confirms the expression of a number of these proteins in maturation stage ameloblasts. The enamel of Cd63-null mice was also examined. Despite increased mRNA and protein expression in the enamel organ during maturation, the enamel of Cd63-null mice appeared normal. This may suggest inherent functional redundancies between Cd63 and related gene products, such as Lamp1 and Cd68. Ameloblast-like LS8 cells treated with the enamel matrix protein complex Emdogain showed upregulation of AP-2 and clathrin subunits, further supporting the existence of a membrane-bound receptor-regulated pathway for the endocytosis of enamel matrix proteins. These data

Adaptor protein Lnk negatively regulates the mutant MPL, MPLW515L associated with myeloproliferative disorders

OpenAIRE

Gery, Sigal; Gueller, Saskia; Chumakova, Katya; Kawamata, Norihiko; Liu, Liqin; Koeffler, H. Phillip

2007-01-01

Recently, activating myeloproliferative leukemia virus oncogene (MPL) mutations, MPLW515L/K, were described in myeloproliferative disorder (MPD) patients. MPLW515L leads to activation of downstream signaling pathways and cytokine-independent proliferation in hematopoietic cells. The adaptor protein Lnk is a negative regulator of several cytokine receptors, including MPL. We show that overexpression of Lnk in Ba/F3-MPLW515L cells inhibits cytokine-independent growth, while suppression of Lnk i...

Several adaptor proteins promote intracellular localisation of the transporter MRP4/ABCC4 in platelets and haematopoietic cells.

Science.gov (United States)

Schaletzki, Yvonne; Kromrey, Marie-Luise; Bröderdorf, Susanne; Hammer, Elke; Grube, Markus; Hagen, Paul; Sucic, Sonja; Freissmuth, Michael; Völker, Uwe; Greinacher, Andreas; Rauch, Bernhard H; Kroemer, Heyo K; Jedlitschky, Gabriele

2017-01-05

The multidrug resistance protein 4 (MRP4/ABCC4) has been identified as an important transporter for signalling molecules including cyclic nucleotides and several lipid mediators in platelets and may thus represent a novel target to interfere with platelet function. Besides its localisation in the plasma membrane, MRP4 has been also detected in the membrane of dense granules in resting platelets. In polarised cells it is localised at the basolateral or apical plasma membrane. To date, the mechanism of MRP4 trafficking has not been elucidated; protein interactions may regulate both the localisation and function of this transporter. We approached this issue by searching for interacting proteins by in vitro binding assays, followed by immunoblotting and mass spectrometry, and by visualising their co-localisation in platelets and haematopoietic cells. We identified the PDZ domain containing scaffold proteins ezrin-binding protein 50 (EBP50/NHERF1), postsynaptic density protein 95 (PSD95), and sorting nexin 27 (SNX27), but also the adaptor protein complex 3 subunit β3A (AP3B1) and the heat shock protein HSP90 as putative interaction partners of MRP4. The knock-down of SNX27, PSD95, and AP3B1 by siRNA in megakaryoblastic leukaemia cells led to a redistribution of MRP4 from intracellular structures to the plasma membrane. Inhibition of HSP90 led to a diminished expression and retention of MRP4 in the endoplasmic reticulum. These results indicate that MRP4 localisation and function are regulated by multiple protein interactions. Changes in the adaptor proteins can hence lead to altered localisation and function of the transporter.

The adaptor protein CIKS/Act1 is essential for IL-25-mediated allergic airway inflammation1

Science.gov (United States)

Claudio, Estefania; Sønder, Søren Ulrik; Saret, Sun; Carvalho, Gabrielle; Ramalingam, Thirumalai R; Wynn, Thomas A; Chariot, Alain; Garcia-Perganeda, Antonio; Leonardi, Antonio; Paun, Andrea; Chen, Amy; Ren, Nina Y.; Wang, Hongshan; Siebenlist, Ulrich

2008-01-01

IL-17 is the signature cytokine of recently discovered T helper type 17 (Th17) cells, which are prominent in defense against extracellular bacteria and fungi as well as in autoimmune diseases, such as rheumatoid arthritis and experimental autoimmune encephalomyelitis in animal models. IL-25 is a member of the IL-17 family of cytokines, but has been associated with Th2 responses instead and may negatively cross-regulate Th17/IL-17 responses. IL-25 can initiate an allergic asthma-like inflammation in the airways, which includes recruitment of eosinophils, mucus hypersecretion, Th2 cytokine production and airways hyperreactivity. We demonstrate that these effects of IL-25 are entirely dependent on the adaptor protein CIKS (a.k.a. Act1). Surprisingly, this adaptor is necessary to transmit IL-17 signals as well, despite the very distinct biologic responses these two cytokines elicit. We identify CD11c+ macrophage-like lung cells as physiologic relevant targets of IL-25 in vivo. PMID:19155511

PHF6 Degrees of Separation: The Multifaceted Roles of a Chromatin Adaptor Protein.

Science.gov (United States)

Todd, Matthew A M; Ivanochko, Danton; Picketts, David J

2015-06-19

The importance of chromatin regulation to human disease is highlighted by the growing number of mutations identified in genes encoding chromatin remodeling proteins. While such mutations were first identified in severe developmental disorders, or in specific cancers, several genes have been implicated in both, including the plant homeodomain finger protein 6 (PHF6) gene. Indeed, germline mutations in PHF6 are the cause of the Börjeson-Forssman-Lehmann X-linked intellectual disability syndrome (BFLS), while somatic PHF6 mutations have been identified in T-cell acute lymphoblastic leukemia (T-ALL) and acute myeloid leukemia (AML). Studies from different groups over the last few years have made a significant impact towards a functional understanding of PHF6 protein function. In this review, we summarize the current knowledge of PHF6 with particular emphasis on how it interfaces with a distinct set of interacting partners and its functional roles in the nucleoplasm and nucleolus. Overall, PHF6 is emerging as a key chromatin adaptor protein critical to the regulation of neurogenesis and hematopoiesis.

Architecture and roles of periplasmic adaptor proteins in tripartite efflux assemblies.

Directory of Open Access Journals (Sweden)

Vassiliy N. Bavro

2015-05-01

Full Text Available Recent years have seen major advances in the structural understanding of the different components of tripartite efflux assemblies, which encompass the multidrug efflux (MDR pumps and type I secretion systems. The majority of these investigations have focused on the role played by the inner membrane transporters and the outer membrane factor (OMF, leaving the third component of the system – the Periplasmic Adaptor Proteins (PAPs - relatively understudied. Here we review the current state of knowledge of these versatile proteins which, far from being passive linkers between the OMF and the transporter, emerge as active architects of tripartite assemblies, and play diverse roles in the transport process. Recognition between the PAPs and OMFs is essential for pump assembly and function, and targeting this interaction may provide a novel avenue for combating multidrug resistance. With the recent advances elucidating the drug-efflux and energetics of the tripartite assemblies, the understanding of the interaction between the OMFs and PAPs is the last piece remaining in the complete structure of the tripartite pump assembly puzzle.

Biochemical and genetic analysis of the Drk SH2/SH3 adaptor protein of Drosophila.

OpenAIRE

Raabe, T; Olivier, J P; Dickson, B J; Liu, X; Gish, G D; Pawson, T; Hafen, E

1995-01-01

The Drk SH3-SH2-SH3 adaptor protein has been genetically identified in a screen for rate-limiting components acting downstream of the Sevenless (Sev) receptor tyrosine kinase in the developing eye of Drosophila. It provides a link between the activated Sev receptor and Sos, a guanine nucleotide release factor that activates Ras1. We have used a combined biochemical and genetic approach to study the interactions between Sev, Drk and Sos. We show that Tyr2546 in the cytoplasmic tail of Sev is r...

Adaptor Protein Complex 2 (AP-2) Mediated, Clathrin Dependent Endocytosis, And Related Gene Activities, Are A Prominent Feature During Maturation Stage Amelogenesis

Science.gov (United States)

LACRUZ, Rodrigo S.; BROOKES, Steven J.; WEN, Xin; JIMENEZ, Jaime M.; VIKMAN, Susanna; HU, Ping; WHITE, Shane N.; LYNGSTADAAS, S. Petter; OKAMOTO, Curtis T.; SMITH, Charles E.; PAINE, Michael L.

2012-01-01

Molecular events defining enamel matrix removal during amelogenesis are poorly understood. Early reports have suggested that adaptor proteins (AP) participate in ameloblast-mediated endocytosis. Enamel formation involves the secretory and maturation stages, with an increase in resorptive function during the latter. Here, using real time PCR, we show that the expression of clathrin and adaptor protein subunits are up-regulated in maturation stage rodent enamel organ cells. AP-2 is the most up-regulated of the four distinct adaptor protein complexes. Immunolocalization confirms the presence of AP-2 and clathrin in ameloblasts with strongest reactivity at the apical pole. These data suggest that the resorptive functions of enamel cells involve AP-2 mediated, clathrin dependent endocytosis, thus implying the likelihood of a specific membrane-bound receptor(s) of enamel matrix protein debris. The mRNA expression of other endocytosis-related gene products is also up-regulated during maturation including: lysosomal-associated membrane protein 1 (Lamp1), cluster of differentiation 63 and 68 (Cd63 and Cd68), ATPase, H+ transporting, lysosomal V0 subunit D2 (Atp6v0d2), ATPase, H+ transporting, lysosomal V1 subunit B2 (Atp6v1b2), chloride channel, voltage-sensitive 7 (Clcn7) and cathepsin K (Ctsk). Immunohistological data confirms the expression of a number of these proteins in maturation stage ameloblasts. The enamel of Cd63-null mice was also examined. Despite increased mRNA and protein expression in the enamel organ during maturation, the enamel of Cd63-null mice appeared normal. This may suggest inherent functional redundancies between Cd63 and related gene products, such as Lamp1 and Cd68. Ameloblast-like LS8 cells treated with the enamel matrix protein complex Emdogain® showed up-regulation of AP-2 and clathrin subunits, further supporting the existence of a membrane-bound receptor regulated pathway for the endocytosis of enamel matrix proteins. These data together

A novel method for evaluating microglial activation using ionized calcium-binding adaptor protein-1 staining : cell body to cell size ratio

NARCIS (Netherlands)

Hovens, Iris; Nyakas, Csaba; Schoemaker, Regina

2014-01-01

Aim: The aim was to validate a newly developed methodology of semi-automatic image analysis to analyze microglial morphology as marker for microglial activation in ionized calcium-binding adaptor protein-1 (IBA-1) stained brain sections. Methods: The novel method was compared to currently used

Stargazin regulates AMPA receptor trafficking through adaptor protein complexes during long-term depression

Science.gov (United States)

Matsuda, Shinji; Kakegawa, Wataru; Budisantoso, Timotheus; Nomura, Toshihiro; Kohda, Kazuhisa; Yuzaki, Michisuke

2013-11-01

Long-term depression (LTD) underlies learning and memory in various brain regions. Although postsynaptic AMPA receptor trafficking mediates LTD, its underlying molecular mechanisms remain largely unclear. Here we show that stargazin, a transmembrane AMPA receptor regulatory protein, forms a ternary complex with adaptor proteins AP-2 and AP-3A in hippocampal neurons, depending on its phosphorylation state. Inhibiting the stargazin-AP-2 interaction disrupts NMDA-induced AMPA receptor endocytosis, and inhibiting that of stargazin-AP-3A abrogates the late endosomal/lysosomal trafficking of AMPA receptors, thereby upregulating receptor recycling to the cell surface. Similarly, stargazin’s interaction with AP-2 or AP-3A is necessary for low-frequency stimulus-evoked LTD in CA1 hippocampal neurons. Thus, stargazin has a crucial role in NMDA-dependent LTD by regulating two trafficking pathways of AMPA receptors—transport from the cell surface to early endosomes and from early endosomes to late endosomes/lysosomes—through its sequential binding to AP-2 and AP-3A.

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....

Identification of actin binding protein, ABP-280, as a binding partner of human Lnk adaptor protein.

Science.gov (United States)

He, X; Li, Y; Schembri-King, J; Jakes, S; Hayashi, J

2000-08-01

Human Lnk (hLnk) is an adaptor protein with multiple functional domains that regulates T cell activation signaling. In order to identify cellular Lnk binding partners, a yeast two-hybrid screening of human spleen cDNA library was carried out using human hLnk as bait. A polypeptide sequence identical to the C-terminal segment of the actin binding protein (ABP-280) was identified as a hLnk binding protein. The expressed hLnk and the FLAG tagged C-terminal 673 amino acid residues of ABP-280 or the endogenous ABP-280 in COS-7 cells could be co-immunoprecipitated using antibodies either to hLnk, FLAG or ABP-280, respectively. Furthermore, immunofluorescence confocal microscope showed that hLnk and ABP-280 co-localized at the plasma membrane and at juxtanuclear region of COS-7 cells. In Jurkat cells, the endogenous hLnk also associates with the endogenous ABP-280 indicating that the association of these two proteins is physiological. The interacting domains of both proteins were mapped using yeast two-hybrid assays. Our results indicate that hLnk binds to the residues 2006-2454 (repeats 19-23C) of ABP-280. The domain in hLnk that associates with ABP-280 was mapped to an interdomain region of 56 amino acids between pleckstrin homology and Src homology 2 domains. These results suggest that hLnk may exert its regulatory role through its association with ABP-280.

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

Crystal Structures and Thermodynamic Analysis Reveal Distinct Mechanisms of CD28 Phosphopeptide Binding to the Src Homology 2 (SH2) Domains of Three Adaptor Proteins*

Science.gov (United States)

Inaba, Satomi; Numoto, Nobutaka; Ogawa, Shuhei; Morii, Hisayuki; Ikura, Teikichi; Abe, Ryo; Ito, Nobutoshi; Oda, Masayuki

2017-01-01

Full activation of T cells and differentiation into effector T cells are essential for many immune responses and require co-stimulatory signaling via the CD28 receptor. Extracellular ligand binding to CD28 recruits protein-tyrosine kinases to its cytoplasmic tail, which contains a YMNM motif. Following phosphorylation of the tyrosine, the proteins growth factor receptor-bound protein 2 (Grb2), Grb2-related adaptor downstream of Shc (Gads), and p85 subunit of phosphoinositide 3-kinase may bind to pYMNM (where pY is phosphotyrosine) via their Src homology 2 (SH2) domains, leading to downstream signaling to distinct immune pathways. These three adaptor proteins bind to the same site on CD28 with variable affinity, and all are important for CD28-mediated co-stimulatory function. However, the mechanism of how these proteins recognize and compete for CD28 is unclear. To visualize their interactions with CD28, we have determined the crystal structures of Gads SH2 and two p85 SH2 domains in complex with a CD28-derived phosphopeptide. The high resolution structures obtained revealed that, whereas the CD28 phosphopeptide bound to Gads SH2 is in a bent conformation similar to that when bound to Grb2 SH2, it adopts a more extended conformation when bound to the N- and C-terminal SH2 domains of p85. These differences observed in the peptide-protein interactions correlated well with the affinity and other thermodynamic parameters for each interaction determined by isothermal titration calorimetry. The detailed insight into these interactions reported here may inform the development of compounds that specifically inhibit the association of CD28 with these adaptor proteins to suppress excessive T cell responses, such as in allergies and autoimmune diseases. PMID:27927989

Crystal Structures and Thermodynamic Analysis Reveal Distinct Mechanisms of CD28 Phosphopeptide Binding to the Src Homology 2 (SH2) Domains of Three Adaptor Proteins.

Science.gov (United States)

Inaba, Satomi; Numoto, Nobutaka; Ogawa, Shuhei; Morii, Hisayuki; Ikura, Teikichi; Abe, Ryo; Ito, Nobutoshi; Oda, Masayuki

2017-01-20

Full activation of T cells and differentiation into effector T cells are essential for many immune responses and require co-stimulatory signaling via the CD28 receptor. Extracellular ligand binding to CD28 recruits protein-tyrosine kinases to its cytoplasmic tail, which contains a YMNM motif. Following phosphorylation of the tyrosine, the proteins growth factor receptor-bound protein 2 (Grb2), Grb2-related adaptor downstream of Shc (Gads), and p85 subunit of phosphoinositide 3-kinase may bind to pYMNM (where pY is phosphotyrosine) via their Src homology 2 (SH2) domains, leading to downstream signaling to distinct immune pathways. These three adaptor proteins bind to the same site on CD28 with variable affinity, and all are important for CD28-mediated co-stimulatory function. However, the mechanism of how these proteins recognize and compete for CD28 is unclear. To visualize their interactions with CD28, we have determined the crystal structures of Gads SH2 and two p85 SH2 domains in complex with a CD28-derived phosphopeptide. The high resolution structures obtained revealed that, whereas the CD28 phosphopeptide bound to Gads SH2 is in a bent conformation similar to that when bound to Grb2 SH2, it adopts a more extended conformation when bound to the N- and C-terminal SH2 domains of p85. These differences observed in the peptide-protein interactions correlated well with the affinity and other thermodynamic parameters for each interaction determined by isothermal titration calorimetry. The detailed insight into these interactions reported here may inform the development of compounds that specifically inhibit the association of CD28 with these adaptor proteins to suppress excessive T cell responses, such as in allergies and autoimmune diseases. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

Adaptor assembly for coupling turbine blades to rotor disks

Science.gov (United States)

Garcia-Crespo, Andres Jose; Delvaux, John McConnell

2014-09-23

An adaptor assembly for coupling a blade root of a turbine blade to a root slot of a rotor disk is described. The adaptor assembly includes a turbine blade having a blade root and an adaptor body having an adaptor root. The adaptor body defines a slot having an open end configured to receive the blade root of the turbine blade such that the adaptor root of the adaptor body and the blade root of the turbine blade are adjacent to one another when the blade root of the turbine blade is positioned within the slot. Both the adaptor root of the adaptor body and the blade root of the turbine blade are configured to be received within the root slot of the rotor disk.

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

Protein kinase A-induced internalization of Slack channels from the neuronal membrane occurs by adaptor protein-2/clathrin-mediated endocytosis.

Science.gov (United States)

Gururaj, Sushmitha; Evely, Katherine M; Pryce, Kerri D; Li, Jun; Qu, Jun; Bhattacharjee, Arin

2017-11-24

The sodium-activated potassium (K Na ) channel Kcnt1 (Slack) is abundantly expressed in nociceptor (pain-sensing) neurons of the dorsal root ganglion (DRG), where they transmit the large outward conductance I KNa and arbitrate membrane excitability. Slack channel expression at the DRG membrane is necessary for their characteristic firing accommodation during maintained stimulation, and reduced membrane channel density causes hyperexcitability. We have previously shown that in a pro-inflammatory state, a decrease in membrane channel expression leading to reduced Slack-mediated I KNa expression underlies DRG neuronal sensitization. An important component of the inflammatory milieu, PKA internalizes Slack channels from the DRG membrane, reduces I KNa , and produces DRG neuronal hyperexcitability when activated in cultured primary DRG neurons. Here, we show that this PKA-induced retrograde trafficking of Slack channels also occurs in intact spinal cord slices and that it is carried out by adaptor protein-2 (AP-2) via clathrin-mediated endocytosis. We provide mass spectrometric and biochemical evidence of an association of native neuronal AP-2 adaptor proteins with Slack channels, facilitated by a dileucine motif housed in the cytoplasmic Slack C terminus that binds AP-2. By creating a competitive peptide blocker of AP-2-Slack binding, we demonstrated that this interaction is essential for clathrin recruitment to the DRG membrane, Slack channel endocytosis, and DRG neuronal hyperexcitability after PKA activation. Together, these findings uncover AP-2 and clathrin as players in Slack channel regulation. Given the significant role of Slack in nociceptive neuronal excitability, the AP-2 clathrin-mediated endocytosis trafficking mechanism may enable targeting of peripheral and possibly, central neuronal sensitization. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

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...

Losses, Expansions, and Novel Subunit Discovery of Adaptor Protein Complexes in Haptophyte Algae.

Science.gov (United States)

Lee, Laura J Y; Klute, Mary J; Herman, Emily K; Read, Betsy; Dacks, Joel B

2015-11-01

The phylum Haptophyta (Diaphoratickes) contains marine algae that perform biomineralization, extruding large, distinctive calcium carbonate scales (coccoliths) that completely cover the cell. Coccolith production is an important part of global carbon cycling; however, the membrane trafficking pathway by which they are secreted has not yet been elucidated. In most eukaryotes, post-Golgi membrane trafficking involves five heterotetrameric adaptor protein (AP) complexes, which impart cargo selection specificity. To better understand coccolith secretion, we performed comparative genomic, phylogenetic, and transcriptomic analyses of the AP complexes in Emiliania huxleyi strains 92A, Van556, EH2, and CCMP1516, and related haptophytes Gephyrocapsa oceanica and Isochrysis galbana; the latter has lost the ability to biomineralize. We show that haptophytes have a modified membrane trafficking system (MTS), as we found both AP subunit losses and duplications. Additionally, we identified a single conserved subunit of the AP-related TSET complex, whose expression suggests a functional role in membrane trafficking. Finally, we detected novel alpha adaptin ear and gamma adaptin ear proteins, the first of their kind to be described outside of opisthokonts. These novel ear proteins and the sculpting of the MTS may support the capacity for biomineralization in haptophytes, enhancing their ability to perform this highly specialized form of secretion. Copyright © 2015 Elsevier GmbH. All rights reserved.

Conformational changes in the AAA ATPase p97–p47 adaptor complex

Science.gov (United States)

Beuron, Fabienne; Dreveny, Ingrid; Yuan, Xuemei; Pye, Valerie E; Mckeown, Ciaran; Briggs, Louise C; Cliff, Matthew J; Kaneko, Yayoi; Wallis, Russell; Isaacson, Rivka L; Ladbury, John E; Matthews, Steve J; Kondo, Hisao; Zhang, Xiaodong; Freemont, Paul S

2006-01-01

The AAA+ATPase p97/VCP, helped by adaptor proteins, exerts its essential role in cellular events such as endoplasmic reticulum-associated protein degradation or the reassembly of Golgi, ER and the nuclear envelope after mitosis. Here, we report the three-dimensional cryo-electron microscopy structures at ∼20 Å resolution in two nucleotide states of the endogenous hexameric p97 in complex with a recombinant p47 trimer, one of the major p97 adaptor proteins involved in membrane fusion. Depending on the nucleotide state, we observe the p47 trimer to be in two distinct arrangements on top of the p97 hexamer. By combining the EM data with NMR and other biophysical measurements, we propose a model of ATP-dependent p97(N) domain motions that lead to a rearrangement of p47 domains, which could result in the disassembly of target protein complexes. PMID:16601695

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.

Localization of the kinesin adaptor proteins trafficking kinesin proteins 1 and 2 in primary cultures of hippocampal pyramidal and cortical neurons.

Science.gov (United States)

Loss, Omar; Stephenson, F Anne

2015-07-01

Neuronal function requires regulated anterograde and retrograde trafficking of mitochondria along microtubules by using the molecular motors kinesin and dynein. Previous work has established that trafficking kinesin proteins (TRAKs),TRAK1 and TRAK2, are kinesin adaptor proteins that link mitochondria to kinesin motor proteins via an acceptor protein in the mitochondrial outer membrane, etc. the Rho GTPase Miro. Recent studies have shown that TRAK1 preferentially controls mitochondrial transport in axons of hippocampal neurons by virtue of its binding to both kinesin and dynein motor proteins, whereas TRAK2 controls mitochondrial transport in dendrites resulting from its binding to dynein. This study further investigates the subcellular localization of TRAK1 and TRAK2 in primary cultures of hippocampal and cortical neurons by using both commercial antibodies and anti-TRAK1 and anti-TRAK2 antibodies raised in our own laboratory (in-house). Whereas TRAK1 was prevalently localized in axons of hippocampal and cortical neurons, TRAK2 was more prevalent in dendrites of hippocampal neurons. In cortical neurons, TRAK2 was equally distributed between axons and dendrites. Some qualitative differences were observed between commercial and in-house-generated antibody immunostaining. © 2015 Wiley Periodicals, Inc.

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.

SH2/SH3 adaptor proteins can link tyrosine kinases to a Ste20-related protein kinase, HPK1.

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Anafi, M; Kiefer, F; Gish, G D; Mbamalu, G; Iscove, N N; Pawson, T

1997-10-31

Ste20-related protein kinases have been implicated as regulating a range of cellular responses, including stress-activated protein kinase pathways and the control of cytoskeletal architecture. An important issue involves the identities of the upstream signals and regulators that might control the biological functions of mammalian Ste20-related protein kinases. HPK1 is a protein-serine/threonine kinase that possesses a Ste20-like kinase domain, and in transfected cells activates a protein kinase pathway leading to the stress-activated protein kinase SAPK/JNK. Here we have investigated candidate upstream regulators that might interact with HPK1. HPK1 possesses an N-terminal catalytic domain and an extended C-terminal tail with four proline-rich motifs. The SH3 domains of Grb2 bound in vitro to specific proline-rich motifs in the HPK1 tail and functioned synergistically to direct the stable binding of Grb2 to HPK1 in transfected Cos1 cells. Epidermal growth factor (EGF) stimulation did not affect the binding of Grb2 to HPK1 but induced recruitment of the Grb2.HPK1 complex to the autophosphorylated EGF receptor and to the Shc docking protein. Several activated receptor and cytoplasmic tyrosine kinases, including the EGF receptor, stimulated the tyrosine phosphorylation of the HPK1 serine/threonine kinase. These results suggest that HPK1, a mammalian Ste20-related protein-serine/threonine kinase, can potentially associate with protein-tyrosine kinases through interactions mediated by SH2/SH3 adaptors such as Grb2. Such interaction may provide a possible mechanism for cross-talk between distinct biochemical pathways following the activation of tyrosine kinases.

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

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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.

CD6 and Linker of Activated T Cells are Potential Interaction Partners for T Cell-Specific Adaptor Protein.

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Hem, C D; Ekornhol, M; Granum, S; Sundvold-Gjerstad, V; Spurkland, A

2017-02-01

The T cell-specific adaptor protein (TSAd) contains several protein interaction domains, and is merging as a modulator of T cell activation. Several interaction partners for the TSAd proline-rich region and phosphotyrosines have been identified, including the Src and Tec family kinases lymphocyte-specific protein tyrosine kinase and interleukin 2-inducible T cell kinase. Via its Src homology 2 (SH2) domain, TSAd may thus function as a link between these enzymes and other signalling molecules. However, few binding partners to the TSAd SH2 domain in T cells are hitherto known. Through the use of in silico ligand prediction, peptide spot arrays, pull-down and immunoprecipitation experiments, we here report novel interactions between the TSAd SH2 domain and CD6 phosphotyrosine (pTyr) 629 and linker of activated T cells (LAT) pTyr 171 , pTyr 191 and pTyr 226 . © 2016 The Foundation for the Scandinavian Journal of Immunology.

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

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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.

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

Science.gov (United States)

Chia, Wei Sheng; Chia, Diana Xueqi; Rao, Feng; Bar Nun, Shoshana; Geifman Shochat, Susana

2012-01-01

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.

Adaptor proteins intersectin 1 and 2 bind similar proline-rich ligands but are differentially recognized by SH2 domain-containing proteins.

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Olga Novokhatska

Full Text Available BACKGROUND: Scaffolding proteins of the intersectin (ITSN family, ITSN1 and ITSN2, are crucial for the initiation stage of clathrin-mediated endocytosis. These proteins are closely related but have implications in distinct pathologies. To determine how these proteins could be separated in certain cell pathways we performed a comparative study of ITSNs. METHODOLOGY/PRINCIPAL FINDINGS: We have shown that endogenous ITSN1 and ITSN2 colocalize and form a complex in cells. A structural comparison of five SH3 domains, which mediated most ITSNs protein-protein interactions, demonstrated a similarity of their ligand-binding sites. We showed that the SH3 domains of ITSN2 bound well-established interactors of ITSN1 as well as newly identified ITSNs protein partners. A search for a novel interacting interface revealed multiple tyrosines that could be phosphorylated in ITSN2. Phosphorylation of ITSN2 isoforms but not ITSN1 short isoform was observed in various cell lines. EGF stimulation of HeLa cells enhanced tyrosine phosphorylation of ITSN2 isoforms and enabled their recognition by the SH2 domains of the Fyn, Fgr and Abl1 kinases, the regulatory subunit of PI3K, the adaptor proteins Grb2 and Crk, and phospholipase C gamma. The SH2 domains mentioned were unable to bind ITSN1 short isoform. CONCLUSIONS/SIGNIFICANCE: Our results indicate that during evolution of vertebrates ITSN2 acquired a novel protein-interaction interface that allows its specific recognition by the SH2 domains of signaling proteins. We propose that these data could be important to understand the functional diversity of paralogous ITSN proteins.

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

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,…

Biochemical and genetic analysis of the Drk SH2/SH3 adaptor protein of Drosophila.

Science.gov (United States)

Raabe, T; Olivier, J P; Dickson, B; Liu, X; Gish, G D; Pawson, T; Hafen, E

1995-06-01

The Drk SH3-SH2-SH3 adaptor protein has been genetically identified in a screen for rate-limiting components acting downstream of the Sevenless (Sev) receptor tyrosine kinase in the developing eye of Drosophila. It provides a link between the activated Sev receptor and Sos, a guanine nucleotide release factor that activates Ras1. We have used a combined biochemical and genetic approach to study the interactions between Sev, Drk and Sos. We show that Tyr2546 in the cytoplasmic tail of Sev is required for Drk binding, probably because it provides a recognition site for the Drk SH2 domain. Interestingly, a mutation at this site does not completely block Sev function in vivo. This may suggest that Sev can signal in a Drk-independent, parallel pathway or that Drk can also bind to an intermediate docking protein. Analysis of the Drk-Sos interaction has identified a high affinity binding site for Drk SH3 domains in the Sos tail. We show that the N-terminal Drk SH3 domain is primarily responsible for binding to the tail of Sos in vitro, and for signalling to Ras in vivo.

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

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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.

The motogenic and mitogenic responses to HGF are amplified by the Shc adaptor protein

DEFF Research Database (Denmark)

Pelicci, G; Giordano, S; Zhen, Z

1995-01-01

The receptor of Hepatocyte Growth Factor-Scatter Factor (HGF) is a tyrosine kinase which regulates cell motility and growth. After ligand-induced tyrosine phosphorylation, the HGF receptor associates with the Shc adaptor, via the SH2 domain. Site-directed mutagenesis of the HGF receptor indicates...

Structural complementarity of Toll/interleukin-1 receptor domains in Toll-like receptors and the adaptors Mal and MyD88.

Science.gov (United States)

Dunne, Aisling; Ejdeback, Mikael; Ludidi, Phumzile L; O'Neill, Luke A J; Gay, Nicholas J

2003-10-17

The Toll/interleukin 1 receptor (TIR) domain is a region found in the cytoplasmic tails of members of the Toll-like receptor/interleukin-1 receptor superfamily. The domain is essential for signaling and is also found in the adaptor proteins Mal (MyD88 adaptor-like) and MyD88, which function to couple activation of the receptor to downstream signaling components. Experimental structures of two Toll/interleukin 1 receptor domains reveal a alpha-beta-fold similar to that of the bacterial chemotaxis protein CheY, and other evidence suggests that the adaptors can make heterotypic interactions with both the receptors and themselves. Here we show that the purified TIR domains of Mal and MyD88 can form stable heterodimers and also that Mal homodimers and oligomers are dissociated in the presence of ATP. To identify structural features that may contribute to the formation of signaling complexes, we produced models of the TIR domains from human Toll-like receptor 4 (TLR4), Mal, and MyD88. We found that although the overall fold is conserved the electrostatic surface potentials are quite distinct. Docking studies of the models suggest that Mal and MyD88 bind to different regions in TLRs 2 and 4, a finding consistent with a cooperative role of the two adaptors in signaling. Mal and MyD88 are predicted to interact at a third non-overlapping site, suggesting that the receptor and adaptors may form heterotetrameric complexes. The theoretical model of the interactions is supported by experimental data from glutathione S-transferase pull-downs and co-immunoprecipitations. Neither theoretical nor experimental data suggest a direct role for the conserved proline in the BB-loop in the association of TLR4, Mal, and MyD88. Finally we show a sequence relationship between the Drosophila protein Tube and Mal that may indicate a functional equivalence of these two adaptors in the Drosophila and vertebrate Toll pathways.

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.

Expression analysis of the Toll-like receptor and TIR domain adaptor families of zebrafish.

NARCIS (Netherlands)

Meijer, A.H.; Krens, SF Gabby; Rodriguez, IA Medina; He, S; Bitter, W.; Snaar-Jagalska, B Ewa; Spaink, H.P.

2004-01-01

The zebrafish genomic sequence database was analysed for the presence of genes encoding members of the Toll-like receptors (TLR) and interleukin receptors (IL-R) and associated adaptor proteins containing a TIR domain. The resulting predictions show the presence of one or more counterparts for the

The adaptor protein CrkII regulates IGF-1-induced biological behaviors of pancreatic ductal adenocarcinoma.

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Liu, Rui; Wang, Qing; Xu, Guangying; Li, Kexin; Zhou, Lingli; Xu, Baofeng

2016-01-01

Recently, the adaptor protein CrkII has been proved to function in initiating signals for proliferation and invasion in some malignancies. However, the specific mechanisms underlying insulin-like growth factor 1 (IGF-1)-CrkII signaling-induced proliferation of pancreatic ductal adenocarcinoma (PDAC) were not unraveled. In this work, PDAC tissues and cell lines were subjected to in vitro and in vivo assays. Our findings showed that CrkII was abundantly expressed in PDAC tissues and closely correlated with tumor-node-metastasis (TNM) stage and invasion. When cells were subjected to si-CrkII, si-CrkII inhibited IGF-1-mediated PDAC cell growth. In vitro, we demonstrated the upregulation of CrkII, p-Erk1/2, and p-Akt occurring in IGF-1-treated PDAC cells. Conversely, si-CrkII affected upregulation of CrkII, p-Erk1/2, and p-Akt. In addition, cell cycle and in vivo assay identified that knockdown of CrkII inhibited the entry of G1 into S phase and the increase of PDAC tumor weight. In conclusion, CrkII mediates IGF-1 signaling and further balanced PDAC biological behaviors via Erk1/2 and Akt pathway, which indicates that CrkII gene and protein may act as an effective target for the treatment of PDAC.

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.

Tetraspanins and Transmembrane Adaptor Proteins As Plasma Membrane Organizers-Mast Cell Case.

Science.gov (United States)

Halova, Ivana; Draber, Petr

2016-01-01

The plasma membrane contains diverse and specialized membrane domains, which include tetraspanin-enriched domains (TEMs) and transmembrane adaptor protein (TRAP)-enriched domains. Recent biophysical, microscopic, and functional studies indicated that TEMs and TRAP-enriched domains are involved in compartmentalization of physicochemical events of such important processes as immunoreceptor signal transduction and chemotaxis. Moreover, there is evidence of a cross-talk between TEMs and TRAP-enriched domains. In this review we discuss the presence and function of such domains and their crosstalk using mast cells as a model. The combined data based on analysis of selected mast cell-expressed tetraspanins [cluster of differentiation (CD)9, CD53, CD63, CD81, CD151)] or TRAPs [linker for activation of T cells (LAT), non-T cell activation linker (NTAL), and phosphoprotein associated with glycosphingolipid-enriched membrane microdomains (PAG)] using knockout mice or specific antibodies point to a diversity within these two families and bring evidence of the important roles of these molecules in signaling events. An example of this diversity is physical separation of two TRAPs, LAT and NTAL, which are in many aspects similar but show plasma membrane location in different microdomains in both non-activated and activated cells. Although our understanding of TEMs and TRAP-enriched domains is far from complete, pharmaceutical applications of the knowledge about these domains are under way.

Adaptor protein containing PH domain, PTB domain and leucine zipper (APPL1) regulates the protein level of EGFR by modulating its trafficking

International Nuclear Information System (INIS)

Lee, Jae-Rin; Hahn, Hwa-Sun; Kim, Young-Hoon; Nguyen, Hong-Hoa; Yang, Jun-Mo; Kang, Jong-Sun; Hahn, Myong-Joon

2011-01-01

Highlights: ► APPL1 regulates the protein level of EGFR in response to EGF stimulation. ► Depletion of APPL1 accelerates the movement of EGF/EGFR from the cell surface to the perinuclear region in response to EGF. ► Knockdown of APPL1 enhances the activity of Rab5. -- Abstract: The EGFR-mediated signaling pathway regulates multiple biological processes such as cell proliferation, survival and differentiation. Previously APPL1 (adaptor protein containing PH domain, PTB domain and leucine zipper 1) has been reported to function as a downstream effector of EGF-initiated signaling. Here we demonstrate that APPL1 regulates EGFR protein levels in response to EGF stimulation. Overexpression of APPL1 enhances EGFR stabilization while APPL1 depletion by siRNA reduces EGFR protein levels. APPL1 depletion accelerates EGFR internalization and movement of EGF/EGFR from cell surface to the perinuclear region in response to EGF treatment. Conversely, overexpression of APPL1 decelerates EGFR internalization and translocation of EGF/EGFR to the perinuclear region. Furthermore, APPL1 depletion enhances the activity of Rab5 which is involved in internalization and trafficking of EGFR and inhibition of Rab5 in APPL1-depleted cells restored EGFR levels. Consistently, APPL1 depletion reduced activation of Akt, the downstream signaling effector of EGFR and this is restored by inhibition of Rab5. These findings suggest that APPL1 is required for EGFR signaling by regulation of EGFR stabilities through inhibition of Rab5.

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

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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.

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.

Human kidney anion exchanger 1 interacts with adaptor-related protein complex 1 {mu}1A (AP-1 mu1A)

Energy Technology Data Exchange (ETDEWEB)

Sawasdee, Nunghathai; Junking, Mutita [Division of Medical Molecular Biology and BIOTEC-Medical Biotechnology Unit, Department of Research and Development, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700 (Thailand); Ngaojanlar, Piengpaga [Division of Medical Molecular Biology and BIOTEC-Medical Biotechnology Unit, Department of Research and Development, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700 (Thailand); Department of Immunology and Graduate Program in Immunology, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700 (Thailand); Sukomon, Nattakan; Ungsupravate, Duangporn [Division of Medical Molecular Biology and BIOTEC-Medical Biotechnology Unit, Department of Research and Development, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700 (Thailand); Limjindaporn, Thawornchai [Division of Medical Molecular Biology and BIOTEC-Medical Biotechnology Unit, Department of Research and Development, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700 (Thailand); Department of Anatomy, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700 (Thailand); Akkarapatumwong, Varaporn [Institute of Molecular Biosciences, Mahidol University at Salaya Campus, Nakorn Pathom 73170 (Thailand); Noisakran, Sansanee [Division of Medical Molecular Biology and BIOTEC-Medical Biotechnology Unit, Department of Research and Development, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700 (Thailand); Yenchitsomanus, Pa-thai, E-mail: grpye@mahidol.ac.th [Division of Medical Molecular Biology and BIOTEC-Medical Biotechnology Unit, Department of Research and Development, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700 (Thailand)

2010-10-08

Research highlights: {yields} Trafficking defect of kAE1 is a cause of dRTA but trafficking pathway of kAE1 has not been clearly described. {yields} Adaptor-related protein complex 1 {mu}1A (AP-1 mu1A) was firstly reported to interact with kAE1. {yields} The interacting site for AP-1 mu1A on Ct-kAE1 was found to be Y904DEV907, a subset of YXXO motif. {yields} AP-1 mu1A knockdown showed a marked reduction of kAE1 on the cell membrane and its accumulation in endoplasmic reticulum. {yields} AP-1 mu1A has a critical role in kAE1 trafficking to the plasma membrane. -- Abstract: Kidney anion exchanger 1 (kAE1) mediates chloride (Cl{sup -}) and bicarbonate (HCO{sub 3}{sup -}) exchange at the basolateral membrane of kidney {alpha}-intercalated cells. Impaired trafficking of kAE1 leads to defect of the Cl{sup -}/HCO{sub 3}{sup -} exchange at the basolateral membrane and failure of proton (H{sup +}) 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 {mu}1A (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

The AP2 clathrin adaptor protein complex regulates the abundance of GLR-1 glutamate receptors in the ventral nerve cord of Caenorhabditis elegans.

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Garafalo, Steven D; Luth, Eric S; Moss, Benjamin J; Monteiro, Michael I; Malkin, Emily; Juo, Peter

2015-05-15

Regulation of glutamate receptor (GluR) abundance at synapses by clathrin-mediated endocytosis can control synaptic strength and plasticity. We take advantage of viable, null mutations in subunits of the clathrin adaptor protein 2 (AP2) complex in Caenorhabditis elegans to characterize the in vivo role of AP2 in GluR trafficking. In contrast to our predictions for an endocytic adaptor, we found that levels of the GluR GLR-1 are decreased at synapses in the ventral nerve cord (VNC) of animals with mutations in the AP2 subunits APM-2/μ2, APA-2/α, or APS-2/σ2. Rescue experiments indicate that APM-2/μ2 functions in glr-1-expressing interneurons and the mature nervous system to promote GLR-1 levels in the VNC. Genetic analyses suggest that APM-2/μ2 acts upstream of GLR-1 endocytosis in the VNC. Consistent with this, GLR-1 accumulates in cell bodies of apm-2 mutants. However, GLR-1 does not appear to accumulate at the plasma membrane of the cell body as expected, but instead accumulates in intracellular compartments including Syntaxin-13- and RAB-14-labeled endosomes. This study reveals a novel role for the AP2 clathrin adaptor in promoting the abundance of GluRs at synapses in vivo, and implicates AP2 in the regulation of GluR trafficking at an early step in the secretory pathway. © 2015 Garafalo et al. This article is distributed by The American Society for Cell Biology under license from the author(s). Two months after publication it is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

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

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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…

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

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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.

Tetraspanins and Transmembrane Adaptor Proteins as Plasma Membrane Organizers – Mast Cell Case

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Ivana eHalova

2016-05-01

Full Text Available The plasma membrane contains diverse and specialized membrane domains, which include tetraspanin-enriched domains (TEMs and transmembrane adaptor protein (TRAP-enriched domains. Recent biophysical, microscopic and functional studies indicated that TEMs and TRAP-enriched domains are involved in compartmentalization of physicochemical events of such important processes as immunoreceptor signal transduction and chemotaxis. Moreover, there is evidence of a cross-talk between TEMs and TRAP-enriched domains. In this review we discuss the presence and function of such domains and their crosstalk using mast cells as a model. The combined data based on analysis of selected mast cell-expressed tetraspanins [cluster of differentiation (CD9, CD53, CD63, CD81, CD151] or TRAPs [linker for activation of T cells (LAT, non-T cell activation linker (NTAL, and phosphoprotein associated with glycosphingolipid-enriched membrane microdomains (PAG] using knockout mice or specific antibodies point to a diversity within these two families and bring evidence of the important roles of these molecules in signaling events. An example of this diversity is physical separation of two TRAPs, LAT and NTAL, which are in many aspects similar but show plasma membrane location in different microdomains in both non-activated and activated cells. Although our understanding of TEMs and TRAP-enriched domains is far from complete, pharmaceutical applications of the knowledge about these domains are under way.

Adaptor protein complex 2-mediated endocytosis is crucial for male reproductive organ development in Arabidopsis.

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Kim, Soo Youn; Xu, Zheng-Yi; Song, Kyungyoung; Kim, Dae Heon; Kang, Hyangju; Reichardt, Ilka; Sohn, Eun Ju; Friml, Jirí; Juergens, Gerd; Hwang, Inhwan

2013-08-01

Fertilization in flowering plants requires the temporal and spatial coordination of many developmental processes, including pollen production, anther dehiscence, ovule production, and pollen tube elongation. However, it remains elusive as to how this coordination occurs during reproduction. Here, we present evidence that endocytosis, involving heterotetrameric adaptor protein complex 2 (AP-2), plays a crucial role in fertilization. An Arabidopsis thaliana mutant ap2m displays multiple defects in pollen production and viability, as well as elongation of staminal filaments and pollen tubes, all of which are pivotal processes needed for fertilization. Of these abnormalities, the defects in elongation of staminal filaments and pollen tubes were partially rescued by exogenous auxin. Moreover, DR5rev:GFP (for green fluorescent protein) expression was greatly reduced in filaments and anthers in ap2m mutant plants. At the cellular level, ap2m mutants displayed defects in both endocytosis of N-(3-triethylammonium-propyl)-4-(4-diethylaminophenylhexatrienyl) pyridinium dibromide, a lypophilic dye used as an endocytosis marker, and polar localization of auxin-efflux carrier PIN FORMED2 (PIN2) in the stamen filaments. Moreover, these defects were phenocopied by treatment with Tyrphostin A23, an inhibitor of endocytosis. Based on these results, we propose that AP-2-dependent endocytosis plays a crucial role in coordinating the multiple developmental aspects of male reproductive organs by modulating cellular auxin level through the regulation of the amount and polarity of PINs.

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)

Adaptor protein Lnk negatively regulates the mutant MPL, MPLW515L associated with myeloproliferative disorders.

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Gery, Sigal; Gueller, Saskia; Chumakova, Katya; Kawamata, Norihiko; Liu, Liqin; Koeffler, H Phillip

2007-11-01

Recently, activating myeloproliferative leukemia virus oncogene (MPL) mutations, MPLW515L/K, were described in myeloproliferative disorder (MPD) patients. MPLW515L leads to activation of downstream signaling pathways and cytokine-independent proliferation in hematopoietic cells. The adaptor protein Lnk is a negative regulator of several cytokine receptors, including MPL. We show that overexpression of Lnk in Ba/F3-MPLW515L cells inhibits cytokine-independent growth, while suppression of Lnk in UT7-MPLW515L cells enhances proliferation. Lnk blocks the activation of Jak2, Stat3, Erk, and Akt in these cells. Furthermore, MPLW515L-expressing cells are more susceptible to Lnk inhibitory functions than their MPL wild-type (MPLWT)-expressing counterparts. Lnk associates with activated MPLWT and MPLW515L and colocalizes with the receptors at the plasma membrane. The SH2 domain of Lnk is essential for its binding and for its down-regulation of MPLWT and MPLW515L. Lnk itself is tyrosine-phosphorylated following thrombopoietin stimulation. Further elucidating the cellular pathways that attenuate MPLW515L will provide insight into the pathogenesis of MPD and could help develop specific therapeutic approaches.

Protein complex prediction in large ontology attributed protein-protein interaction networks.

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Zhang, Yijia; Lin, Hongfei; Yang, Zhihao; Wang, Jian; Li, Yanpeng; Xu, Bo

2013-01-01

Protein complexes are important for unraveling the secrets of cellular organization and function. Many computational approaches have been developed to predict protein complexes in protein-protein interaction (PPI) networks. However, most existing approaches focus mainly on the topological structure of PPI networks, and largely ignore the gene ontology (GO) annotation information. In this paper, we constructed ontology attributed PPI networks with PPI data and GO resource. After constructing ontology attributed networks, we proposed a novel approach called CSO (clustering based on network structure and ontology attribute similarity). Structural information and GO attribute information are complementary in ontology attributed networks. CSO can effectively take advantage of the correlation between frequent GO annotation sets and the dense subgraph for protein complex prediction. Our proposed CSO approach was applied to four different yeast PPI data sets and predicted many well-known protein complexes. The experimental results showed that CSO was valuable in predicting protein complexes and achieved state-of-the-art performance.

Signaling by Kit protein-tyrosine kinase--the stem cell factor receptor.

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Roskoski, Robert

2005-11-11

Signaling by stem cell factor and Kit, its receptor, plays important roles in gametogenesis, hematopoiesis, mast cell development and function, and melanogenesis. Moreover, human and mouse embryonic stem cells express Kit transcripts. Stem cell factor exists as both a soluble and a membrane-bound glycoprotein while Kit is a receptor protein-tyrosine kinase. The complete absence of stem cell factor or Kit is lethal. Deficiencies of either produce defects in red and white blood cell production, hypopigmentation, and sterility. Gain-of-function mutations of Kit are associated with several human neoplasms including acute myelogenous leukemia, gastrointestinal stromal tumors, and mastocytomas. Kit consists of an extracellular domain, a transmembrane segment, a juxtamembrane segment, and a protein kinase domain that contains an insert of about 80 amino acid residues. Binding of stem cell factor to Kit results in receptor dimerization and activation of protein kinase activity. The activated receptor becomes autophosphorylated at tyrosine residues that serve as docking sites for signal transduction molecules containing SH2 domains. The adaptor protein APS, Src family kinases, and Shp2 tyrosyl phosphatase bind to phosphotyrosine 568. Shp1 tyrosyl phosphatase and the adaptor protein Shc bind to phosphotyrosine 570. C-terminal Src kinase homologous kinase and the adaptor Shc bind to both phosphotyrosines 568 and 570. These residues occur in the juxtamembrane segment of Kit. Three residues in the kinase insert domain are phosphorylated and attract the adaptor protein Grb2 (Tyr703), phosphatidylinositol 3-kinase (Tyr721), and phospholipase Cgamma (Tyr730). Phosphotyrosine 900 in the distal kinase domain binds phosphatidylinositol 3-kinase which in turn binds the adaptor protein Crk. Phosphotyrosine 936, also in the distal kinase domain, binds the adaptor proteins APS, Grb2, and Grb7. Kit has the potential to participate in multiple signal transduction pathways as a result of

Spectral affinity in protein networks.

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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

NSP-CAS Protein Complexes: Emerging Signaling Modules in Cancer.

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Wallez, Yann; Mace, Peter D; Pasquale, Elena B; Riedl, Stefan J

2012-05-01

The CAS (CRK-associated substrate) family of adaptor proteins comprises 4 members, which share a conserved modular domain structure that enables multiple protein-protein interactions, leading to the assembly of intracellular signaling platforms. Besides their physiological role in signal transduction downstream of a variety of cell surface receptors, CAS proteins are also critical for oncogenic transformation and cancer cell malignancy through associations with a variety of regulatory proteins and downstream effectors. Among the regulatory partners, the 3 recently identified adaptor proteins constituting the NSP (novel SH2-containing protein) family avidly bind to the conserved carboxy-terminal focal adhesion-targeting (FAT) domain of CAS proteins. NSP proteins use an anomalous nucleotide exchange factor domain that lacks catalytic activity to form NSP-CAS signaling modules. Additionally, the NSP SH2 domain can link NSP-CAS signaling assemblies to tyrosine-phosphorylated cell surface receptors. NSP proteins can potentiate CAS function by affecting key CAS attributes such as expression levels, phosphorylation state, and subcellular localization, leading to effects on cell adhesion, migration, and invasion as well as cell growth. The consequences of these activities are well exemplified by the role that members of both families play in promoting breast cancer cell invasiveness and resistance to antiestrogens. In this review, we discuss the intriguing interplay between the NSP and CAS families, with a particular focus on cancer signaling networks.

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

Spectral affinity in protein networks

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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

Absence of the inflammasome adaptor ASC reduces hypoxia-induced pulmonary hypertension in mice.

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Cero, Fadila Telarevic; Hillestad, Vigdis; Sjaastad, Ivar; Yndestad, Arne; Aukrust, Pål; Ranheim, Trine; Lunde, Ida Gjervold; Olsen, Maria Belland; Lien, Egil; Zhang, Lili; Haugstad, Solveig Bjærum; Løberg, Else Marit; Christensen, Geir; Larsen, Karl-Otto; Skjønsberg, Ole Henning

2015-08-15

Pulmonary hypertension is a serious condition that can lead to premature death. The mechanisms involved are incompletely understood although a role for the immune system has been suggested. Inflammasomes are part of the innate immune system and consist of the effector caspase-1 and a receptor, where nucleotide-binding oligomerization domain-like receptor pyrin domain-containing 3 (NLRP3) is the best characterized and interacts with the adaptor protein apoptosis-associated speck-like protein containing a caspase-recruitment domain (ASC). To investigate whether ASC and NLRP3 inflammasome components are involved in hypoxia-induced pulmonary hypertension, we utilized mice deficient in ASC and NLRP3. Active caspase-1, IL-18, and IL-1β, which are regulated by inflammasomes, were measured in lung homogenates in wild-type (WT), ASC(-/-), and NLRP3(-/-) mice, and phenotypical changes related to pulmonary hypertension and right ventricular remodeling were characterized after hypoxic exposure. Right ventricular systolic pressure (RVSP) of ASC(-/-) mice was significantly lower than in WT exposed to hypoxia (40.8 ± 1.5 mmHg vs. 55.8 ± 2.4 mmHg, P right ventricular remodeling. RVSP of NLRP3(-/-) mice exposed to hypoxia was not significantly altered compared with WT hypoxia. Whereas hypoxia increased protein levels of caspase-1, IL-18, and IL-1β in WT and NLRP3(-/-) mice, this response was absent in ASC(-/-) mice. Moreover, ASC(-/-) mice displayed reduced muscularization and collagen deposition around arteries. In conclusion, hypoxia-induced elevated right ventricular pressure and remodeling were attenuated in mice lacking the inflammasome adaptor protein ASC, suggesting that inflammasomes play an important role in the pathogenesis of pulmonary hypertension. Copyright © 2015 the American Physiological Society.

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

Study on the isothermal forging process of MB26 magnesium alloy adaptor

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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.

Unified Alignment of Protein-Protein Interaction Networks.

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Malod-Dognin, Noël; Ban, Kristina; Pržulj, Nataša

2017-04-19

Paralleling the increasing availability of protein-protein interaction (PPI) network data, several network alignment methods have been proposed. Network alignments have been used to uncover functionally conserved network parts and to transfer annotations. However, due to the computational intractability of the network alignment problem, aligners are heuristics providing divergent solutions and no consensus exists on a gold standard, or which scoring scheme should be used to evaluate them. We comprehensively evaluate the alignment scoring schemes and global network aligners on large scale PPI data and observe that three methods, HUBALIGN, L-GRAAL and NATALIE, regularly produce the most topologically and biologically coherent alignments. We study the collective behaviour of network aligners and observe that PPI networks are almost entirely aligned with a handful of aligners that we unify into a new tool, Ulign. Ulign enables complete alignment of two networks, which traditional global and local aligners fail to do. Also, multiple mappings of Ulign define biologically relevant soft clusterings of proteins in PPI networks, which may be used for refining the transfer of annotations across networks. Hence, PPI networks are already well investigated by current aligners, so to gain additional biological insights, a paradigm shift is needed. We propose such a shift come from aligning all available data types collectively rather than any particular data type in isolation from others.

A transgenic Drosophila model demonstrates that the Helicobacter pylori CagA protein functions as a eukaryotic Gab adaptor.

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Crystal M Botham

2008-05-01

Full Text Available Infection with the human gastric pathogen Helicobacter pylori is associated with a spectrum of diseases including gastritis, peptic ulcers, gastric adenocarcinoma, and gastric mucosa-associated lymphoid tissue lymphoma. The cytotoxin-associated gene A (CagA protein of H. pylori, which is translocated into host cells via a type IV secretion system, is a major risk factor for disease development. Experiments in gastric tissue culture cells have shown that once translocated, CagA activates the phosphatase SHP-2, which is a component of receptor tyrosine kinase (RTK pathways whose over-activation is associated with cancer formation. Based on CagA's ability to activate SHP-2, it has been proposed that CagA functions as a prokaryotic mimic of the eukaryotic Grb2-associated binder (Gab adaptor protein, which normally activates SHP-2. We have developed a transgenic Drosophila model to test this hypothesis by investigating whether CagA can function in a well-characterized Gab-dependent process: the specification of photoreceptors cells in the Drosophila eye. We demonstrate that CagA expression is sufficient to rescue photoreceptor development in the absence of the Drosophila Gab homologue, Daughter of Sevenless (DOS. Furthermore, CagA's ability to promote photoreceptor development requires the SHP-2 phosphatase Corkscrew (CSW. These results provide the first demonstration that CagA functions as a Gab protein within the tissue of an organism and provide insight into CagA's oncogenic potential. Since many translocated bacterial proteins target highly conserved eukaryotic cellular processes, such as the RTK signaling pathway, the transgenic Drosophila model should be of general use for testing the in vivo function of bacterial effector proteins and for identifying the host genes through which they function.

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

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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,......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 (In...

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

Adaptor Protein Complex 2–Mediated Endocytosis Is Crucial for Male Reproductive Organ Development in Arabidopsis[W

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Kim, Soo Youn; Xu, Zheng-Yi; Song, Kyungyoung; Kim, Dae Heon; Kang, Hyangju; Reichardt, Ilka; Sohn, Eun Ju; Friml, Jiří; Juergens, Gerd; Hwang, Inhwan

2013-01-01

Fertilization in flowering plants requires the temporal and spatial coordination of many developmental processes, including pollen production, anther dehiscence, ovule production, and pollen tube elongation. However, it remains elusive as to how this coordination occurs during reproduction. Here, we present evidence that endocytosis, involving heterotetrameric adaptor protein complex 2 (AP-2), plays a crucial role in fertilization. An Arabidopsis thaliana mutant ap2m displays multiple defects in pollen production and viability, as well as elongation of staminal filaments and pollen tubes, all of which are pivotal processes needed for fertilization. Of these abnormalities, the defects in elongation of staminal filaments and pollen tubes were partially rescued by exogenous auxin. Moreover, DR5rev:GFP (for green fluorescent protein) expression was greatly reduced in filaments and anthers in ap2m mutant plants. At the cellular level, ap2m mutants displayed defects in both endocytosis of N-(3-triethylammonium-propyl)-4-(4-diethylaminophenylhexatrienyl) pyridinium dibromide, a lypophilic dye used as an endocytosis marker, and polar localization of auxin-efflux carrier PIN FORMED2 (PIN2) in the stamen filaments. Moreover, these defects were phenocopied by treatment with Tyrphostin A23, an inhibitor of endocytosis. Based on these results, we propose that AP-2–dependent endocytosis plays a crucial role in coordinating the multiple developmental aspects of male reproductive organs by modulating cellular auxin level through the regulation of the amount and polarity of PINs. PMID:23975898

The p66(Shc adaptor protein controls oxidative stress response in early bovine embryos.

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Dean H Betts

Full Text Available The in vitro production of mammalian embryos suffers from high frequencies of developmental failure due to excessive levels of permanent embryo arrest and apoptosis caused by oxidative stress. The p66Shc stress adaptor protein controls oxidative stress response of somatic cells by regulating intracellular ROS levels through multiple pathways, including mitochondrial ROS generation and the repression of antioxidant gene expression. We have previously demonstrated a strong relationship with elevated p66Shc levels, reduced antioxidant levels and greater intracellular ROS generation with the high incidence of permanent cell cycle arrest of 2-4 cell embryos cultured under high oxygen tensions or after oxidant treatment. The main objective of this study was to establish a functional role for p66Shc in regulating the oxidative stress response during early embryo development. Using RNA interference in bovine zygotes we show that p66Shc knockdown embryos exhibited increased MnSOD levels, reduced intracellular ROS and DNA damage that resulted in a greater propensity for development to the blastocyst stage. P66Shc knockdown embryos were stress resistant exhibiting significantly reduced intracellular ROS levels, DNA damage, permanent 2-4 cell embryo arrest and diminished apoptosis frequencies after oxidant treatment. The results of this study demonstrate that p66Shc controls the oxidative stress response in early mammalian embryos. Small molecule inhibition of p66Shc may be a viable clinical therapy to increase the developmental potential of in vitro produced mammalian embryos.

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

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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.

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

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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.

The adaptor CRADD/RAIDD controls activation of endothelial cells by proinflammatory stimuli.

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Qiao, Huan; Liu, Yan; Veach, Ruth A; Wylezinski, Lukasz; Hawiger, Jacek

2014-08-08

A hallmark of inflammation, increased vascular permeability, is induced in endothelial cells by multiple agonists through stimulus-coupled assembly of the CARMA3 signalosome, which contains the adaptor protein BCL10. Previously, we reported that BCL10 in immune cells is targeted by the "death" adaptor CRADD/RAIDD (CRADD), which negatively regulates nuclear factor κB (NFκB)-dependent cytokine and chemokine expression in T cells (Lin, Q., Liu, Y., Moore, D. J., Elizer, S. K., Veach, R. A., Hawiger, J., and Ruley, H. E. (2012) J. Immunol. 188, 2493-2497). This novel anti-inflammatory CRADD-BCL10 axis prompted us to analyze CRADD expression and its potential anti-inflammatory action in non-immune cells. We focused our study on microvascular endothelial cells because they play a key role in inflammation. We found that CRADD-deficient murine endothelial cells display heightened BCL10-mediated expression of the pleotropic proinflammatory cytokine IL-6 and chemokine monocyte chemoattractant protein-1 (MCP-1/CCL2) in response to LPS and thrombin. Moreover, these agonists also induce significantly increased permeability in cradd(-/-), as compared with cradd(+/+), primary murine endothelial cells. CRADD-deficient cells displayed more F-actin polymerization with concomitant disruption of adherens junctions. In turn, increasing intracellular CRADD by delivery of a novel recombinant cell-penetrating CRADD protein (CP-CRADD) restored endothelial barrier function and suppressed the induction of IL-6 and MCP-1 evoked by LPS and thrombin. Likewise, CP-CRADD enhanced barrier function in CRADD-sufficient endothelial cells. These results indicate that depletion of endogenous CRADD compromises endothelial barrier function in response to inflammatory signals. Thus, we define a novel function for CRADD in endothelial cells as an inducible suppressor of BCL10, a key mediator of responses to proinflammatory agonists. © 2014 by The American Society for Biochemistry and Molecular Biology

Adaptor protein 1 B mu subunit does not contribute to the recycling of kAE1 protein in polarized renal epithelial cells.

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Almomani, Ensaf Y; Touret, Nicolas; Cordat, Emmanuelle

2018-04-13

Mutations in the gene encoding the kidney anion exchanger 1 (kAE1) can lead to distal renal tubular acidosis (dRTA). dRTA mutations reported within the carboxyl (C)-terminal tail of kAE1 result in apical mis-targeting of the exchanger in polarized renal epithelial cells. As kAE1 physically interacts with the μ subunit of epithelial adaptor protein 1 B (AP-1B), we investigated the role of heterologously expressed μ1B subunit of the AP-1B complex for kAE1 retention to the basolateral membrane in polarized porcine LLC-PK1 renal epithelial cells that are devoid of endogenous AP-1B. We confirmed the interaction and close proximity between kAE1 and μ1B using immunoprecipitation and proximity ligation assay, respectively. Expressing the human μ1B subunit in these cells decreased significantly the amount of cell surface kAE1 at the steady state, but had no significant effect on kAE1 recycling and endocytosis. We show that (i) heterologous expression of μ1B displaces the physical interaction of endogenous GAPDH with kAE1 WT supporting that both AP-1B and GAPDH proteins bind to an overlapping site on kAE1 and (ii) phosphorylation of tyrosine 904 within the potential YDEV interaction motif does not alter the kAE1/AP-1B interaction. We conclude that μ1B subunit is not involved in recycling of kAE1.

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

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

An Interaction between KSHV ORF57 and UIF Provides mRNA-Adaptor Redundancy in Herpesvirus Intronless mRNA Export

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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

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.

Aftereffects of Spectrally Similar and Dissimilar Spectral Motion Adaptors in the Tritone Paradox

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Stephanie Malek

2018-05-01

Full Text Available Shepard tones consist of octave-spaced components, whose amplitudes are generated under a fixed bell-shaped spectral envelope. They are well defined in pitch chroma, but generate octave confusions that in turn can produce ambiguities in the perceived relative pitch heights when their chromas are exactly a tritone apart (the tritone paradox. This study examined the effects of tonal context on relative pitch height judgments using adaptor sequences followed by target sequences (pairs of Shepard tones of different chromas separated by a tritone. Listeners judged whether the second target Shepard tone was higher or lower than the first. Adaptor sequences consisted of rising or falling scales (43 s at the beginning of each block, 4 s before each target sequence. Two sets of Shepard tones were used for adaptors and targets that were generated under spectral envelopes centered at either A3 (220 Hz and C6 (1,046 Hz. Pitch direction judgments (rising vs. falling to spectrally consistent (A3–A3, C6–C6 and inconsistent (A3–C6, C6–A3 adaptor-target combinations were studied. Large significant contrastive aftereffects (0.08–0.21 change in fraction of pitch direction responses were only found for the Shepard tones that were judged as higher in the control condition (judgments about the target sequences without adaptor sequences for the consistent adaptor-target conditions (A3–A3, C6–C6. The experiments rule out explanations based on non-sensory decision making processes. Possible explanations in terms of perceptual aftereffects caused by adaptation in central auditory frequency-motion detectors are discussed.

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

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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

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

Energy Technology Data Exchange (ETDEWEB)

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

2009-12-01

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

DiffSLC: A graph centrality method to detect essential proteins of a protein-protein interaction network.

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Mistry, Divya; Wise, Roger P; Dickerson, Julie A

2017-01-01

Identification of central genes and proteins in biomolecular networks provides credible candidates for pathway analysis, functional analysis, and essentiality prediction. The DiffSLC centrality measure predicts central and essential genes and proteins using a protein-protein interaction network. Network centrality measures prioritize nodes and edges based on their importance to the network topology. These measures helped identify critical genes and proteins in biomolecular networks. The proposed centrality measure, DiffSLC, combines the number of interactions of a protein and the gene coexpression values of genes from which those proteins were translated, as a weighting factor to bias the identification of essential proteins in a protein interaction network. Potentially essential proteins with low node degree are promoted through eigenvector centrality. Thus, the gene coexpression values are used in conjunction with the eigenvector of the network's adjacency matrix and edge clustering coefficient to improve essentiality prediction. The outcome of this prediction is shown using three variations: (1) inclusion or exclusion of gene co-expression data, (2) impact of different coexpression measures, and (3) impact of different gene expression data sets. For a total of seven networks, DiffSLC is compared to other centrality measures using Saccharomyces cerevisiae protein interaction networks and gene expression data. Comparisons are also performed for the top ranked proteins against the known essential genes from the Saccharomyces Gene Deletion Project, which show that DiffSLC detects more essential proteins and has a higher area under the ROC curve than other compared methods. This makes DiffSLC a stronger alternative to other centrality methods for detecting essential genes using a protein-protein interaction network that obeys centrality-lethality principle. DiffSLC is implemented using the igraph package in R, and networkx package in Python. The python package can be

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

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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.

Bottom nozzle for nuclear reactor fuel assembly having an adaptor plate and a coupled filtration plate

International Nuclear Information System (INIS)

Verdier, M.; Mortgat, R.

1992-01-01

The bottom nozzle includes an adaptor plate with openings to allow the passage of water and a filtration plate with small holes. The openings in the adaptor plate are symmetrical with regard to medians and diagonals. Within each zone, some of the openings are rectangular and some may be circular. The small holes in the filtration plate coincide with the rectangular openings in the adaptor plate

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

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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.

Protein Networks in Alzheimer's Disease

DEFF Research Database (Denmark)

Carlsen, Eva 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...

Network Compression as a Quality Measure for Protein Interaction Networks

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Royer, Loic; Reimann, Matthias; Stewart, A. Francis; Schroeder, Michael

2012-01-01

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. PMID:22719828

The CRKL gene encoding an adaptor protein is amplified, overexpressed, and a possible therapeutic target in gastric cancer

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Natsume Hiroko

2012-07-01

Full Text Available Abstract Background Genomic DNA amplification is a genetic factor involved in cancer, and some oncogenes, such as ERBB2, are highly amplified in gastric cancer. We searched for the possible amplification of other genes in gastric cancer. Methods and Results A genome-wide single nucleotide polymorphism microarray analysis was performed using three cell lines of differentiated gastric cancers, and 22 genes (including ERBB2 in five highly amplified chromosome regions (with a copy number of more than 6 were identified. Particular attention was paid to the CRKL gene, the product of which is an adaptor protein containing Src homology 2 and 3 (SH2/SH3 domains. An extremely high CRKL copy number was confirmed in the MKN74 gastric cancer cell line using fluorescence in situ hybridization (FISH, and a high level of CRKL expression was also observed in the cells. The RNA-interference-mediated knockdown of CRKL in MKN74 disclosed the ability of CRKL to upregulate gastric cell proliferation. An immunohistochemical analysis revealed that CRKL protein was overexpressed in 24.4% (88/360 of the primary gastric cancers that were analyzed. The CRKL copy number was also examined in 360 primary gastric cancers using a FISH analysis, and CRKL amplification was found to be associated with CRKL overexpression. Finally, we showed that MKN74 cells with CRKL amplification were responsive to the dual Src/BCR-ABL kinase inhibitor BMS354825, likely via the inhibition of CRKL phosphorylation, and that the proliferation of MKN74 cells was suppressed by treatment with a CRKL-targeting peptide. Conclusion These results suggested that CRKL protein is overexpressed in a subset of gastric cancers and is associated with CRKL amplification in gastric cancer. Furthermore, our results suggested that CRKL protein has the ability to regulate gastric cell proliferation and has the potential to serve as a molecular therapy target for gastric cancer.

Autophagy adaptor protein p62/SQSTM1 and autophagy-related gene Atg5 mediate autophagosome formation in response to Mycobacterium tuberculosis infection in dendritic cells.

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Shintaro Seto

Full Text Available Mycobacterium tuberculosis is an intracellular pathogen that can survive within phagocytic cells by inhibiting phagolysosome biogenesis. However, host cells can control the intracellular M. tuberculosis burden by the induction of autophagy. The mechanism of autophagosome formation to M. tuberculosis has been well studied in macrophages, but remains unclear in dendritic cells. We therefore characterized autophagosome formation in response to M. tuberculosis infection in dendritic cells. Autophagy marker protein LC3, autophagy adaptor protein p62/SQSTM1 (p62 and ubiquitin co-localized to M. tuberculosis in dendritic cells. Mycobacterial autophagosomes fused with lysosomes during infection, and major histcompatibility complex class II molecules (MHC II also localized to mycobacterial autophagosomes. The proteins p62 and Atg5 function in the initiation and progression of autophagosome formation to M. tuberculosis, respectively; p62 mediates ubiquitination of M. tuberculosis and Atg5 is involved in the trafficking of degradative vesicles and MHC II to mycobacterial autophagosomes. These results imply that the autophagosome formation to M. tuberculosis in dendritic cells promotes the antigen presentation of mycobacterial peptides to CD4(+ T lymphocytes via MHC II.

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

Finding local communities in protein networks.

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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

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

NAPS: Network Analysis of Protein Structures

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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

The Hypoxic Regulator of Sterol Synthesis Nro1 Is a Nuclear Import Adaptor

Energy Technology Data Exchange (ETDEWEB)

T Yeh; C Lee; L Amzel; P Espenshade; M Bianchet

2011-12-31

Fission yeast protein Sre1, the homolog of the mammalian sterol regulatory element-binding protein (SREBP), is a hypoxic transcription factor required for sterol homeostasis and low-oxygen growth. Nro1 regulates the stability of the N-terminal transcription factor domain of Sre1 (Sre1N) by inhibiting the action of the prolyl 4-hydroxylase-like Ofd1 in an oxygen-dependent manner. The crystal structure of Nro1 determined at 2.2 {angstrom} resolution shows an all-{alpha}-helical fold that can be divided into two domains: a small N-terminal domain, and a larger C-terminal HEAT-repeat domain. Follow-up studies showed that Nro1 defines a new class of nuclear import adaptor that functions both in Ofd1 nuclear localization and in the oxygen-dependent inhibition of Ofd1 to control the hypoxic response.

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 .

3DProIN: Protein-Protein Interaction Networks and Structure Visualization.

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Li, Hui; Liu, Chunmei

2014-06-14

3DProIN is a computational tool to visualize protein-protein interaction networks in both two dimensional (2D) and three dimensional (3D) view. It models protein-protein interactions in a graph and explores the biologically relevant features of the tertiary structures of each protein in the network. Properties such as color, shape and name of each node (protein) of the network can be edited in either 2D or 3D views. 3DProIN is implemented using 3D Java and C programming languages. The internet crawl technique is also used to parse dynamically grasped protein interactions from protein data bank (PDB). It is a java applet component that is embedded in the web page and it can be used on different platforms including Linux, Mac and Window using web browsers such as Firefox, Internet Explorer, Chrome and Safari. It also was converted into a mac app and submitted to the App store as a free app. Mac users can also download the app from our website. 3DProIN is available for academic research at http://bicompute.appspot.com.

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/.

Construction of ontology augmented networks for protein complex prediction.

Science.gov (United States)

Zhang, Yijia; Lin, Hongfei; Yang, Zhihao; Wang, Jian

2013-01-01

Protein complexes are of great importance in understanding the principles of cellular organization and function. The increase in available protein-protein interaction data, gene ontology and other resources make it possible to develop computational methods for protein complex prediction. Most existing methods focus mainly on the topological structure of protein-protein interaction networks, and largely ignore the gene ontology annotation information. In this article, we constructed ontology augmented networks with protein-protein interaction data and gene ontology, which effectively unified the topological structure of protein-protein interaction networks and the similarity of gene ontology annotations into unified distance measures. After constructing ontology augmented networks, a novel method (clustering based on ontology augmented networks) was proposed to predict protein complexes, which was capable of taking into account the topological structure of the protein-protein interaction network, as well as the similarity of gene ontology annotations. Our method was applied to two different yeast protein-protein interaction datasets and predicted many well-known complexes. The experimental results showed that (i) ontology augmented networks and the unified distance measure can effectively combine the structure closeness and gene ontology annotation similarity; (ii) our method is valuable in predicting protein complexes and has higher F1 and accuracy compared to other competing methods.

Discovering disease-associated genes in weighted protein-protein interaction networks

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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.

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.

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

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.

The adaptor Lnk (SH2B3): an emerging regulator in vascular cells and a link between immune and inflammatory signaling.

Science.gov (United States)

Devallière, Julie; Charreau, Béatrice

2011-11-15

A better knowledge of the process by which inflammatory extracellular signals are relayed from the plasma membrane to specific intracellular sites is a key step to understand how inflammation develops and how it is regulated. This review focuses on Lnk (SH2B3) a member, with SH2B1 and SH2B2, of the SH2B family of adaptor proteins that influences a variety of signaling pathways mediated by Janus kinase and receptor tyrosine kinases. SH2B adaptor proteins contain conserved dimerization, pleckstrin homology, and SH2 domains. Initially described as a regulator of hematopoiesis and lymphocyte differentiation, Lnk now emerges as a key regulator in hematopoeitic and non hematopoeitic cells such as endothelial cells (EC) moderating growth factor and cytokine receptor-mediated signaling. In EC, Lnk is a negative regulator of TNF signaling that reduce proinflammatory phenotype and prevent EC from apoptosis. Lnk is a modulator in integrin signaling and actin cytoskeleton organization in both platelets and EC with an impact on cell adhesion, migration and thrombosis. In this review, we discuss some recent insights proposing Lnk as a key regulator of bone marrow-endothelial progenitor cell kinetics, including the ability to cell growth, endothelial commitment, mobilization, and recruitment for vascular regeneration. Finally, novel findings also provided evidences that mutations in Lnk gene are strongly linked to myeloproliferative disorders but also autoimmune and inflammatory syndromes where both immune and vascular cells display a role. Overall, these studies emphasize the importance of the Lnk adaptor molecule not only as prognostic marker but also as potential therapeutic target. Copyright © 2011 Elsevier Inc. All rights reserved.

In silico modeling of the yeast protein and protein family interaction network

Science.gov (United States)

Goh, K.-I.; Kahng, B.; Kim, D.

2004-03-01

Understanding of how protein interaction networks of living organisms have evolved or are organized can be the first stepping stone in unveiling how life works on a fundamental ground. Here we introduce an in silico ``coevolutionary'' model for the protein interaction network and the protein family network. The essential ingredient of the model includes the protein family identity and its robustness under evolution, as well as the three previously proposed: gene duplication, divergence, and mutation. This model produces a prototypical feature of complex networks in a wide range of parameter space, following the generalized Pareto distribution in connectivity. Moreover, we investigate other structural properties of our model in detail with some specific values of parameters relevant to the yeast Saccharomyces cerevisiae, showing excellent agreement with the empirical data. Our model indicates that the physical constraints encoded via the domain structure of proteins play a crucial role in protein interactions.

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.

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.

NECAPs are negative regulators of the AP2 clathrin adaptor complex.

Science.gov (United States)

Beacham, Gwendolyn M; Partlow, Edward A; Lange, Jeffrey J; Hollopeter, Gunther

2018-01-18

Eukaryotic cells internalize transmembrane receptors via clathrin-mediated endocytosis, but it remains unclear how the machinery underpinning this process is regulated. We recently discovered that membrane-associated muniscin proteins such as FCHo and SGIP initiate endocytosis by converting the AP2 clathrin adaptor complex to an open, active conformation that is then phosphorylated (Hollopeter et al., 2014). Here we report that loss of ncap-1 , the sole C. elegans gene encoding an adaptiN Ear-binding Coat-Associated Protein (NECAP), bypasses the requirement for FCHO-1. Biochemical analyses reveal AP2 accumulates in an open, phosphorylated state in ncap-1 mutant worms, suggesting NECAPs promote the closed, inactive conformation of AP2. Consistent with this model, NECAPs preferentially bind open and phosphorylated forms of AP2 in vitro and localize with constitutively open AP2 mutants in vivo. NECAPs do not associate with phosphorylation-defective AP2 mutants, implying that phosphorylation precedes NECAP recruitment. We propose NECAPs function late in endocytosis to inactivate AP2. © 2018, Beacham et al.

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

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.

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

The Ras suppressor Rsu-1 binds to the LIM 5 domain of the adaptor protein PINCH1 and participates in adhesion-related functions

International Nuclear Information System (INIS)

Dougherty, Gerard W.; Chopp, Treasa; Qi Shengmei; Cutler, Mary Lou

2005-01-01

Rsu-1 is a highly conserved leucine rich repeat (LRR) protein that is expressed ubiquitously in mammalian cells. Rsu-1 was identified based on its ability to inhibit transformation by Ras, and previous studies demonstrated that ectopic expression of Rsu-1 inhibited anchorage-independent growth of Ras-transformed cells and human tumor cell lines. Using GAL4-based yeast two-hybrid screening, the LIM domain protein, PINCH1, was identified as the binding partner of Rsu-1. PINCH1 is an adaptor protein that localizes to focal adhesions and it has been implicated in the regulation of adhesion functions. Subdomain mapping in yeast revealed that Rsu-1 binds to the LIM 5 domain of PINCH1, a region not previously identified as a specific binding domain for any other protein. Additional testing demonstrated that PINCH2, which is highly homologous to PINCH1, except in the LIM 5 domain, does not interact with Rsu-1. Glutathione transferase fusion protein binding studies determined that the LRR region of Rsu-1 interacts with PINCH1. Transient expression studies using epitope-tagged Rsu-1 and PINCH1 revealed that Rsu-1 co-immunoprecipitated with PINCH1 and colocalized with vinculin at sites of focal adhesions in mammalian cells. In addition, endogenous P33 Rsu-1 from 293T cells co-immunoprecipitated with transiently expressed myc-tagged PINCH1. Furthermore, RNAi-induced reduction in Rsu-1 RNA and protein inhibited cell attachment, and while previous studies demonstrated that ectopic expression of Rsu-1 inhibited Jun kinase activation, the depletion of Rsu-1 resulted in activation of Jun and p38 stress kinases. These studies demonstrate that Rsu-1 interacts with PINCH1 in mammalian cells and functions, in part, by altering cell adhesion

Downregulation of adaptor protein MyD88 compromises the angiogenic potential of B16 murine melanoma

Science.gov (United States)

Araya, Paula; Nuñez, Nicolás Gonzalo; Mena, Hebe Agustina; Bocco, José Luis; Negrotto, Soledad; Maccioni, Mariana

2017-01-01

The mechanisms that link inflammatory responses to cancer development remain a subject of intense investigation, emphasizing the need to better understand the cellular and molecular pathways that create a tumor promoting microenvironment. The myeloid differentiation primary response protein MyD88 acts as a main adaptor molecule for the signaling cascades initiated from Toll-like receptors (TLRs) and the interleukin 1 receptor (IL-1R). MyD88 has been shown to contribute to tumorigenesis in many inflammation-associated cancer models. In this study, we sought to better define the role of MyD88 in neoplastic cells using a murine melanoma model. Herein, we have demonstrated that MyD88 expression is required to maintain the angiogenic switch that supports B16 melanoma growth. By knocking down MyD88 we reduced TLR-mediated NF-κB activation with no evident effects over cell proliferation and survival. In addition, MyD88 downregulation was associated with a decrease of HIF1α levels and its target gene VEGF, in correlation with an impaired capability to induce capillary sprouting and tube formation of endothelial cells. Melanomas developed from cells lacking MyD88 showed an enhanced secretion of chemoattractant ligands such as CCL2, CXCL10 and CXCL1 and have an improved infiltration of macrophages to the tumor site. Our results imply that cell-autonomous signaling through MyD88 is required to sustain tumor growth and underscore its function as an important positive modulator of tumor angiogenesis. PMID:28662055

Protein enriched pasta: structure and digestibility of its protein network.

Science.gov (United States)

Laleg, Karima; Barron, Cécile; Santé-Lhoutellier, Véronique; Walrand, Stéphane; Micard, Valérie

2016-02-01

Wheat (W) pasta was enriched in 6% gluten (G), 35% faba (F) or 5% egg (E) to increase its protein content (13% to 17%). The impact of the enrichment on the multiscale structure of the pasta and on in vitro protein digestibility was studied. Increasing the protein content (W- vs. G-pasta) strengthened pasta structure at molecular and macroscopic scales but reduced its protein digestibility by 3% by forming a higher covalently linked protein network. Greater changes in the macroscopic and molecular structure of the pasta were obtained by varying the nature of protein used for enrichment. Proteins in G- and E-pasta were highly covalently linked (28-32%) resulting in a strong pasta structure. Conversely, F-protein (98% SDS-soluble) altered the pasta structure by diluting gluten and formed a weak protein network (18% covalent link). As a result, protein digestibility in F-pasta was significantly higher (46%) than in E- (44%) and G-pasta (39%). The effect of low (55 °C, LT) vs. very high temperature (90 °C, VHT) drying on the protein network structure and digestibility was shown to cause greater molecular changes than pasta formulation. Whatever the pasta, a general strengthening of its structure, a 33% to 47% increase in covalently linked proteins and a higher β-sheet structure were observed. However, these structural differences were evened out after the pasta was cooked, resulting in identical protein digestibility in LT and VHT pasta. Even after VHT drying, F-pasta had the best amino acid profile with the highest protein digestibility, proof of its nutritional interest.

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.

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.

Optimal neural networks for protein-structure prediction

International Nuclear Information System (INIS)

Head-Gordon, T.; Stillinger, F.H.

1993-01-01

The successful application of neural-network algorithms for prediction of protein structure is stymied by three problem areas: the sparsity of the database of known protein structures, poorly devised network architectures which make the input-output mapping opaque, and a global optimization problem in the multiple-minima space of the network variables. We present a simplified polypeptide model residing in two dimensions with only two amino-acid types, A and B, which allows the determination of the global energy structure for all possible sequences of pentamer, hexamer, and heptamer lengths. This model simplicity allows us to compile a complete structural database and to devise neural networks that reproduce the tertiary structure of all sequences with absolute accuracy and with the smallest number of network variables. These optimal networks reveal that the three problem areas are convoluted, but that thoughtful network designs can actually deconvolute these detrimental traits to provide network algorithms that genuinely impact on the ability of the network to generalize or learn the desired mappings. Furthermore, the two-dimensional polypeptide model shows sufficient chemical complexity so that transfer of neural-network technology to more realistic three-dimensional proteins is evident

Protein complex prediction based on k-connected subgraphs in protein interaction network

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Habibi Mahnaz

2010-09-01

Full Text Available Abstract Background Protein complexes play an important role in cellular mechanisms. Recently, several methods have been presented to predict protein complexes in a protein interaction network. In these methods, a protein complex is predicted as a dense subgraph of protein interactions. However, interactions data are incomplete and a protein complex does not have to be a complete or dense subgraph. Results We propose a more appropriate protein complex prediction method, CFA, that is based on connectivity number on subgraphs. We evaluate CFA using several protein interaction networks on reference protein complexes in two benchmark data sets (MIPS and Aloy, containing 1142 and 61 known complexes respectively. We compare CFA to some existing protein complex prediction methods (CMC, MCL, PCP and RNSC in terms of recall and precision. We show that CFA predicts more complexes correctly at a competitive level of precision. Conclusions Many real complexes with different connectivity level in protein interaction network can be predicted based on connectivity number. Our CFA program and results are freely available from http://www.bioinf.cs.ipm.ir/softwares/cfa/CFA.rar.

U1 Adaptor Oligonucleotides Targeting BCL2 and GRM1 Suppress Growth of Human Melanoma Xenografts In Vivo

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Rafal Goraczniak

2013-01-01

Full Text Available U1 Adaptor is a recently discovered oligonucleotide-based gene-silencing technology with a unique mechanism of action that targets nuclear pre-mRNA processing. U1 Adaptors have two distinct functional domains, both of which must be present on the same oligonucleotide to exert their gene-silencing function. Here, we present the first in vivo use of U1 Adaptors by targeting two different human genes implicated in melanomagenesis, B-cell lymphoma 2 (BCL2 and metabotropic glutamate receptor 1 (GRM1, in a human melanoma cell xenograft mouse model system. Using a newly developed dendrimer delivery system, anti-BCL2 U1 Adaptors were very potent and suppressed tumor growth at doses as low as 34 µg/kg with twice weekly intravenous (iv administration. Anti-GRM1 U1 Adaptors suppressed tumor xenograft growth with similar potency. Mechanism of action was demonstrated by showing target gene suppression in tumors and by observing that negative control U1 Adaptors with just one functional domain show no tumor suppression activity. The anti-BCL2 and anti-GRM1 treatments were equally effective against cell lines harboring either wild-type or a mutant V600E B-RAF allele, the most common mutation in melanoma. Treatment of normal immune-competent mice (C57BL6 indicated no organ toxicity or immune stimulation. These proof-of-concept studies represent an in-depth (over 800 mice in ~108 treatment groups validation that U1 Adaptors are a highly potent gene-silencing therapeutic and open the way for their further development to treat other human diseases.

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

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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

Enhancement of B-cell receptor signaling by a point mutation of adaptor protein 3BP2 identified in human inherited disease cherubism.

Science.gov (United States)

Ogi, Kazuhiro; Nakashima, Kenji; Chihara, Kazuyasu; Takeuchi, Kenji; Horiguchi, Tomoko; Fujieda, Shigeharu; Sada, Kiyonao

2011-09-01

Tyrosine phosphorylation of adaptor protein c-Abl-Src homology 3 (SH3) domain-binding protein-2 (3BP2, also referred to SH3BP2) positively regulates the B-cell antigen receptor (BCR)-mediated signal transduction, leading to the activation of nuclear factor of activated T cells (NFAT). Here we showed the effect of the proline to arginine substitution of 3BP2 in which is the most common mutation in patients with cherubism (P418R) on B-cell receptor signaling. Comparing to the wild type, overexpression of the mutant form of 3BP2 (3BP2-P416R, corresponding to P418R in human protein) enhanced BCR-mediated activation of NFAT. 3BP2-P416R increased the signaling complex formation with Syk, phospholipase C-γ2 (PLC-γ2), and Vav1. In contrast, 3BP2-P416R could not change the association with the negative regulator 14-3-3. Loss of the association mutant that was incapable to associate with 14-3-3 could not mimic BCR-mediated NFAT activation in Syk-deficient cells. Moreover, BCR-mediated phosphorylation of extracellular signal regulated kinase (ERK) and c-Jun N-terminal kinase (JNK) was not affected by P416R mutation. These results showed that P416R mutation of 3BP2 causes the gain of function in B cells by increasing the interaction with specific signaling molecules. © 2011 The Authors. Journal compilation © 2011 by the Molecular Biology Society of Japan/Blackwell Publishing Ltd.

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

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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.

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.

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

KAUST Repository

Chowdhary, Rajesh; Tan, Sin Lam; Zhang, Jinfeng; Karnik, Shreyas; Bajic, Vladimir B.; Liu, Jun S.

2012-01-01

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.

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

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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.

Unveiling protein functions through the dynamics of the interaction network.

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Irene Sendiña-Nadal

Full Text Available Protein interaction networks have become a tool to study biological processes, either for predicting molecular functions or for designing proper new drugs to regulate the main biological interactions. Furthermore, such networks are known to be organized in sub-networks of proteins contributing to the same cellular function. However, the protein function prediction is not accurate and each protein has traditionally been assigned to only one function by the network formalism. By considering the network of the physical interactions between proteins of the yeast together with a manual and single functional classification scheme, we introduce a method able to reveal important information on protein function, at both micro- and macro-scale. In particular, the inspection of the properties of oscillatory dynamics on top of the protein interaction network leads to the identification of misclassification problems in protein function assignments, as well as to unveil correct identification of protein functions. We also demonstrate that our approach can give a network representation of the meta-organization of biological processes by unraveling the interactions between different functional classes.

Crystal structure of Src-like adaptor protein 2 reveals close association of SH3 and SH2 domains through β-sheet formation.

Science.gov (United States)

Wybenga-Groot, Leanne E; McGlade, C Jane

2013-12-01

The Src-like adaptor proteins (SLAP/SLAP2) are key components of Cbl-dependent downregulation of antigen receptor, cytokine receptor, and receptor tyrosine kinase signaling in hematopoietic cells. SLAP and SLAP2 consist of adjacent SH3 and SH2 domains that are most similar in sequence to Src family kinases (SFKs). Notably, the SH3-SH2 connector sequence is significantly shorter in SLAP/SLAP2 than in SFKs. To understand the structural implication of a short SH3-SH2 connector sequence, we solved the crystal structure of a protein encompassing the SH3 domain, SH3-SH2 connector, and SH2 domain of SLAP2 (SLAP2-32). While both domains adopt typical folds, the short SH3-SH2 connector places them in close association. Strand βe of the SH3 domain interacts with strand βA of the SH2 domain, resulting in the formation of a continuous β sheet that spans the length of the protein. Disruption of the SH3/SH2 interface through mutagenesis decreases SLAP-32 stability in vitro, consistent with inter-domain binding being an important component of SLAP2 structure and function. The canonical peptide binding pockets of the SH3 and SH2 domains are fully accessible, in contrast to other protein structures that display direct interaction between SH3 and SH2 domains, in which either peptide binding surface is obstructed by the interaction. Our results reveal potential sites of novel interaction for SH3 and SH2 domains, and illustrate the adaptability of SH2 and SH3 domains in mediating interactions. As well, our results suggest that the SH3 and SH2 domains of SLAP2 function interdependently, with implications on their mode of substrate binding. © 2013.

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

Protein Annotation from Protein Interaction Networks and Gene Ontology

OpenAIRE

Nguyen, Cao D.; Gardiner, Katheleen J.; Cios, Krzysztof J.

2011-01-01

We introduce a novel method for annotating protein function that combines Naïve Bayes and association rules, and takes advantage of the underlying topology in protein interaction networks and the structure of graphs in the Gene Ontology. We apply our method to proteins from the Human Protein Reference Database (HPRD) and show that, in comparison with other approaches, it predicts protein functions with significantly higher recall with no loss of precision. Specifically, it achieves 51% precis...

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...

Evidence of probabilistic behaviour in protein interaction networks

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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.

Gene Prioritization by Integrated Analysis of Protein Structural and Network Topological Properties for the Protein-Protein Interaction Network of Neurological Disorders

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Yashna Paul

2016-01-01

Full Text Available Neurological disorders are known to show similar phenotypic manifestations like anxiety, depression, and cognitive impairment. There is a need to identify shared genetic markers and molecular pathways in these diseases, which lead to such comorbid conditions. Our study aims to prioritize novel genetic markers that might increase the susceptibility of patients affected with one neurological disorder to other diseases with similar manifestations. Identification of pathways involving common candidate markers will help in the development of improved diagnosis and treatments strategies for patients affected with neurological disorders. This systems biology study for the first time integratively uses 3D-structural protein interface descriptors and network topological properties that characterize proteins in a neurological protein interaction network, to aid the identification of genes that are previously not known to be shared between these diseases. Results of protein prioritization by machine learning have identified known as well as new genetic markers which might have direct or indirect involvement in several neurological disorders. Important gene hubs have also been identified that provide an evidence for shared molecular pathways in the neurological disease network.

Construction and analysis of protein-protein interaction networks based on proteomics data of prostate cancer

Science.gov (United States)

CHEN, CHEN; SHEN, HONG; ZHANG, LI-GUO; LIU, JIAN; CAO, XIAO-GE; YAO, AN-LIANG; KANG, SHAO-SAN; GAO, WEI-XING; HAN, HUI; CAO, FENG-HONG; LI, ZHI-GUO

2016-01-01

Currently, using human prostate cancer (PCa) tissue samples to conduct proteomics research has generated a large amount of data; however, only a very small amount has been thoroughly investigated. In this study, we manually carried out the mining of the full text of proteomics literature that involved comparisons between PCa and normal or benign tissue and identified 41 differentially expressed proteins verified or reported more than 2 times from different research studies. We regarded these proteins as seed proteins to construct a protein-protein interaction (PPI) network. The extended network included one giant network, which consisted of 1,264 nodes connected via 1,744 edges, and 3 small separate components. The backbone network was then constructed, which was derived from key nodes and the subnetwork consisting of the shortest path between seed proteins. Topological analyses of these networks were conducted to identify proteins essential for the genesis of PCa. Solute carrier family 2 (facilitated glucose transporter), member 4 (SLC2A4) had the highest closeness centrality located in the center of each network, and the highest betweenness centrality and largest degree in the backbone network. Tubulin, beta 2C (TUBB2C) had the largest degree in the giant network and subnetwork. In addition, using module analysis of the whole PPI network, we obtained a densely connected region. Functional annotation indicated that the Ras protein signal transduction biological process, mitogen-activated protein kinase (MAPK), neurotrophin and the gonadotropin-releasing hormone (GnRH) signaling pathway may play an important role in the genesis and development of PCa. Further investigation of the SLC2A4, TUBB2C proteins, and these biological processes and pathways may therefore provide a potential target for the diagnosis and treatment of PCa. PMID:27121963

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).

A library of 7TM receptor C-terminal tails - Interactions with the proposed post-endocytic sorting proteins ERM-binding phosphoprotein 50 (EBP50), N-ethylmaleimide-sensitive factor (NSF), sorting nexin 1 (SNX1), and G protein-coupled receptor-associated sorting protein (GASP)

DEFF Research Database (Denmark)

Heydorn, A.; Sondergaard, B.P.; Ersbøll, Bjarne Kjær

2004-01-01

Adaptor and scaffolding proteins determine the cellular targeting, the spatial, and thereby the functional association of G protein-coupled seven-transmembrane receptors with co-receptors, transducers, and downstream effectors and the adaptors determine post-signaling events such as receptor...... only a single receptor tail, i.e. the beta(2)-adrenergic receptor, whereas N-ethylmaleimide-sensitive factor bound 11 of the tail-fusion proteins. Of the two proteins proposed to target receptors for lysosomal degradation, sorting nexin 1 (SNX1) bound 10 and the C-terminal domain of G protein...... the expected nanomolar affinities for interaction with SNX1. Truncations of the NK1 receptor revealed that an extended binding epitope is responsible for the interaction with both SNX1 and G protein-coupled receptor-associated sorting protein as well as with N-ethylmaleimide-sensitive factor. It is concluded...

A library of 7TM receptor C-terminal tails. Interactions with the proposed post-endocytic sorting proteins ERM-binding phosphoprotein 50 (EBP50), N-ethylmaleimide-sensitive factor (NSF), sorting nexin 1 (SNX1), and G protein-coupled receptor-associated sorting protein (GASP)

DEFF Research Database (Denmark)

Heydorn, Arne; Søndergaard, Birgitte P; Ersbøll, Bjarne

2004-01-01

Adaptor and scaffolding proteins determine the cellular targeting, the spatial, and thereby the functional association of G protein-coupled seven-transmembrane receptors with co-receptors, transducers, and downstream effectors and the adaptors determine post-signaling events such as receptor...... only a single receptor tail, i.e. the beta(2)-adrenergic receptor, whereas N-ethylmaleimide-sensitive factor bound 11 of the tail-fusion proteins. Of the two proteins proposed to target receptors for lysosomal degradation, sorting nexin 1 (SNX1) bound 10 and the C-terminal domain of G protein...... the expected nanomolar affinities for interaction with SNX1. Truncations of the NK(1) receptor revealed that an extended binding epitope is responsible for the interaction with both SNX1 and G protein-coupled receptor-associated sorting protein as well as with N-ethylmaleimide-sensitive factor. It is concluded...

P-Finder: Reconstruction of Signaling Networks from Protein-Protein Interactions and GO Annotations.

Science.gov (United States)

Young-Rae Cho; Yanan Xin; Speegle, Greg

2015-01-01

Because most complex genetic diseases are caused by defects of cell signaling, illuminating a signaling cascade is essential for understanding their mechanisms. We present three novel computational algorithms to reconstruct signaling networks between a starting protein and an ending protein using genome-wide protein-protein interaction (PPI) networks and gene ontology (GO) annotation data. A signaling network is represented as a directed acyclic graph in a merged form of multiple linear pathways. An advanced semantic similarity metric is applied for weighting PPIs as the preprocessing of all three methods. The first algorithm repeatedly extends the list of nodes based on path frequency towards an ending protein. The second algorithm repeatedly appends edges based on the occurrence of network motifs which indicate the link patterns more frequently appearing in a PPI network than in a random graph. The last algorithm uses the information propagation technique which iteratively updates edge orientations based on the path strength and merges the selected directed edges. Our experimental results demonstrate that the proposed algorithms achieve higher accuracy than previous methods when they are tested on well-studied pathways of S. cerevisiae. Furthermore, we introduce an interactive web application tool, called P-Finder, to visualize reconstructed signaling networks.

Protein-protein interaction networks identify targets which rescue the MPP+ cellular model of Parkinson’s disease

Science.gov (United States)

Keane, Harriet; Ryan, Brent J.; Jackson, Brendan; Whitmore, Alan; Wade-Martins, Richard

2015-11-01

Neurodegenerative diseases are complex multifactorial disorders characterised by the interplay of many dysregulated physiological processes. As an exemplar, Parkinson’s disease (PD) involves multiple perturbed cellular functions, including mitochondrial dysfunction and autophagic dysregulation in preferentially-sensitive dopamine neurons, a selective pathophysiology recapitulated in vitro using the neurotoxin MPP+. Here we explore a network science approach for the selection of therapeutic protein targets in the cellular MPP+ model. We hypothesised that analysis of protein-protein interaction networks modelling MPP+ toxicity could identify proteins critical for mediating MPP+ toxicity. Analysis of protein-protein interaction networks constructed to model the interplay of mitochondrial dysfunction and autophagic dysregulation (key aspects of MPP+ toxicity) enabled us to identify four proteins predicted to be key for MPP+ toxicity (P62, GABARAP, GBRL1 and GBRL2). Combined, but not individual, knockdown of these proteins increased cellular susceptibility to MPP+ toxicity. Conversely, combined, but not individual, over-expression of the network targets provided rescue of MPP+ toxicity associated with the formation of autophagosome-like structures. We also found that modulation of two distinct proteins in the protein-protein interaction network was necessary and sufficient to mitigate neurotoxicity. Together, these findings validate our network science approach to multi-target identification in complex neurological diseases.

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.

Safeguards of Neurotransmission: Endocytic Adaptors as Regulators of Synaptic Vesicle Composition and Function

Directory of Open Access Journals (Sweden)

Natalie Kaempf

2017-10-01

Full Text Available Communication between neurons relies on neurotransmitters which are released from synaptic vesicles (SVs upon Ca2+ stimuli. To efficiently load neurotransmitters, sense the rise in intracellular Ca2+ and fuse with the presynaptic membrane, SVs need to be equipped with a stringently controlled set of transmembrane proteins. In fact, changes in SV protein composition quickly compromise neurotransmission and most prominently give rise to epileptic seizures. During exocytosis SVs fully collapse into the presynaptic membrane and consequently have to be replenished to sustain neurotransmission. Therefore, surface-stranded SV proteins have to be efficiently retrieved post-fusion to be used for the generation of a new set of fully functional SVs, a process in which dedicated endocytic sorting adaptors play a crucial role. The question of how the precise reformation of SVs is achieved is intimately linked to how SV membranes are retrieved. For a long time both processes were believed to be two sides of the same coin since Clathrin-mediated endocytosis (CME, the proposed predominant SV recycling mode, will jointly retrieve SV membranes and proteins. However, with the recent proposal of Clathrin-independent SV recycling pathways SV membrane retrieval and SV reformation turn into separable events. This review highlights the progress made in unraveling the molecular mechanisms mediating the high-fidelity retrieval of SV proteins and discusses how the gathered knowledge about SV protein recycling fits in with the new notions of SV membrane endocytosis.

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.

Transmembrane adaptor molecules: a new category of lymphoid-cell markers

Czech Academy of Sciences Publication Activity Database

Tedoldi, S.; Paterson, J.C.; Hansmann, M.-L.; Natkunam, Y.; Rüdiger, T.; Angelisová, Pavla; Du, M.Q.; Roberton, H.; Roncador, G.; Sanchez, L.; Pozzobon, M.; Masir, N.; Barry, R.; Pileri, S.; Mason, D.Y.; Marafioti, T.; Hořejší, Václav

2006-01-01

Roč. 107, č. 1 (2006), s. 213-221 ISSN 0006-4971 R&D Projects: GA MŠk(CZ) 1M0506 Institutional research plan: CEZ:AV0Z50520514 Keywords : transmembrane adaptors * PAG * LIME Subject RIV: EC - Immunology Impact factor: 10.370, year: 2006

CombiMotif: A new algorithm for network motifs discovery in protein-protein interaction networks

Science.gov (United States)

Luo, Jiawei; Li, Guanghui; Song, Dan; Liang, Cheng

2014-12-01

Discovering motifs in protein-protein interaction networks is becoming a current major challenge in computational biology, since the distribution of the number of network motifs can reveal significant systemic differences among species. However, this task can be computationally expensive because of the involvement of graph isomorphic detection. In this paper, we present a new algorithm (CombiMotif) that incorporates combinatorial techniques to count non-induced occurrences of subgraph topologies in the form of trees. The efficiency of our algorithm is demonstrated by comparing the obtained results with the current state-of-the art subgraph counting algorithms. We also show major differences between unicellular and multicellular organisms. The datasets and source code of CombiMotif are freely available upon request.

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

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

2018-03-22

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

Listeriolysin O Regulates the Expression of Optineurin, an Autophagy Adaptor That Inhibits the Growth of Listeria monocytogenes.

Science.gov (United States)

Puri, Madhu; La Pietra, Luigi; Mraheil, Mobarak Abu; Lucas, Rudolf; Chakraborty, Trinad; Pillich, Helena

2017-09-05

Autophagy, a well-established defense mechanism, enables the elimination of intracellular pathogens including Listeria monocytogenes . Host cell recognition results in ubiquitination of L . monocytogenes and interaction with autophagy adaptors p62/SQSTM1 and NDP52, which target bacteria to autophagosomes by binding to microtubule-associated protein 1 light chain 3 (LC3). Although studies have indicated that L . monocytogenes induces autophagy, the significance of this process in the infectious cycle and the mechanisms involved remain poorly understood. Here, we examined the role of the autophagy adaptor optineurin (OPTN), the phosphorylation of which by the TANK binding kinase 1 (TBK1) enhances its affinity for LC3 and promotes autophagosomal degradation, during L . monocytogenes infection. In LC3- and OPTN-depleted host cells, intracellular replicating L . monocytogenes increased, an effect not seen with a mutant lacking the pore-forming toxin listeriolysin O (LLO). LLO induced the production of OPTN. In host cells expressing an inactive TBK1, bacterial replication was also inhibited. Our studies have uncovered an OPTN-dependent pathway in which L . monocytogenes uses LLO to restrict bacterial growth. Hence, manipulation of autophagy by L . monocytogenes , either through induction or evasion, represents a key event in its intracellular life style and could lead to either cytosolic growth or persistence in intracellular vacuolar structures.

Predicting Protein Function via Semantic Integration of Multiple Networks.

Science.gov (United States)

Yu, Guoxian; Fu, Guangyuan; Wang, Jun; Zhu, Hailong

2016-01-01

Determining the biological functions of proteins is one of the key challenges in the post-genomic era. The rapidly accumulated large volumes of proteomic and genomic data drives to develop computational models for automatically predicting protein function in large scale. Recent approaches focus on integrating multiple heterogeneous data sources and they often get better results than methods that use single data source alone. In this paper, we investigate how to integrate multiple biological data sources with the biological knowledge, i.e., Gene Ontology (GO), for protein function prediction. We propose a method, called SimNet, to Semantically integrate multiple functional association Networks derived from heterogenous data sources. SimNet firstly utilizes GO annotations of proteins to capture the semantic similarity between proteins and introduces a semantic kernel based on the similarity. Next, SimNet constructs a composite network, obtained as a weighted summation of individual networks, and aligns the network with the kernel to get the weights assigned to individual networks. Then, it applies a network-based classifier on the composite network to predict protein function. Experiment results on heterogenous proteomic data sources of Yeast, Human, Mouse, and Fly show that, SimNet not only achieves better (or comparable) results than other related competitive approaches, but also takes much less time. The Matlab codes of SimNet are available at https://sites.google.com/site/guoxian85/simnet.

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

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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.

Specificity and evolvability in eukaryotic protein interaction networks.

Directory of Open Access Journals (Sweden)

Pedro Beltrao

2007-02-01

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

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.

Protein annotation from protein interaction networks and Gene Ontology.

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Nguyen, Cao D; Gardiner, Katheleen J; Cios, Krzysztof J

2011-10-01

We introduce a novel method for annotating protein function that combines Naïve Bayes and association rules, and takes advantage of the underlying topology in protein interaction networks and the structure of graphs in the Gene Ontology. We apply our method to proteins from the Human Protein Reference Database (HPRD) and show that, in comparison with other approaches, it predicts protein functions with significantly higher recall with no loss of precision. Specifically, it achieves 51% precision and 60% recall versus 45% and 26% for Majority and 24% and 61% for χ²-statistics, respectively. Copyright © 2011 Elsevier Inc. All rights reserved.

Enigma interacts with adaptor protein with PH and SH2 domains to control insulin-induced actin cytoskeleton remodeling and glucose transporter 4 translocation.

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Barrès, Romain; Grémeaux, Thierry; Gual, Philippe; Gonzalez, Teresa; Gugenheim, Jean; Tran, Albert; Le Marchand-Brustel, Yannick; Tanti, Jean-François

2006-11-01

APS (adaptor protein with PH and SH2 domains) initiates a phosphatidylinositol 3-kinase-independent pathway involved in insulin-stimulated glucose transport. We recently identified Enigma, a PDZ and LIM domain-containing protein, as a partner of APS and showed that APS-Enigma complex plays a critical role in actin cytoskeleton organization in fibroblastic cells. Because actin rearrangement is important for insulin-induced glucose transporter 4 (Glut 4) translocation, we studied the potential involvement of Enigma in insulin-induced glucose transport in 3T3-L1 adipocytes. Enigma mRNA was expressed in differentiated adipocytes and APS and Enigma were colocalized with cortical actin. Expression of an APS mutant unable to bind Enigma increased the insulin-induced Glut 4 translocation to the plasma membrane. By contrast, overexpression of Enigma inhibited insulin-stimulated glucose transport and Glut 4 translocation without alterations in proximal insulin signaling. This inhibitory effect was prevented with the deletion of the LIM domains of Enigma. Using time-lapse fluorescent microscopy of green fluorescent protein-actin, we demonstrated that the overexpression of Enigma altered insulin-induced actin rearrangements, whereas the expression of Enigma without its LIM domains was without effect. A physiological link between increased expression of Enigma and an alteration in insulin-induced glucose uptake was suggested by the increase in Enigma mRNA expression in adipose tissue of diabetic obese patients. Taken together, these data strongly suggest that the interaction between APS and Enigma is involved in insulin-induced Glut 4 translocation by regulating cortical actin remodeling and raise the possibility that modification of APS/Enigma ratio could participate in the alteration of insulin-induced glucose uptake in adipose tissue.

Design and Calibration of a Dispersive Imaging Spectrometer Adaptor for a Fast IR Camera on NSTX-U

Science.gov (United States)

Reksoatmodjo, Richard; Gray, Travis; Princeton Plasma Physics Laboratory Team

2017-10-01

A dispersive spectrometer adaptor was designed, constructed and calibrated for use on a fast infrared camera employed to measure temperatures on the lower divertor tiles of the NSTX-U tokamak. This adaptor efficiently and evenly filters and distributes long-wavelength infrared photons between 8.0 and 12.0 microns across the 128x128 pixel detector of the fast IR camera. By determining the width of these separated wavelength bands across the camera detector, and then determining the corresponding average photon count for each photon wavelength, a very accurate measurement of the temperature, and thus heat flux, of the divertor tiles can be calculated using Plank's law. This approach of designing an exterior dispersive adaptor for the fast IR camera allows accurate temperature measurements to be made of materials with unknown emissivity. Further, the relative simplicity and affordability of this adaptor design provides an attractive option over more expensive, slower, dispersive IR camera systems. This work was made possible by funding from the Department of Energy for the Summer Undergraduate Laboratory Internship (SULI) program. This work is supported by the US DOE Contract No. DE-AC02-09CH11466.

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.

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...

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...

Topological and organizational properties of the products of house-keeping and tissue-specific genes in protein-protein interaction networks.

Science.gov (United States)

Lin, Wen-Hsien; Liu, Wei-Chung; Hwang, Ming-Jing

2009-03-11

Human cells of various tissue types differ greatly in morphology despite having the same set of genetic information. Some genes are expressed in all cell types to perform house-keeping functions, while some are selectively expressed to perform tissue-specific functions. In this study, we wished to elucidate how proteins encoded by human house-keeping genes and tissue-specific genes are organized in human protein-protein interaction networks. We constructed protein-protein interaction networks for different tissue types using two gene expression datasets and one protein-protein interaction database. We then calculated three network indices of topological importance, the degree, closeness, and betweenness centralities, to measure the network position of proteins encoded by house-keeping and tissue-specific genes, and quantified their local connectivity structure. Compared to a random selection of proteins, house-keeping gene-encoded proteins tended to have a greater number of directly interacting neighbors and occupy network positions in several shortest paths of interaction between protein pairs, whereas tissue-specific gene-encoded proteins did not. In addition, house-keeping gene-encoded proteins tended to connect with other house-keeping gene-encoded proteins in all tissue types, whereas tissue-specific gene-encoded proteins also tended to connect with other tissue-specific gene-encoded proteins, but only in approximately half of the tissue types examined. Our analysis showed that house-keeping gene-encoded proteins tend to occupy important network positions, while those encoded by tissue-specific genes do not. The biological implications of our findings were discussed and we proposed a hypothesis regarding how cells organize their protein tools in protein-protein interaction networks. Our results led us to speculate that house-keeping gene-encoded proteins might form a core in human protein-protein interaction networks, while clusters of tissue-specific gene

Pythoscape: a framework for generation of large protein similarity networks.

Science.gov (United States)

Barber, Alan E; Babbitt, Patricia C

2012-11-01

Pythoscape is a framework implemented in Python for processing large protein similarity networks for visualization in other software packages. Protein similarity networks are graphical representations of sequence, structural and other similarities among proteins for which pairwise all-by-all similarity connections have been calculated. Mapping of biological and other information to network nodes or edges enables hypothesis creation about sequence-structure-function relationships across sets of related proteins. Pythoscape provides several options to calculate pairwise similarities for input sequences or structures, applies filters to network edges and defines sets of similar nodes and their associated data as single nodes (termed representative nodes) for compression of network information and output data or formatted files for visualization.

Design principles for cancer therapy guided by changes in complexity of protein-protein interaction networks.

Science.gov (United States)

Benzekry, Sebastian; Tuszynski, Jack A; Rietman, Edward A; Lakka Klement, Giannoula

2015-05-28

The ever-increasing expanse of online bioinformatics data is enabling new ways to, not only explore the visualization of these data, but also to apply novel mathematical methods to extract meaningful information for clinically relevant analysis of pathways and treatment decisions. One of the methods used for computing topological characteristics of a space at different spatial resolutions is persistent homology. This concept can also be applied to network theory, and more specifically to protein-protein interaction networks, where the number of rings in an individual cancer network represents a measure of complexity. We observed a linear correlation of R = -0.55 between persistent homology and 5-year survival of patients with a variety of cancers. This relationship was used to predict the proteins within a protein-protein interaction network with the most impact on cancer progression. By re-computing the persistent homology after computationally removing an individual node (protein) from the protein-protein interaction network, we were able to evaluate whether such an inhibition would lead to improvement in patient survival. The power of this approach lied in its ability to identify the effects of inhibition of multiple proteins and in the ability to expose whether the effect of a single inhibition may be amplified by inhibition of other proteins. More importantly, we illustrate specific examples of persistent homology calculations, which correctly predict the survival benefit observed effects in clinical trials using inhibitors of the identified molecular target. We propose that computational approaches such as persistent homology may be used in the future for selection of molecular therapies in clinic. The technique uses a mathematical algorithm to evaluate the node (protein) whose inhibition has the highest potential to reduce network complexity. The greater the drop in persistent homology, the greater reduction in network complexity, and thus a larger

A neuromorphic implementation of multiple spike-timing synaptic plasticity rules for large-scale neural networks

Directory of Open Access Journals (Sweden)

Runchun Mark Wang

2015-05-01

Full Text Available We present a neuromorphic implementation of multiple synaptic plasticity learning rules, which include both Spike Timing Dependent Plasticity (STDP and Spike Timing Dependent Delay Plasticity (STDDP. We present a fully digital implementation as well as a mixed-signal implementation, both of which use a novel dynamic-assignment time-multiplexing approach and support up to 2^26 (64M synaptic plasticity elements. Rather than implementing dedicated synapses for particular types of synaptic plasticity, we implemented a more generic synaptic plasticity adaptor array that is separate from the neurons in the neural network. Each adaptor performs synaptic plasticity according to the arrival times of the pre- and post-synaptic spikes assigned to it, and sends out a weighted and/or delayed pre-synaptic spike to the target synapse in the neural network. This strategy provides great flexibility for building complex large-scale neural networks, as a neural network can be configured for multiple synaptic plasticity rules without changing its structure. We validate the proposed neuromorphic implementations with measurement results and illustrate that the circuits are capable of performing both STDP and STDDP. We argue that it is practical to scale the work presented here up to 2^36 (64G synaptic adaptors on a current high-end FPGA platform.

Manufacturing and QA of adaptors for LHC

International Nuclear Information System (INIS)

Madhu Murthy, V.; Dwivedi, J.; Goswami, S.G.; Soni, H.C.; Mainaud Durand, H.; Quesnel, J.P.; )

2006-01-01

The LHC low beta quadrupoles, have very tight alignment tolerances and are located in areas with strong radiation field. They require remote re-alignment, by motorized jacks, based on the feedback of alignment sensors of each magnet. Jacks designed to support arc cryomagnets of LHC are modified and motorized with the help of adaptors. Two types of adapters, for vertical and transverse axes of the jacks, were developed and supplied through collaboration between RRCAT, DAE, India and CERN, Geneva. This paper describes their functional requirements, manufacture and quality assurance (QA). (author)

An Adaptor Domain-Mediated Auto-Catalytic Interfacial Kinase Reaction

Science.gov (United States)

Liao, Xiaoli; Su, Jing; Mrksich, Milan

2010-01-01

This paper describes a model system for studying the auto-catalytic phosphorylation of an immobilized substrate by a kinase enzyme. This work uses self-assembled monolayers (SAMs) of alkanethiolates on gold to present the peptide substrate on a planar surface. Treatment of the monolayer with Abl kinase results in phosphorylation of the substrate. The phosphorylated peptide then serves as a ligand for the SH2 adaptor domain of the kinase and thereby directs the kinase activity to nearby peptide substrates. This directed reaction is intramolecular and proceeds with a faster rate than does the initial, intermolecular reaction, making this an auto-catalytic process. The kinetic non-linearity gives rise to properties that have no counterpart in the corresponding homogeneous phase reaction: in one example, the rate for phosphorylation of a mixture of two peptides is faster than the sum of the rates for phosphorylation of each peptide when presented alone. This work highlights the use of an adaptor domain in modulating the activity of a kinase enzyme for an immobilized substrate and offers a new approach for studying biochemical reactions in spatially inhomogeneous settings. PMID:19821459

Rapid Sampling of Hydrogen Bond Networks for Computational Protein Design.

Science.gov (United States)

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

2018-05-08

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.

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

Evidence for the additions of clustered interacting nodes during the evolution of protein interaction networks from network motifs

Directory of Open Access Journals (Sweden)

Guo Hao

2011-05-01

Full Text Available Abstract Background High-throughput screens have revealed large-scale protein interaction networks defining most cellular functions. How the proteins were added to the protein interaction network during its growth is a basic and important issue. Network motifs represent the simplest building blocks of cellular machines and are of biological significance. Results Here we study the evolution of protein interaction networks from the perspective of network motifs. We find that in current protein interaction networks, proteins of the same age class tend to form motifs and such co-origins of motif constituents are affected by their topologies and biological functions. Further, we find that the proteins within motifs whose constituents are of the same age class tend to be densely interconnected, co-evolve and share the same biological functions, and these motifs tend to be within protein complexes. Conclusions Our findings provide novel evidence for the hypothesis of the additions of clustered interacting nodes and point out network motifs, especially the motifs with the dense topology and specific function may play important roles during this process. Our results suggest functional constraints may be the underlying driving force for such additions of clustered interacting nodes.

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

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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

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.

Solution structure, dynamics and thermodynamics of the three SH3 domains of CD2AP

Energy Technology Data Exchange (ETDEWEB)

Roldan, Jose L. Ortega [Universidad de Granada, Departamento de Quimica Fisica e Instituto de Biotecnologia, Facultad de Ciencias (Spain); Blackledge, Martin [Institut de Biologie Structurale Jean-Pierre Ebel, CEA, CNRS, UJF UMR 5075, Protein Dynamics and Flexibility by NMR (France); Nuland, Nico A. J. van, E-mail: nvnuland@vub.ac.be [Vrije Universiteit Brussel, Structural Biology Brussels (Belgium); Azuaga, Ana I. [Universidad de Granada, Departamento de Quimica Fisica e Instituto de Biotecnologia, Facultad de Ciencias (Spain)

2011-06-15

CD2 associated protein (CD2AP) is an adaptor protein that plays an important role in cell to cell union needed for the kidney function. It contains three N-terminal SH3 domains that are able to interact among others with CD2, ALIX, c-Cbl and Ubiquitin. To understand the role of the individual SH3 domains of this adaptor protein we have performed a complete structural, thermodynamic and dynamic characterization of the separate domains using NMR and DSC. The energetic contributions to the stability and the backbone dynamics have been related to the structural features of each domain using the structure-based FoldX algorithm. We have found that the N-terminal SH3 domain of both adaptor proteins CD2AP and CIN85 are the most stable SH3 domains that have been studied until now. This high stability is driven by a more extensive network of intra-molecular interactions. We believe that this increased stabilization of N-terminal SH3 domains in adaptor proteins is crucial to maintain the necessary conformation to establish the proper interactions critical for the recruitment of their natural targets.

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.

Potato leafroll virus structural proteins manipulate overlapping, yet distinct protein interaction networks during infection.

Science.gov (United States)

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

2015-06-01

Potato leafroll virus (PLRV) produces a readthrough protein (RTP) via translational readthrough of the coat protein amber stop codon. The RTP functions as a structural component of the virion and as a nonincorporated protein in concert with numerous insect and plant proteins to regulate virus movement/transmission and tissue tropism. Affinity purification coupled to quantitative MS was used to generate protein interaction networks for a PLRV mutant that is unable to produce the read through domain (RTD) and compared to the known wild-type PLRV protein interaction network. By quantifying differences in the protein interaction networks, we identified four distinct classes of PLRV-plant interactions: those plant and nonstructural viral proteins interacting with assembled coat protein (category I); plant proteins in complex with both coat protein and RTD (category II); plant proteins in complex with the RTD (category III); and plant proteins that had higher affinity for virions lacking the RTD (category IV). Proteins identified as interacting with the RTD are potential candidates for regulating viral processes that are mediated by the RTP such as phloem retention and systemic movement and can potentially be useful targets for the development of strategies to prevent infection and/or viral transmission of Luteoviridae species that infect important crop species. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

ATM-Dependent Phosphorylation of All Three Members of the MRN Complex: From Sensor to Adaptor.

Science.gov (United States)

Lavin, Martin F; Kozlov, Sergei; Gatei, Magtouf; Kijas, Amanda W

2015-10-23

The recognition, signalling and repair of DNA double strand breaks (DSB) involves the participation of a multitude of proteins and post-translational events that ensure maintenance of genome integrity. Amongst the proteins involved are several which when mutated give rise to genetic disorders characterised by chromosomal abnormalities, cancer predisposition, neurodegeneration and other pathologies. ATM (mutated in ataxia-telangiectasia (A-T) and members of the Mre11/Rad50/Nbs1 (MRN complex) play key roles in this process. The MRN complex rapidly recognises and locates to DNA DSB where it acts to recruit and assist in ATM activation. ATM, in the company of several other DNA damage response proteins, in turn phosphorylates all three members of the MRN complex to initiate downstream signalling. While ATM has hundreds of substrates, members of the MRN complex play a pivotal role in mediating the downstream signalling events that give rise to cell cycle control, DNA repair and ultimately cell survival or apoptosis. Here we focus on the interplay between ATM and the MRN complex in initiating signaling of breaks and more specifically on the adaptor role of the MRN complex in mediating ATM signalling to downstream substrates to control different cellular processes.

Enhancing the Functional Content of Eukaryotic Protein Interaction Networks

Science.gov (United States)

Pandey, Gaurav; Arora, Sonali; Manocha, Sahil; Whalen, Sean

2014-01-01

Protein interaction networks are a promising type of data for studying complex biological systems. However, despite the rich information embedded in these networks, these networks face important data quality challenges of noise and incompleteness that adversely affect the results obtained from their analysis. Here, we apply a robust measure of local network structure called common neighborhood similarity (CNS) to address these challenges. Although several CNS measures have been proposed in the literature, an understanding of their relative efficacies for the analysis of interaction networks has been lacking. We follow the framework of graph transformation to convert the given interaction network into a transformed network corresponding to a variety of CNS measures evaluated. The effectiveness of each measure is then estimated by comparing the quality of protein function predictions obtained from its corresponding transformed network with those from the original network. Using a large set of human and fly protein interactions, and a set of over GO terms for both, we find that several of the transformed networks produce more accurate predictions than those obtained from the original network. In particular, the measure and other continuous CNS measures perform well this task, especially for large networks. Further investigation reveals that the two major factors contributing to this improvement are the abilities of CNS measures to prune out noisy edges and enhance functional coherence in the transformed networks. PMID:25275489

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

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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.

Protein-Protein Interaction Network and Gene Ontology

Science.gov (United States)

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

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

Protein complex prediction based on k-connected subgraphs in protein interaction network

OpenAIRE

Habibi, Mahnaz; Eslahchi, Changiz; Wong, Limsoon

2010-01-01

Abstract Background Protein complexes play an important role in cellular mechanisms. Recently, several methods have been presented to predict protein complexes in a protein interaction network. In these methods, a protein complex is predicted as a dense subgraph of protein interactions. However, interactions data are incomplete and a protein complex does not have to be a complete or dense subgraph. Results We propose a more appropriate protein complex prediction method, CFA, that is based on ...

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

Discovering functional interdependence relationship in PPI networks for protein complex identification.

Science.gov (United States)

Lam, Winnie W M; Chan, Keith C C

2012-04-01

Protein molecules interact with each other in protein complexes to perform many vital functions, and different computational techniques have been developed to identify protein complexes in protein-protein interaction (PPI) networks. These techniques are developed to search for subgraphs of high connectivity in PPI networks under the assumption that the proteins in a protein complex are highly interconnected. While these techniques have been shown to be quite effective, it is also possible that the matching rate between the protein complexes they discover and those that are previously determined experimentally be relatively low and the "false-alarm" rate can be relatively high. This is especially the case when the assumption of proteins in protein complexes being more highly interconnected be relatively invalid. To increase the matching rate and reduce the false-alarm rate, we have developed a technique that can work effectively without having to make this assumption. The name of the technique called protein complex identification by discovering functional interdependence (PCIFI) searches for protein complexes in PPI networks by taking into consideration both the functional interdependence relationship between protein molecules and the network topology of the network. The PCIFI works in several steps. The first step is to construct a multiple-function protein network graph by labeling each vertex with one or more of the molecular functions it performs. The second step is to filter out protein interactions between protein pairs that are not functionally interdependent of each other in the statistical sense. The third step is to make use of an information-theoretic measure to determine the strength of the functional interdependence between all remaining interacting protein pairs. Finally, the last step is to try to form protein complexes based on the measure of the strength of functional interdependence and the connectivity between proteins. For performance evaluation

Network based approaches reveal clustering in protein point patterns

Science.gov (United States)

Parker, Joshua; Barr, Valarie; Aldridge, Joshua; Samelson, Lawrence E.; Losert, Wolfgang

2014-03-01

Recent advances in super-resolution imaging have allowed for the sub-diffraction measurement of the spatial location of proteins on the surfaces of T-cells. The challenge is to connect these complex point patterns to the internal processes and interactions, both protein-protein and protein-membrane. We begin analyzing these patterns by forming a geometric network amongst the proteins and looking at network measures, such the degree distribution. This allows us to compare experimentally observed patterns to models. Specifically, we find that the experimental patterns differ from heterogeneous Poisson processes, highlighting an internal clustering structure. Further work will be to compare our results to simulated protein-protein interactions to determine clustering mechanisms.

Modeling of axonal endoplasmic reticulum network by spastic paraplegia proteins.

Science.gov (United States)

Yalçın, Belgin; Zhao, Lu; Stofanko, Martin; O'Sullivan, Niamh C; Kang, Zi Han; Roost, Annika; Thomas, Matthew R; Zaessinger, Sophie; Blard, Olivier; Patto, Alex L; Sohail, Anood; Baena, Valentina; Terasaki, Mark; O'Kane, Cahir J

2017-07-25

Axons contain a smooth tubular endoplasmic reticulum (ER) network that is thought to be continuous with ER throughout the neuron; the mechanisms that form this axonal network are unknown. Mutations affecting reticulon or REEP proteins, with intramembrane hairpin domains that model ER membranes, cause an axon degenerative disease, hereditary spastic paraplegia (HSP). We show that Drosophila axons have a dynamic axonal ER network, which these proteins help to model. Loss of HSP hairpin proteins causes ER sheet expansion, partial loss of ER from distal motor axons, and occasional discontinuities in axonal ER. Ultrastructural analysis reveals an extensive ER network in axons, which shows larger and fewer tubules in larvae that lack reticulon and REEP proteins, consistent with loss of membrane curvature. Therefore HSP hairpin-containing proteins are required for shaping and continuity of axonal ER, thus suggesting roles for ER modeling in axon maintenance and function.

Pythoscape: A framework for generation of large protein similarity networks

OpenAIRE

Babbitt, Patricia; Barber, AE; Babbitt, PC

2012-01-01

Pythoscape is a framework implemented in Python for processing large protein similarity networks for visualization in other software packages. Protein similarity networks are graphical representations of sequence, structural and other similarities among pr

Exploration of the dynamic properties of protein complexes predicted from spatially constrained protein-protein interaction networks.

Directory of Open Access Journals (Sweden)

Eric A Yen

2014-05-01

Full Text Available Protein complexes are not static, but rather highly dynamic with subunits that undergo 1-dimensional diffusion with respect to each other. Interactions within protein complexes are modulated through regulatory inputs that alter interactions and introduce new components and deplete existing components through exchange. While it is clear that the structure and function of any given protein complex is coupled to its dynamical properties, it remains a challenge to predict the possible conformations that complexes can adopt. Protein-fragment Complementation Assays detect physical interactions between protein pairs constrained to ≤8 nm from each other in living cells. This method has been used to build networks composed of 1000s of pair-wise interactions. Significantly, these networks contain a wealth of dynamic information, as the assay is fully reversible and the proteins are expressed in their natural context. In this study, we describe a method that extracts this valuable information in the form of predicted conformations, allowing the user to explore the conformational landscape, to search for structures that correlate with an activity state, and estimate the abundance of conformations in the living cell. The generator is based on a Markov Chain Monte Carlo simulation that uses the interaction dataset as input and is constrained by the physical resolution of the assay. We applied this method to an 18-member protein complex composed of the seven core proteins of the budding yeast Arp2/3 complex and 11 associated regulators and effector proteins. We generated 20,480 output structures and identified conformational states using principle component analysis. We interrogated the conformation landscape and found evidence of symmetry breaking, a mixture of likely active and inactive conformational states and dynamic exchange of the core protein Arc15 between core and regulatory components. Our method provides a novel tool for prediction and

Unveiling network-based functional features through integration of gene expression into protein networks.

Science.gov (United States)

Jalili, Mahdi; Gebhardt, Tom; Wolkenhauer, Olaf; Salehzadeh-Yazdi, Ali

2018-06-01

Decoding health and disease phenotypes is one of the fundamental objectives in biomedicine. Whereas high-throughput omics approaches are available, it is evident that any single omics approach might not be adequate to capture the complexity of phenotypes. Therefore, integrated multi-omics approaches have been used to unravel genotype-phenotype relationships such as global regulatory mechanisms and complex metabolic networks in different eukaryotic organisms. Some of the progress and challenges associated with integrated omics studies have been reviewed previously in comprehensive studies. In this work, we highlight and review the progress, challenges and advantages associated with emerging approaches, integrating gene expression and protein-protein interaction networks to unravel network-based functional features. This includes identifying disease related genes, gene prioritization, clustering protein interactions, developing the modules, extract active subnetworks and static protein complexes or dynamic/temporal protein complexes. We also discuss how these approaches contribute to our understanding of the biology of complex traits and diseases. This article is part of a Special Issue entitled: Cardiac adaptations to obesity, diabetes and insulin resistance, edited by Professors Jan F.C. Glatz, Jason R.B. Dyck and Christine Des Rosiers. Copyright © 2018 Elsevier B.V. All rights reserved.

A tensegrity model for hydrogen bond networks in proteins

OpenAIRE

Bywater, Robert P.

2017-01-01

Hydrogen-bonding networks in proteins considered as structural tensile elements are in balance separately from any other stabilising interactions that may be in operation. The hydrogen bond arrangement in the network is reminiscent of tensegrity structures in architecture and sculpture. Tensegrity has been discussed before in cells and tissues and in proteins. In contrast to previous work only hydrogen bonds are studied here. The other interactions within proteins are either much stronger − c...

Stimulation through the T cell receptor induces Cbl association with Crk proteins and the guanine nucleotide exchange protein C3G

NARCIS (Netherlands)

Reedquist, K. A.; Fukazawa, T.; Panchamoorthy, G.; Langdon, W. Y.; Shoelson, S. E.; Druker, B. J.; Band, H.

1996-01-01

We and others have recently identified Cbl, the protein product of the c-cbl protooncogene, as an early tyrosine kinase substrate upon T cell activation and have shown that Cbl forms in vivo complexes with Src family tyrosine kinases, Grb2 adaptor protein, and the p85 subunit of PI-3 kinase. Here we

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

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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.

Similar Pathogen Targets in Arabidopsis thaliana and Homo sapiens Protein Networks

Science.gov (United States)

2012-09-21

Similar Pathogen Targets in Arabidopsis thaliana and Homo sapiens Protein Networks Paulo Shakarian1*, J. Kenneth Wickiser2 1 Paulo Shakarian...significantly attacked. Citation: Shakarian P, Wickiser JK (2012) Similar Pathogen Targets in Arabidopsis thaliana and Homo sapiens Protein Networks...to 00-00-2012 4. TITLE AND SUBTITLE Similar Pathogen Targets in Arabidopsis thaliana and Homo sapiens Protein Networks 5a. CONTRACT NUMBER 5b

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

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.

Conservation of protein abundance patterns reveals the regulatory architecture of the EGFR-MAPK pathway

Energy Technology Data Exchange (ETDEWEB)

Shi, T.; Niepel, M.; McDermott, J. E.; Gao, Y.; Nicora, C. D.; Chrisler, W. B.; Markillie, L. M.; Petyuk, V. A.; Smith, R. D.; Rodland, K. D.; Sorger, P. K.; Qian, W. -J.; Wiley, H. S.

2016-07-12

It is not known whether cancer cells generally show quantitative differences in the expression of signaling pathway proteins that could dysregulate signal transduction. To explore this issue, we first defined the primary components of the EGF-MAPK pathway in normal human mammary epithelial cells, identifying 16 core proteins and 10 feedback regulators. We then quantified their absolute abundance across a panel of normal and cancer cell lines. We found that core pathway proteins were expressed at very similar levels across all cell types. In contrast, the EGFR and transcriptionally controlled feedback regulators were expressed at highly variable levels. The absolute abundance of most core pathway proteins was between 50,000- 70,000 copies per cell, but the adaptors SOS1, SOS2, and GAB1 were found at far lower levels (2,000-5,000 per cell). MAPK signaling showed saturation in all cells between 3,000-10,000 occupied EGFR, consistent with the idea that low adaptor levels limit signaling. Our results suggest that the core MAPK pathway is essentially invariant across different cell types, with cell- specific differences in signaling likely due to variable levels of feedback regulators. The low abundance of adaptors relative to the EGFR could be responsible for previous observation of saturable signaling, endocytosis, and high affinity EGFR.

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.

Genetic variation shapes protein networks mainly through non-transcriptional mechanisms.

Directory of Open Access Journals (Sweden)

Eric J Foss

2011-09-01

Full Text Available Networks of co-regulated transcripts in genetically diverse populations have been studied extensively, but little is known about the degree to which these networks cause similar co-variation at the protein level. We quantified 354 proteins in a genetically diverse population of yeast segregants, which allowed for the first time construction of a coherent protein co-variation matrix. We identified tightly co-regulated groups of 36 and 93 proteins that were made up predominantly of genes involved in ribosome biogenesis and amino acid metabolism, respectively. Even though the ribosomal genes were tightly co-regulated at both the protein and transcript levels, genetic regulation of proteins was entirely distinct from that of transcripts, and almost no genes in this network showed a significant correlation between protein and transcript levels. This result calls into question the widely held belief that in yeast, as opposed to higher eukaryotes, ribosomal protein levels are regulated primarily by regulating transcript levels. Furthermore, although genetic regulation of the amino acid network was more similar for proteins and transcripts, regression analysis demonstrated that even here, proteins vary predominantly as a result of non-transcriptional variation. We also found that cis regulation, which is common in the transcriptome, is rare at the level of the proteome. We conclude that most inter-individual variation in levels of these particular high abundance proteins in this genetically diverse population is not caused by variation of their underlying transcripts.

Membranes and mammalian glycolipid transferring proteins.

Science.gov (United States)

Tuuf, Jessica; Mattjus, Peter

2014-02-01

Glycolipids are synthesized in and on various organelles throughout the cell. Their trafficking inside the cell is complex and involves both vesicular and protein-mediated machineries. Most important for the bulk lipid transport is the vesicular system, however, lipids moved by transfer proteins are also becoming more characterized. Here we review the latest advances in the glycolipid transfer protein (GLTP) and the phosphoinositol 4-phosphate adaptor protein-2 (FAPP2) field, from a membrane point of view. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Caenorhabditis elegans fibroblast growth factor receptor signaling can occur independently of the multi-substrate adaptor FRS2.

Science.gov (United States)

Lo, Te-Wen; Bennett, Daniel C; Goodman, S Jay; Stern, Michael J

2010-06-01

The components of receptor tyrosine kinase signaling complexes help to define the specificity of the effects of their activation. The Caenorhabditis elegans fibroblast growth factor receptor (FGFR), EGL-15, regulates a number of processes, including sex myoblast (SM) migration guidance and fluid homeostasis, both of which require a Grb2/Sos/Ras cassette of signaling components. Here we show that SEM-5/Grb2 can bind directly to EGL-15 to mediate SM chemoattraction. A yeast two-hybrid screen identified SEM-5 as able to interact with the carboxy-terminal domain (CTD) of EGL-15, a domain that is specifically required for SM chemoattraction. This interaction requires the SEM-5 SH2-binding motifs present in the CTD (Y(1009) and Y(1087)), and these sites are required for the CTD role of EGL-15 in SM chemoattraction. SEM-5, but not the SEM-5 binding sites located in the CTD, is required for the fluid homeostasis function of EGL-15, indicating that SEM-5 can link to EGL-15 through an alternative mechanism. The multi-substrate adaptor protein FRS2 serves to link vertebrate FGFRs to Grb2. In C. elegans, an FRS2-like gene, rog-1, functions upstream of a Ras/MAPK pathway for oocyte maturation but is not required for EGL-15 function. Thus, unlike the vertebrate FGFRs, which require the multi-substrate adaptor FRS2 to recruit Grb2, EGL-15 can recruit SEM-5/Grb2 directly.

The innate immunity adaptor SARM translocates to the nucleus to stabilize lamins and prevent DNA fragmentation in response to pro-apoptotic signaling.

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Chad R Sethman

Full Text Available Sterile alpha and armadillo-motif containing protein (SARM, a highly conserved and structurally unique member of the MyD88 family of Toll-like receptor adaptors, plays an important role in innate immunity signaling and apoptosis. Its exact mechanism of intracellular action remains unclear. Apoptosis is an ancient and ubiquitous process of programmed cell death that results in disruption of the nuclear lamina and, ultimately, dismantling of the nucleus. In addition to supporting the nuclear membrane, lamins serve important roles in chromatin organization, epigenetic regulation, transcription, nuclear transport, and mitosis. Mutations and other damage that destabilize nuclear lamins (laminopathies underlie a number of intractable human diseases. Here, we report that SARM translocates to the nucleus of human embryonic kidney cells by using its amino-terminal Armadillo repeat region. Within the nucleus, SARM forms a previously unreported lattice akin to the nuclear lamina scaffold. Moreover, we show that SARM protects lamins from apoptotic degradation and reduces internucleosomal DNA fragmentation in response to signaling induced by the proinflammatory cytokine Tumor Necrosis Factor alpha. These findings indicate an important link between the innate immunity adaptor SARM and stabilization of nuclear lamins during inflammation-driven apoptosis in human cells.

Methods for the Analysis of Protein Phosphorylation-Mediated Cellular Signaling Networks

Science.gov (United States)

White, Forest M.; Wolf-Yadlin, Alejandro

2016-06-01

Protein phosphorylation-mediated cellular signaling networks regulate almost all aspects of cell biology, including the responses to cellular stimulation and environmental alterations. These networks are highly complex and comprise hundreds of proteins and potentially thousands of phosphorylation sites. Multiple analytical methods have been developed over the past several decades to identify proteins and protein phosphorylation sites regulating cellular signaling, and to quantify the dynamic response of these sites to different cellular stimulation. Here we provide an overview of these methods, including the fundamental principles governing each method, their relative strengths and weaknesses, and some examples of how each method has been applied to the analysis of complex signaling networks. When applied correctly, each of these techniques can provide insight into the topology, dynamics, and regulation of protein phosphorylation signaling networks.

New function of the adaptor protein SH2B1 in brain-derived neurotrophic factor-induced neurite outgrowth.

Directory of Open Access Journals (Sweden)

Chien-Hung Shih

Full Text Available Neurite outgrowth is an essential process for the establishment of the nervous system. Brain-derived neurotrophic factor (BDNF binds to its receptor TrkB and regulates axonal and dendritic morphology of neurons through signal transduction and gene expression. SH2B1 is a signaling adaptor protein that regulates cellular signaling in various physiological processes. The purpose of this study is to investigate the role of SH2B1 in the development of the central nervous system. In this study, we show that knocking down SH2B1 reduces neurite formation of cortical neurons whereas overexpression of SH2B1β promotes the development of hippocampal neurons. We further demonstrate that SH2B1β promotes BDNF-induced neurite outgrowth and signaling using the established PC12 cells stably expressing TrkB, SH2B1β or SH2B1β mutants. Our data indicate that overexpressing SH2B1β enhances BDNF-induced MEK-ERK1/2, and PI3K-AKT signaling pathways. Inhibition of MEK-ERK1/2 and PI3K-AKT pathways by specific inhibitors suggest that these two pathways are required for SH2B1β-promoted BDNF-induced neurite outgrowth. Moreover, SH2B1β enhances BDNF-stimulated phosphorylation of signal transducer and activator of transcription 3 at serine 727. Finally, our data indicate that the SH2 domain and tyrosine phosphorylation of SH2B1β contribute to BDNF-induced signaling pathways and neurite outgrowth. Taken together, these findings demonstrate that SH2B1β promotes BDNF-induced neurite outgrowth through enhancing pathways involved MEK-ERK1/2 and PI3K-AKT.

Ubiquitin-Mediated Regulation of Endocytosis by Proteins of the Arrestin Family

Directory of Open Access Journals (Sweden)

Michel Becuwe

2012-01-01

Full Text Available In metazoans, proteins of the arrestin family are key players of G-protein-coupled receptors (GPCRS signaling and trafficking. Following stimulation, activated receptors are phosphorylated, thus allowing the binding of arrestins and hence an “arrest” of receptor signaling. Arrestins act by uncoupling receptors from G proteins and contribute to the recruitment of endocytic proteins, such as clathrin, to direct receptor trafficking into the endocytic pathway. Arrestins also serve as adaptor proteins by promoting the recruitment of ubiquitin ligases and participate in the agonist-induced ubiquitylation of receptors, known to have impact on their subcellular localization and stability. Recently, the arrestin family has expanded following the discovery of arrestin-related proteins in other eukaryotes such as yeasts or fungi. Surprisingly, most of these proteins are also involved in the ubiquitylation and endocytosis of plasma membrane proteins, thus suggesting that the role of arrestins as ubiquitin ligase adaptors is at the core of these proteins' functions. Importantly, arrestins are themselves ubiquitylated, and this modification is crucial for their function. In this paper, we discuss recent data on the intricate connections between arrestins and the ubiquitin pathway in the control of endocytosis.

Functional modules by relating protein interaction networks and gene expression.

Science.gov (United States)

Tornow, Sabine; Mewes, H W

2003-11-01

Genes and proteins are organized on the basis of their particular mutual relations or according to their interactions in cellular and genetic networks. These include metabolic or signaling pathways and protein interaction, regulatory or co-expression networks. Integrating the information from the different types of networks may lead to the notion of a functional network and functional modules. To find these modules, we propose a new technique which is based on collective, multi-body correlations in a genetic network. We calculated the correlation strength of a group of genes (e.g. in the co-expression network) which were identified as members of a module in a different network (e.g. in the protein interaction network) and estimated the probability that this correlation strength was found by chance. Groups of genes with a significant correlation strength in different networks have a high probability that they perform the same function. Here, we propose evaluating the multi-body correlations by applying the superparamagnetic approach. We compare our method to the presently applied mean Pearson correlations and show that our method is more sensitive in revealing functional relationships.

Semantic integration to identify overlapping functional modules in protein interaction networks

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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.

A tensegrity model for hydrogen bond networks in proteins.

Science.gov (United States)

Bywater, Robert P

2017-05-01

Hydrogen-bonding networks in proteins considered as structural tensile elements are in balance separately from any other stabilising interactions that may be in operation. The hydrogen bond arrangement in the network is reminiscent of tensegrity structures in architecture and sculpture. Tensegrity has been discussed before in cells and tissues and in proteins. In contrast to previous work only hydrogen bonds are studied here. The other interactions within proteins are either much stronger - covalent bonds connecting the atoms in the molecular skeleton or weaker forces like the so-called hydrophobic interactions. It has been demonstrated that the latter operate independently from hydrogen bonds. Each category of interaction must, if the protein is to have a stable structure, balance out. The hypothesis here is that the entire hydrogen bond network is in balance without any compensating contributions from other types of interaction. For sidechain-sidechain, sidechain-backbone and backbone-backbone hydrogen bonds in proteins, tensegrity balance ("closure") is required over the entire length of the polypeptide chain that defines individually folding units in globular proteins ("domains") as well as within the repeating elements in fibrous proteins that consist of extended chain structures. There is no closure to be found in extended structures that do not have repeating elements. This suggests an explanation as to why globular domains, as well as the repeat units in fibrous proteins, have to have a defined number of residues. Apart from networks of sidechain-sidechain hydrogen bonds there are certain key points at which this closure is achieved in the sidechain-backbone hydrogen bonds and these are associated with demarcation points at the start or end of stretches of secondary structure. Together, these three categories of hydrogen bond achieve the closure that is necessary for the stability of globular protein domains as well as repeating elements in fibrous proteins.

Dynamic functional modules in co-expressed protein interaction networks of dilated cardiomyopathy

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Oyang Yen-Jen

2010-10-01

Full Text Available Abstract Background Molecular networks represent the backbone of molecular activity within cells and provide opportunities for understanding the mechanism of diseases. While protein-protein interaction data constitute static network maps, integration of condition-specific co-expression information provides clues to the dynamic features of these networks. Dilated cardiomyopathy is a leading cause of heart failure. Although previous studies have identified putative biomarkers or therapeutic targets for heart failure, the underlying molecular mechanism of dilated cardiomyopathy remains unclear. Results We developed a network-based comparative analysis approach that integrates protein-protein interactions with gene expression profiles and biological function annotations to reveal dynamic functional modules under different biological states. We found that hub proteins in condition-specific co-expressed protein interaction networks tended to be differentially expressed between biological states. Applying this method to a cohort of heart failure patients, we identified two functional modules that significantly emerged from the interaction networks. The dynamics of these modules between normal and disease states further suggest a potential molecular model of dilated cardiomyopathy. Conclusions We propose a novel framework to analyze the interaction networks in different biological states. It successfully reveals network modules closely related to heart failure; more importantly, these network dynamics provide new insights into the cause of dilated cardiomyopathy. The revealed molecular modules might be used as potential drug targets and provide new directions for heart failure therapy.

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.

MetaGO: Predicting Gene Ontology of Non-homologous Proteins Through Low-Resolution Protein Structure Prediction and Protein-Protein Network Mapping.

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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.

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

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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.

Advances in organometallic and protein chemistry

OpenAIRE

Ryan, C. P.

2010-01-01

This thesis describes two areas of scientific investigation. The first contains a description of a study on the synthesis of biotinylated and fluoresceinylated bromomaleimide based reagents. Upon synthesis, the ability of these reagents to add reversibly to cysteine containing proteins is investigated by a series of LCMS experiments. A single point mutant (L111C) of the SH2 domain of the Grb2 adaptor protein, containing a single cysteine residue, is chosen as an ideal protein for study. Thus ...

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

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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.

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

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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.

Neuron-Like Networks Between Ribosomal Proteins Within the Ribosome

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Poirot, Olivier; Timsit, Youri

2016-05-01

From brain to the World Wide Web, information-processing networks share common scale invariant properties. Here, we reveal the existence of neural-like networks at a molecular scale within the ribosome. We show that with their extensions, ribosomal proteins form complex assortative interaction networks through which they communicate through tiny interfaces. The analysis of the crystal structures of 50S eubacterial particles reveals that most of these interfaces involve key phylogenetically conserved residues. The systematic observation of interactions between basic and aromatic amino acids at the interfaces and along the extension provides new structural insights that may contribute to decipher the molecular mechanisms of signal transmission within or between the ribosomal proteins. Similar to neurons interacting through “molecular synapses”, ribosomal proteins form a network that suggest an analogy with a simple molecular brain in which the “sensory-proteins” innervate the functional ribosomal sites, while the “inter-proteins” interconnect them into circuits suitable to process the information flow that circulates during protein synthesis. It is likely that these circuits have evolved to coordinate both the complex macromolecular motions and the binding of the multiple factors during translation. This opens new perspectives on nanoscale information transfer and processing.

In vitro nuclear interactome of the HIV-1 Tat protein.

LENUS (Irish Health Repository)

Gautier, Virginie W

2009-01-01

BACKGROUND: One facet of the complexity underlying the biology of HIV-1 resides not only in its limited number of viral proteins, but in the extensive repertoire of cellular proteins they interact with and their higher-order assembly. HIV-1 encodes the regulatory protein Tat (86-101aa), which is essential for HIV-1 replication and primarily orchestrates HIV-1 provirus transcriptional regulation. Previous studies have demonstrated that Tat function is highly dependent on specific interactions with a range of cellular proteins. However they can only partially account for the intricate molecular mechanisms underlying the dynamics of proviral gene expression. To obtain a comprehensive nuclear interaction map of Tat in T-cells, we have designed a proteomic strategy based on affinity chromatography coupled with mass spectrometry. RESULTS: Our approach resulted in the identification of a total of 183 candidates as Tat nuclear partners, 90% of which have not been previously characterised. Subsequently we applied in silico analysis, to validate and characterise our dataset which revealed that the Tat nuclear interactome exhibits unique signature(s). First, motif composition analysis highlighted that our dataset is enriched for domains mediating protein, RNA and DNA interactions, and helicase and ATPase activities. Secondly, functional classification and network reconstruction clearly depicted Tat as a polyvalent protein adaptor and positioned Tat at the nexus of a densely interconnected interaction network involved in a range of biological processes which included gene expression regulation, RNA biogenesis, chromatin structure, chromosome organisation, DNA replication and nuclear architecture. CONCLUSION: We have completed the in vitro Tat nuclear interactome and have highlighted its modular network properties and particularly those involved in the coordination of gene expression by Tat. Ultimately, the highly specialised set of molecular interactions identified will

The Pch2 AAA+ ATPase promotes phosphorylation of the Hop1 meiotic checkpoint adaptor in response to synaptonemal complex defects.

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Herruzo, Esther; Ontoso, David; González-Arranz, Sara; Cavero, Santiago; Lechuga, Ana; San-Segundo, Pedro A

2016-09-19

Meiotic cells possess surveillance mechanisms that monitor critical events such as recombination and chromosome synapsis. Meiotic defects resulting from the absence of the synaptonemal complex component Zip1 activate a meiosis-specific checkpoint network resulting in delayed or arrested meiotic progression. Pch2 is an evolutionarily conserved AAA+ ATPase required for the checkpoint-induced meiotic block in the zip1 mutant, where Pch2 is only detectable at the ribosomal DNA array (nucleolus). We describe here that high levels of the Hop1 protein, a checkpoint adaptor that localizes to chromosome axes, suppress the checkpoint defect of a zip1 pch2 mutant restoring Mek1 activity and meiotic cell cycle delay. We demonstrate that the critical role of Pch2 in this synapsis checkpoint is to sustain Mec1-dependent phosphorylation of Hop1 at threonine 318. We also show that the ATPase activity of Pch2 is essential for its checkpoint function and that ATP binding to Pch2 is required for its localization. Previous work has shown that Pch2 negatively regulates Hop1 chromosome abundance during unchallenged meiosis. Based on our results, we propose that, under checkpoint-inducing conditions, Pch2 also possesses a positive action on Hop1 promoting its phosphorylation and its proper distribution on unsynapsed chromosome axes. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

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...

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

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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.

Building and analyzing protein interactome networks by cross-species comparisons

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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.

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

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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.

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

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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.

A tensegrity model for hydrogen bond networks in proteins

Directory of Open Access Journals (Sweden)

Robert P. Bywater

2017-05-01

Full Text Available Hydrogen-bonding networks in proteins considered as structural tensile elements are in balance separately from any other stabilising interactions that may be in operation. The hydrogen bond arrangement in the network is reminiscent of tensegrity structures in architecture and sculpture. Tensegrity has been discussed before in cells and tissues and in proteins. In contrast to previous work only hydrogen bonds are studied here. The other interactions within proteins are either much stronger − covalent bonds connecting the atoms in the molecular skeleton or weaker forces like the so-called hydrophobic interactions. It has been demonstrated that the latter operate independently from hydrogen bonds. Each category of interaction must, if the protein is to have a stable structure, balance out. The hypothesis here is that the entire hydrogen bond network is in balance without any compensating contributions from other types of interaction. For sidechain-sidechain, sidechain-backbone and backbone-backbone hydrogen bonds in proteins, tensegrity balance (“closure” is required over the entire length of the polypeptide chain that defines individually folding units in globular proteins (“domains” as well as within the repeating elements in fibrous proteins that consist of extended chain structures. There is no closure to be found in extended structures that do not have repeating elements. This suggests an explanation as to why globular domains, as well as the repeat units in fibrous proteins, have to have a defined number of residues. Apart from networks of sidechain-sidechain hydrogen bonds there are certain key points at which this closure is achieved in the sidechain-backbone hydrogen bonds and these are associated with demarcation points at the start or end of stretches of secondary structure. Together, these three categories of hydrogen bond achieve the closure that is necessary for the stability of globular protein domains as well as repeating

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.

The function of communities in protein interaction networks at multiple scales

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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.

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

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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.

Interplay between chaperones and protein disorder promotes the evolution of protein networks.

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Sebastian Pechmann

2014-06-01

Full Text Available Evolution is driven by mutations, which lead to new protein functions but come at a cost to protein stability. Non-conservative substitutions are of interest in this regard because they may most profoundly affect both function and stability. Accordingly, organisms must balance the benefit of accepting advantageous substitutions with the possible cost of deleterious effects on protein folding and stability. We here examine factors that systematically promote non-conservative mutations at the proteome level. Intrinsically disordered regions in proteins play pivotal roles in protein interactions, but many questions regarding their evolution remain unanswered. Similarly, whether and how molecular chaperones, which have been shown to buffer destabilizing mutations in individual proteins, generally provide robustness during proteome evolution remains unclear. To this end, we introduce an evolutionary parameter λ that directly estimates the rate of non-conservative substitutions. Our analysis of λ in Escherichia coli, Saccharomyces cerevisiae, and Homo sapiens sequences reveals how co- and post-translationally acting chaperones differentially promote non-conservative substitutions in their substrates, likely through buffering of their destabilizing effects. We further find that λ serves well to quantify the evolution of intrinsically disordered proteins even though the unstructured, thus generally variable regions in proteins are often flanked by very conserved sequences. Crucially, we show that both intrinsically disordered proteins and highly re-wired proteins in protein interaction networks, which have evolved new interactions and functions, exhibit a higher λ at the expense of enhanced chaperone assistance. Our findings thus highlight an intricate interplay of molecular chaperones and protein disorder in the evolvability of protein networks. Our results illuminate the role of chaperones in enabling protein evolution, and underline the

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

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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.

Protein Signaling Networks from Single Cell Fluctuations and Information Theory Profiling

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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

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.

Genes2Networks: connecting lists of gene symbols using mammalian protein interactions databases

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Ma'ayan Avi

2007-10-01

Full Text Available Abstract Background In recent years, mammalian protein-protein interaction network databases have been developed. The interactions in these databases are either extracted manually from low-throughput experimental biomedical research literature, extracted automatically from literature using techniques such as natural language processing (NLP, generated experimentally using high-throughput methods such as yeast-2-hybrid screens, or interactions are predicted using an assortment of computational approaches. Genes or proteins identified as significantly changing in proteomic experiments, or identified as susceptibility disease genes in genomic studies, can be placed in the context of protein interaction networks in order to assign these genes and proteins to pathways and protein complexes. Results Genes2Networks is a software system that integrates the content of ten mammalian interaction network datasets. Filtering techniques to prune low-confidence interactions were implemented. Genes2Networks is delivered as a web-based service using AJAX. The system can be used to extract relevant subnetworks created from "seed" lists of human Entrez gene symbols. The output includes a dynamic linkable three color web-based network map, with a statistical analysis report that identifies significant intermediate nodes used to connect the seed list. Conclusion Genes2Networks is powerful web-based software that can help experimental biologists to interpret lists of genes and proteins such as those commonly produced through genomic and proteomic experiments, as well as lists of genes and proteins associated with disease processes. This system can be used to find relationships between genes and proteins from seed lists, and predict additional genes or proteins that may play key roles in common pathways or protein complexes.

Interrogating the architecture of protein assemblies and protein interaction networks by cross-linking mass spectrometry

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Liu, Fan; Heck, Albert J R

2015-01-01

Proteins are involved in almost all processes of the living cell. They are organized through extensive networks of interaction, by tightly bound macromolecular assemblies or more transiently via signaling nodes. Therefore, revealing the architecture of protein complexes and protein interaction

Genetic adaptation of the antibacterial human innate immunity network.

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Casals, Ferran; Sikora, Martin; Laayouni, Hafid; Montanucci, Ludovica; Muntasell, Aura; Lazarus, Ross; Calafell, Francesc; Awadalla, Philip; Netea, Mihai G; Bertranpetit, Jaume

2011-07-11

Pathogens have represented an important selective force during the adaptation of modern human populations to changing social and other environmental conditions. The evolution of the immune system has therefore been influenced by these pressures. Genomic scans have revealed that immune system is one of the functions enriched with genes under adaptive selection. Here, we describe how the innate immune system has responded to these challenges, through the analysis of resequencing data for 132 innate immunity genes in two human populations. Results are interpreted in the context of the functional and interaction networks defined by these genes. Nucleotide diversity is lower in the adaptors and modulators functional classes, and is negatively correlated with the centrality of the proteins within the interaction network. We also produced a list of candidate genes under positive or balancing selection in each population detected by neutrality tests and showed that some functional classes are preferential targets for selection. We found evidence that the role of each gene in the network conditions the capacity to evolve or their evolvability: genes at the core of the network are more constrained, while adaptation mostly occurred at particular positions at the network edges. Interestingly, the functional classes containing most of the genes with signatures of balancing selection are involved in autoinflammatory and autoimmune diseases, suggesting a counterbalance between the beneficial and deleterious effects of the immune response.

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

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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

The DIMA web resource--exploring the protein domain network.

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Pagel, Philipp; Oesterheld, Matthias; Stümpflen, Volker; Frishman, Dmitrij

2006-04-15

Conserved domains represent essential building blocks of most known proteins. Owing to their role as modular components carrying out specific functions they form a network based both on functional relations and direct physical interactions. We have previously shown that domain interaction networks provide substantially novel information with respect to networks built on full-length protein chains. In this work we present a comprehensive web resource for exploring the Domain Interaction MAp (DIMA), interactively. The tool aims at integration of multiple data sources and prediction techniques, two of which have been implemented so far: domain phylogenetic profiling and experimentally demonstrated domain contacts from known three-dimensional structures. A powerful yet simple user interface enables the user to compute, visualize, navigate and download domain networks based on specific search criteria. http://mips.gsf.de/genre/proj/dima

NASCENT: an automatic protein interaction network generation tool for non-model organisms.

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Banky, Daniel; Ordog, Rafael; Grolmusz, Vince

2009-04-24

Large quantity of reliable protein interaction data are available for model organisms in public depositories (e.g., MINT, DIP, HPRD, INTERACT). Most data correspond to experiments with the proteins of Saccharomyces cerevisiae, Drosophila melanogaster, Homo sapiens, Caenorhabditis elegans, Escherichia coli and Mus musculus. For other important organisms the data availability is poor or non-existent. Here we present NASCENT, a completely automatic web-based tool and also a downloadable Java program, capable of modeling and generating protein interaction networks even for non-model organisms. The tool performs protein interaction network modeling through gene-name mapping, and outputs the resulting network in graphical form and also in computer-readable graph-forms, directly applicable by popular network modeling software. http://nascent.pitgroup.org.

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

Cytoprophet: a Cytoscape plug-in for protein and domain interaction networks inference.

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Morcos, Faruck; Lamanna, Charles; Sikora, Marcin; Izaguirre, Jesús

2008-10-01

Cytoprophet is a software tool that allows prediction and visualization of protein and domain interaction networks. It is implemented as a plug-in of Cytoscape, an open source software framework for analysis and visualization of molecular networks. Cytoprophet implements three algorithms that predict new potential physical interactions using the domain composition of proteins and experimental assays. The algorithms for protein and domain interaction inference include maximum likelihood estimation (MLE) using expectation maximization (EM); the set cover approach maximum specificity set cover (MSSC) and the sum-product algorithm (SPA). After accepting an input set of proteins with Uniprot ID/Accession numbers and a selected prediction algorithm, Cytoprophet draws a network of potential interactions with probability scores and GO distances as edge attributes. A network of domain interactions between the domains of the initial protein list can also be generated. Cytoprophet was designed to take advantage of the visual capabilities of Cytoscape and be simple to use. An example of inference in a signaling network of myxobacterium Myxococcus xanthus is presented and available at Cytoprophet's website. http://cytoprophet.cse.nd.edu.

Protein complex detection in PPI networks based on data integration and supervised learning method.

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Yu, Feng; Yang, Zhi; Hu, Xiao; Sun, Yuan; Lin, Hong; Wang, Jian

2015-01-01

Revealing protein complexes are important for understanding principles of cellular organization and function. High-throughput experimental techniques have produced a large amount of protein interactions, which makes it possible to predict protein complexes from protein-protein interaction (PPI) networks. However, the small amount of known physical interactions may limit protein complex detection. The new PPI networks are constructed by integrating PPI datasets with the large and readily available PPI data from biomedical literature, and then the less reliable PPI between two proteins are filtered out based on semantic similarity and topological similarity of the two proteins. Finally, the supervised learning protein complex detection (SLPC), which can make full use of the information of available known complexes, is applied to detect protein complex on the new PPI networks. The experimental results of SLPC on two different categories yeast PPI networks demonstrate effectiveness of the approach: compared with the original PPI networks, the best average improvements of 4.76, 6.81 and 15.75 percentage units in the F-score, accuracy and maximum matching ratio (MMR) are achieved respectively; compared with the denoising PPI networks, the best average improvements of 3.91, 4.61 and 12.10 percentage units in the F-score, accuracy and MMR are achieved respectively; compared with ClusterONE, the start-of the-art complex detection method, on the denoising extended PPI networks, the average improvements of 26.02 and 22.40 percentage units in the F-score and MMR are achieved respectively. The experimental results show that the performances of SLPC have a large improvement through integration of new receivable PPI data from biomedical literature into original PPI networks and denoising PPI networks. In addition, our protein complexes detection method can achieve better performance than ClusterONE.

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.

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

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

2017-02-03

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

Droplet networks with incorporated protein diodes show collective properties

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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.

Experimental and computational analysis of a large protein network that controls fat storage reveals the design principles of a signaling network.

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Al-Anzi, Bader; Arpp, Patrick; Gerges, Sherif; Ormerod, Christopher; Olsman, Noah; Zinn, Kai

2015-05-01

An approach combining genetic, proteomic, computational, and physiological analysis was used to define a protein network that regulates fat storage in budding yeast (Saccharomyces cerevisiae). A computational analysis of this network shows that it is not scale-free, and is best approximated by the Watts-Strogatz model, which generates "small-world" networks with high clustering and short path lengths. The network is also modular, containing energy level sensing proteins that connect to four output processes: autophagy, fatty acid synthesis, mRNA processing, and MAP kinase signaling. The importance of each protein to network function is dependent on its Katz centrality score, which is related both to the protein's position within a module and to the module's relationship to the network as a whole. The network is also divisible into subnetworks that span modular boundaries and regulate different aspects of fat metabolism. We used a combination of genetics and pharmacology to simultaneously block output from multiple network nodes. The phenotypic results of this blockage define patterns of communication among distant network nodes, and these patterns are consistent with the Watts-Strogatz model.

Unravelling Protein-Protein Interaction Networks Linked to Aliphatic and Indole Glucosinolate Biosynthetic Pathways in Arabidopsis

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Sebastian J. Nintemann

2017-11-01

Full Text Available Within the cell, biosynthetic pathways are embedded in protein-protein interaction networks. In Arabidopsis, the biosynthetic pathways of aliphatic and indole glucosinolate defense compounds are well-characterized. However, little is known about the spatial orchestration of these enzymes and their interplay with the cellular environment. To address these aspects, we applied two complementary, untargeted approaches—split-ubiquitin yeast 2-hybrid and co-immunoprecipitation screens—to identify proteins interacting with CYP83A1 and CYP83B1, two homologous enzymes specific for aliphatic and indole glucosinolate biosynthesis, respectively. Our analyses reveal distinct functional networks with substantial interconnection among the identified interactors for both pathway-specific markers, and add to our knowledge about how biochemical pathways are connected to cellular processes. Specifically, a group of protein interactors involved in cell death and the hypersensitive response provides a potential link between the glucosinolate defense compounds and defense against biotrophic pathogens, mediated by protein-protein interactions.

Signatures of pleiotropy, economy and convergent evolution in a domain-resolved map of human-virus protein-protein interaction networks.

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Garamszegi, Sara; Franzosa, Eric A; Xia, Yu

2013-01-01

A central challenge in host-pathogen systems biology is the elucidation of general, systems-level principles that distinguish host-pathogen interactions from within-host interactions. Current analyses of host-pathogen and within-host protein-protein interaction networks are largely limited by their resolution, treating proteins as nodes and interactions as edges. Here, we construct a domain-resolved map of human-virus and within-human protein-protein interaction networks by annotating protein interactions with high-coverage, high-accuracy, domain-centric interaction mechanisms: (1) domain-domain interactions, in which a domain in one protein binds to a domain in a second protein, and (2) domain-motif interactions, in which a domain in one protein binds to a short, linear peptide motif in a second protein. Analysis of these domain-resolved networks reveals, for the first time, significant mechanistic differences between virus-human and within-human interactions at the resolution of single domains. While human proteins tend to compete with each other for domain binding sites by means of sequence similarity, viral proteins tend to compete with human proteins for domain binding sites in the absence of sequence similarity. Independent of their previously established preference for targeting human protein hubs, viral proteins also preferentially target human proteins containing linear motif-binding domains. Compared to human proteins, viral proteins participate in more domain-motif interactions, target more unique linear motif-binding domains per residue, and contain more unique linear motifs per residue. Together, these results suggest that viruses surmount genome size constraints by convergently evolving multiple short linear motifs in order to effectively mimic, hijack, and manipulate complex host processes for their survival. Our domain-resolved analyses reveal unique signatures of pleiotropy, economy, and convergent evolution in viral-host interactions that are

Experimental and computational analysis of a large protein network that controls fat storage reveals the design principles of a signaling network.

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Bader Al-Anzi

2015-05-01

Full Text Available An approach combining genetic, proteomic, computational, and physiological analysis was used to define a protein network that regulates fat storage in budding yeast (Saccharomyces cerevisiae. A computational analysis of this network shows that it is not scale-free, and is best approximated by the Watts-Strogatz model, which generates "small-world" networks with high clustering and short path lengths. The network is also modular, containing energy level sensing proteins that connect to four output processes: autophagy, fatty acid synthesis, mRNA processing, and MAP kinase signaling. The importance of each protein to network function is dependent on its Katz centrality score, which is related both to the protein's position within a module and to the module's relationship to the network as a whole. The network is also divisible into subnetworks that span modular boundaries and regulate different aspects of fat metabolism. We used a combination of genetics and pharmacology to simultaneously block output from multiple network nodes. The phenotypic results of this blockage define patterns of communication among distant network nodes, and these patterns are consistent with the Watts-Strogatz model.

Focal adhesion kinase (FAK1 regulates SHB phosphorylation and its binding with a range of signaling proteins

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Dergai O. V.

2016-02-01

Full Text Available Aim. To investigate an effect of the Focal adhesion kinase 1 (FAK1 expression on the level of tyrosine phosphorylation of an adaptor protein SHB and to find functional consequences of this posttranslational modification. Methods. Recombinant DNA construction, protein expression and purification, human cell transfection, western blot. Results. The expression of FAK1 induces the massive tyrosine phosphorylation of SHB adaptor and enhances its interaction in vitro with SH2 domains of a range of the signaling proteins such as PI3K, ABL, CRK and PLCG1. Additionally we have found that Epstein-Barr virus protein LMP2A can partially mimic the FAK1-mediated effect strongly elevating the efficiency and SHB interaction with the mentioned above proteins. While the expression of individual proteins elevated SHB phosphorylation level, the co-expression of LMP2A and FAK1 did not display a synergetic effect. Conclusions. FAK1 as well as LMP2A induce the SHB tyrosine phosphorylation and enhance its interaction with a set of the signaling proteins.

Exploring overlapping functional units with various structure in protein interaction networks.

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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.

Nonsense mutations in ADTB3A cause complete deficiency of the beta3A subunit of adaptor complex-3 and severe Hermansky-Pudlak syndrome type 2.

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Huizing, Marjan; Scher, Charles D; Strovel, Erin; Fitzpatrick, Diana L; Hartnell, Lisa M; Anikster, Yair; Gahl, William A

2002-02-01

Hermansky-Pudlak syndrome (HPS) is an autosomal recessive disease consisting of oculocutaneous albinism and a storage pool deficiency resulting from absent platelet dense bodies. The disorder is genetically heterogeneous. The majority of patients, including members of a large genetic isolate in northwest Puerto Rico, have mutations in HPS1. Another gene, ADTB3A, was shown to cause HPS-2 in two brothers having compound heterozygous mutations that allowed for residual production of the gene product, the beta3A subunit of adaptor complex-3 (AP-3). This heterotetrameric complex serves as a coat protein-mediating formation of intracellular vesicles, e.g. the melanosome and platelet dense body, from membranes of the trans-Golgi network. We determined the genomic organization of the human ADTB3A gene, with intron/exon boundaries, and describe a third patient with beta3A deficiency. This 5-y-old boy has two nonsense mutations, C1578T (R-->X) and G2028T (E-->X), which produce no ADTB3A mRNA and no beta3A protein. The associated mu3 subunit of AP-3 is also entirely absent. In fibroblasts, the cell biologic concomitant of this deficiency is robust and aberrant trafficking through the plasma membrane of LAMP-3, an integral lysosomal membrane protein normally carried directly to the lysosome. The clinical concomitant is a severe, G-CSF-responsive neutropenia in addition to oculocutaneous albinism and platelet storage pool deficiency. Our findings expand the molecular, cellular, and clinical spectrum of HPS-2 and call for an increased index of suspicion for this diagnosis among patients with features of albinism, bleeding, and neutropenia.

The adaptor SASH1 acts through NOTCH1 and its inhibitor DLK1 in a 3D model of lumenogenesis involving CEACAM1.

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Stubblefield, Kandis; Chean, Jennifer; Nguyen, Tung; Chen, Charng-Jui; Shively, John E

2017-10-15

CEACAM1 transfection into breast cancer cells restores lumen formation in a 3D culture model. Among the top up-regulated genes that were associated with restoration of lumen formation, the adaptor protein SASH1 was identified. Furthermore, SASH1 was shown to be critical for lumen formation by RNAi inhibition. Upon analyzing the gene array from CEACAM1/MCF7 cells treated with SASH1 RNAi, DLK1, an inhibitor of NOTCH1 signaling, was found to be down-regulated to the same extent as SASH1. Subsequent treatment of CEACAM1/MCF7 cells with RNAi to DLK1 also inhibited lumen formation, supporting its association with SASH1. In agreement with the role of DLK1 as a NOTCH1 inhibitor, NOTCH1, as well as its regulated genes HES1 and HEY1, were down-regulated in CEACAM1/MCF7 cells by the action of DLK1 RNAi, and up-regulated by SASH1 RNAi. When CEACAM1/MCF7 cells were treated with a γ-secretase inhibitor known to inhibit NOTCH signaling, lumen formation was inhibited. We conclude that restoration of lumen formation by CEACAM1 regulates the NOTCH1 signaling pathway via the adaptor protein SASH1 and the NOTCH1 inhibitor DLK1. These data suggest that the putative involvement of NOTCH1 as a tumor-promoting gene in breast cancer may depend on its lack of regulation in cancer, whereas its involvement in normal lumen formation requires activation of its expression, and subsequently, inhibition of its signaling. Copyright © 2017 Elsevier Inc. All rights reserved.

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

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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

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

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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

Protein Secondary Structure Prediction Using AutoEncoder Network and Bayes Classifier

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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.

Integration of relational and hierarchical network information for protein function prediction

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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

Identifying essential proteins based on sub-network partition and prioritization by integrating subcellular localization information.

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

2018-06-14

Essential proteins are important participants in various life activities and play a vital role in the survival and reproduction of living organisms. Identification of essential proteins from protein-protein interaction (PPI) networks has great significance to facilitate the study of human complex diseases, the design of drugs and the development of bioinformatics and computational science. Studies have shown that highly connected proteins in a PPI network tend to be essential. A series of computational methods have been proposed to identify essential proteins by analyzing topological structures of PPI networks. However, the high noise in the PPI data can degrade the accuracy of essential protein prediction. Moreover, proteins must be located in the appropriate subcellular localization to perform their functions, and only when the proteins are located in the same subcellular localization, it is possible that they can interact with each other. In this paper, we propose a new network-based essential protein discovery method based on sub-network partition and prioritization by integrating subcellular localization information, named SPP. The proposed method SPP was tested on two different yeast PPI networks obtained from DIP database and BioGRID database. The experimental results show that SPP can effectively reduce the effect of false positives in PPI networks and predict essential proteins more accurately compared with other existing computational methods DC, BC, CC, SC, EC, IC, NC. Copyright © 2018 Elsevier Ltd. All rights reserved.

Hepatitis C Virus Protein Interaction Network Analysis Based on Hepatocellular Carcinoma.

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Yuewen Han

Full Text Available Epidemiological studies have validated the association between hepatitis C virus (HCV infection and hepatocellular carcinoma (HCC. An increasing number of studies show that protein-protein interactions (PPIs between HCV proteins and host proteins play a vital role in infection and mediate HCC progression. In this work, we collected all published interaction between HCV and human proteins, which include 455 unique human proteins participating in 524 HCV-human interactions. Then, we construct the HCV-human and HCV-HCC protein interaction networks, which display the biological knowledge regarding the mechanism of HCV pathogenesis, particularly with respect to pathogenesis of HCC. Through in-depth analysis of the HCV-HCC interaction network, we found that interactors are enriched in the JAK/STAT, p53, MAPK, TNF, Wnt, and cell cycle pathways. Using a random walk with restart algorithm, we predicted the importance of each protein in the HCV-HCC network and found that AKT1 may play a key role in the HCC progression. Moreover, we found that NS5A promotes HCC cells proliferation and metastasis by activating AKT/GSK3β/β-catenin pathway. This work provides a basis for a detailed map tracking new cellular interactions of HCV and identifying potential targets for HCV-related hepatocellular carcinoma treatment.

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

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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

Protein Inference from the Integration of Tandem MS Data and Interactome Networks.

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Zhong, Jiancheng; Wang, Jianxing; Ding, Xiaojun; Zhang, Zhen; Li, Min; Wu, Fang-Xiang; Pan, Yi

2017-01-01

Since proteins are digested into a mixture of peptides in the preprocessing step of tandem mass spectrometry (MS), it is difficult to determine which specific protein a shared peptide belongs to. In recent studies, besides tandem MS data and peptide identification information, some other information is exploited to infer proteins. Different from the methods which first use only tandem MS data to infer proteins and then use network information to refine them, this study proposes a protein inference method named TMSIN, which uses interactome networks directly. As two interacting proteins should co-exist, it is reasonable to assume that if one of the interacting proteins is confidently inferred in a sample, its interacting partners should have a high probability in the same sample, too. Therefore, we can use the neighborhood information of a protein in an interactome network to adjust the probability that the shared peptide belongs to the protein. In TMSIN, a multi-weighted graph is constructed by incorporating the bipartite graph with interactome network information, where the bipartite graph is built with the peptide identification information. Based on multi-weighted graphs, TMSIN adopts an iterative workflow to infer proteins. At each iterative step, the probability that a shared peptide belongs to a specific protein is calculated by using the Bayes' law based on the neighbor protein support scores of each protein which are mapped by the shared peptides. We carried out experiments on yeast data and human data to evaluate the performance of TMSIN in terms of ROC, q-value, and accuracy. The experimental results show that AUC scores yielded by TMSIN are 0.742 and 0.874 in yeast dataset and human dataset, respectively, and TMSIN yields the maximum number of true positives when q-value less than or equal to 0.05. The overlap analysis shows that TMSIN is an effective complementary approach for protein inference.

Dynamical analysis of yeast protein interaction network during the sake brewing process.

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Mirzarezaee, Mitra; Sadeghi, Mehdi; Araabi, Babak N

2011-12-01

Proteins interact with each other for performing essential functions of an organism. They change partners to get involved in various processes at different times or locations. Studying variations of protein interactions within a specific process would help better understand the dynamic features of the protein interactions and their functions. We studied the protein interaction network of Saccharomyces cerevisiae (yeast) during the brewing of Japanese sake. In this process, yeast cells are exposed to several stresses. Analysis of protein interaction networks of yeast during this process helps to understand how protein interactions of yeast change during the sake brewing process. We used gene expression profiles of yeast cells for this purpose. Results of our experiments revealed some characteristics and behaviors of yeast hubs and non-hubs and their dynamical changes during the brewing process. We found that just a small portion of the proteins (12.8 to 21.6%) is responsible for the functional changes of the proteins in the sake brewing process. The changes in the number of edges and hubs of the yeast protein interaction networks increase in the first stages of the process and it then decreases at the final stages.

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

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Wuchty, Stefan

2006-05-23

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. 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. 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 show a simple way to predict potential protein interactions

Genetic adaptation of the antibacterial human innate immunity network

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Lazarus Ross

2011-07-01

Full Text Available Abstract Background Pathogens have represented an important selective force during the adaptation of modern human populations to changing social and other environmental conditions. The evolution of the immune system has therefore been influenced by these pressures. Genomic scans have revealed that immune system is one of the functions enriched with genes under adaptive selection. Results Here, we describe how the innate immune system has responded to these challenges, through the analysis of resequencing data for 132 innate immunity genes in two human populations. Results are interpreted in the context of the functional and interaction networks defined by these genes. Nucleotide diversity is lower in the adaptors and modulators functional classes, and is negatively correlated with the centrality of the proteins within the interaction network. We also produced a list of candidate genes under positive or balancing selection in each population detected by neutrality tests and showed that some functional classes are preferential targets for selection. Conclusions We found evidence that the role of each gene in the network conditions the capacity to evolve or their evolvability: genes at the core of the network are more constrained, while adaptation mostly occurred at particular positions at the network edges. Interestingly, the functional classes containing most of the genes with signatures of balancing selection are involved in autoinflammatory and autoimmune diseases, suggesting a counterbalance between the beneficial and deleterious effects of the immune response.

Scalable rule-based modelling of allosteric proteins and biochemical networks.

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Julien F Ollivier

2010-11-01

Full Text Available Much of the complexity of biochemical networks comes from the information-processing abilities of allosteric proteins, be they receptors, ion-channels, signalling molecules or transcription factors. An allosteric protein can be uniquely regulated by each combination of input molecules that it binds. This "regulatory complexity" causes a combinatorial increase in the number of parameters required to fit experimental data as the number of protein interactions increases. It therefore challenges the creation, updating, and re-use of biochemical models. Here, we propose a rule-based modelling framework that exploits the intrinsic modularity of protein structure to address regulatory complexity. Rather than treating proteins as "black boxes", we model their hierarchical structure and, as conformational changes, internal dynamics. By modelling the regulation of allosteric proteins through these conformational changes, we often decrease the number of parameters required to fit data, and so reduce over-fitting and improve the predictive power of a model. Our method is thermodynamically grounded, imposes detailed balance, and also includes molecular cross-talk and the background activity of enzymes. We use our Allosteric Network Compiler to examine how allostery can facilitate macromolecular assembly and how competitive ligands can change the observed cooperativity of an allosteric protein. We also develop a parsimonious model of G protein-coupled receptors that explains functional selectivity and can predict the rank order of potency of agonists acting through a receptor. Our methodology should provide a basis for scalable, modular and executable modelling of biochemical networks in systems and synthetic biology.

Signatures of pleiotropy, economy and convergent evolution in a domain-resolved map of human-virus protein-protein interaction networks.

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Sara Garamszegi

Full Text Available A central challenge in host-pathogen systems biology is the elucidation of general, systems-level principles that distinguish host-pathogen interactions from within-host interactions. Current analyses of host-pathogen and within-host protein-protein interaction networks are largely limited by their resolution, treating proteins as nodes and interactions as edges. Here, we construct a domain-resolved map of human-virus and within-human protein-protein interaction networks by annotating protein interactions with high-coverage, high-accuracy, domain-centric interaction mechanisms: (1 domain-domain interactions, in which a domain in one protein binds to a domain in a second protein, and (2 domain-motif interactions, in which a domain in one protein binds to a short, linear peptide motif in a second protein. Analysis of these domain-resolved networks reveals, for the first time, significant mechanistic differences between virus-human and within-human interactions at the resolution of single domains. While human proteins tend to compete with each other for domain binding sites by means of sequence similarity, viral proteins tend to compete with human proteins for domain binding sites in the absence of sequence similarity. Independent of their previously established preference for targeting human protein hubs, viral proteins also preferentially target human proteins containing linear motif-binding domains. Compared to human proteins, viral proteins participate in more domain-motif interactions, target more unique linear motif-binding domains per residue, and contain more unique linear motifs per residue. Together, these results suggest that viruses surmount genome size constraints by convergently evolving multiple short linear motifs in order to effectively mimic, hijack, and manipulate complex host processes for their survival. Our domain-resolved analyses reveal unique signatures of pleiotropy, economy, and convergent evolution in viral

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

International Nuclear Information System (INIS)

Ba, Qian; Li, Junyang; Huang, Chao; Li, Jingquan; Chu, Ruiai; Wu, Yongning; Wang, Hui

2015-01-01

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

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.

P³DB 3.0: From plant phosphorylation sites to protein networks.

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Yao, Qiuming; Ge, Huangyi; Wu, Shangquan; Zhang, Ning; Chen, Wei; Xu, Chunhui; Gao, Jianjiong; Thelen, Jay J; Xu, Dong

2014-01-01

In the past few years, the Plant Protein Phosphorylation Database (P(3)DB, http://p3db.org) has become one of the most significant in vivo data resources for studying plant phosphoproteomics. We have substantially updated P(3)DB with respect to format, new datasets and analytic tools. In the P(3)DB 3.0, there are altogether 47 923 phosphosites in 16 477 phosphoproteins curated across nine plant organisms from 32 studies, which have met our multiple quality standards for acquisition of in vivo phosphorylation site data. Centralized by these phosphorylation data, multiple related data and annotations are provided, including protein-protein interaction (PPI), gene ontology, protein tertiary structures, orthologous sequences, kinase/phosphatase classification and Kinase Client Assay (KiC Assay) data--all of which provides context for the phosphorylation event. In addition, P(3)DB 3.0 incorporates multiple network viewers for the above features, such as PPI network, kinase-substrate network, phosphatase-substrate network, and domain co-occurrence network to help study phosphorylation from a systems point of view. Furthermore, the new P(3)DB reflects a community-based design through which users can share datasets and automate data depository processes for publication purposes. Each of these new features supports the goal of making P(3)DB a comprehensive, systematic and interactive platform for phosphoproteomics research.

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

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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.

The Oncogenic Palmitoyi-Protein Network in Prostate Cancer

Science.gov (United States)

2015-06-01

was performed by comparing LFQ intensities computed by MaxQuant.16 After statistical analysis, we identified 29 significantly downregulated and 32... statistical analysis, 30 candidate palmitoyl-proteins with an H/L ratio cutoff of 0.667 were accepted as candidate DHHC3 substrates (Table 1). Among...proteomics, we identified a gigantic palmitoyl-protein network regulated by caveolin-1. Moreover, by integrating RNA interference (RNAi), triplex SILAC, and

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

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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.

How does the antagonism between capping and anti-capping proteins affect actin network dynamics?

International Nuclear Information System (INIS)

Hu Longhua; Papoian, Garegin A

2011-01-01

Actin-based cell motility is essential to many biological processes. We built a simplified, three-dimensional computational model and subsequently performed stochastic simulations to study the growth dynamics of lamellipodia-like branched networks. In this work, we shed light on the antagonism between capping and anti-capping proteins in regulating actin dynamics in the filamentous network. We discuss detailed mechanisms by which capping and anti-capping proteins affect the protrusion speed of the actin network and the rate of nucleation of filaments. We computed a phase diagram showing the regimes of motility enhancement and inhibition by these proteins. Our work shows that the effects of capping and anti-capping proteins are mainly transmitted by modulation of the filamentous network density and local availability of monomeric actin. We discovered that the combination of the capping/anti-capping regulatory network with nucleation-promoting proteins introduces robustness and redundancy in cell motility machinery, allowing the cell to easily achieve maximal protrusion speeds under a broader set of conditions. Finally, we discuss distributions of filament lengths under various conditions and speculate on their potential implication for the emergence of filopodia from the lamellipodial network.

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

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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.

Nuclear adaptor Ldb1 regulates a transcriptional program essential for the maintenance of hematopoietic stem cells.

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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.

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

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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

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

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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.

A Deep Learning Network Approach to ab initio Protein Secondary Structure Prediction.

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Spencer, Matt; Eickholt, Jesse; Jianlin Cheng

2015-01-01

Ab initio protein secondary structure (SS) predictions are utilized to generate tertiary structure predictions, which are increasingly demanded due to the rapid discovery of proteins. Although recent developments have slightly exceeded previous methods of SS prediction, accuracy has stagnated around 80 percent and many wonder if prediction cannot be advanced beyond this ceiling. Disciplines that have traditionally employed neural networks are experimenting with novel deep learning techniques in attempts to stimulate progress. Since neural networks have historically played an important role in SS prediction, we wanted to determine whether deep learning could contribute to the advancement of this field as well. We developed an SS predictor that makes use of the position-specific scoring matrix generated by PSI-BLAST and deep learning network architectures, which we call DNSS. Graphical processing units and CUDA software optimize the deep network architecture and efficiently train the deep networks. Optimal parameters for the training process were determined, and a workflow comprising three separately trained deep networks was constructed in order to make refined predictions. This deep learning network approach was used to predict SS for a fully independent test dataset of 198 proteins, achieving a Q3 accuracy of 80.7 percent and a Sov accuracy of 74.2 percent.

Effect of dataset selection on the topological interpretation of protein interaction networks

Directory of Open Access Journals (Sweden)

Robertson David L

2005-09-01

Full Text Available Abstract Background Studies of the yeast protein interaction network have revealed distinct correlations between the connectivity of individual proteins within the network and the average connectivity of their neighbours. Although a number of biological mechanisms have been proposed to account for these findings, the significance and influence of the specific datasets included in these studies has not been appreciated adequately. Results We show how the use of different interaction data sets, such as those resulting from high-throughput or small-scale studies, and different modelling methodologies for the derivation pair-wise protein interactions, can dramatically change the topology of these networks. Furthermore, we show that some of the previously reported features identified in these networks may simply be the result of experimental or methodological errors and biases. Conclusion When performing network-based studies, it is essential to define what is meant by the term "interaction" and this must be taken into account when interpreting the topologies of the networks generated. Consideration must be given to the type of data included and appropriate controls that take into account the idiosyncrasies of the data must be selected

Rett networked database

DEFF Research Database (Denmark)

Grillo, Elisa; Villard, Laurent; Clarke, Angus

2012-01-01

Rett syndrome (RTT) is a neurodevelopmental disorder with one principal phenotype and several distinct, atypical variants (Zappella, early seizure onset and congenital variants). Mutations in MECP2 are found in most cases of classic RTT but at least two additional genes, CDKL5 and FOXG1, can unde...... clinical features and mutations. We expect that the network will serve for the recruitment of patients into clinical trials and for developing quality measures to drive up standards of medical management....... underlie some (usually variant) cases. There is only limited correlation between genotype and phenotype. The Rett Networked Database (http://www.rettdatabasenetwork.org/) has been established to share clinical and genetic information. Through an "adaptor" process of data harmonization, a set of 293...... can expand indefinitely. Data are entered by a clinician in each center who supervises accuracy. This network was constructed to make available pooled international data for the study of RTT natural history and genotype-phenotype correlation and to indicate the proportion of patients with specific...

A Global Protein Kinase and Phosphatase Interaction Network in Yeast

Science.gov (United States)

Breitkreutz, Ashton; Choi, Hyungwon; Sharom, Jeffrey R.; Boucher, Lorrie; Neduva, Victor; Larsen, Brett; Lin, Zhen-Yuan; Breitkreutz, Bobby-Joe; Stark, Chris; Liu, Guomin; Ahn, Jessica; Dewar-Darch, Danielle; Reguly, Teresa; Tang, Xiaojing; Almeida, Ricardo; Qin, Zhaohui Steve; Pawson, Tony; Gingras, Anne-Claude; Nesvizhskii, Alexey I.; Tyers, Mike

2011-01-01

The interactions of protein kinases and phosphatases with their regulatory subunits and substrates underpin cellular regulation. We identified a kinase and phosphatase interaction (KPI) network of 1844 interactions in budding yeast by mass spectrometric analysis of protein complexes. The KPI network contained many dense local regions of interactions that suggested new functions. Notably, the cell cycle phosphatase Cdc14 associated with multiple kinases that revealed roles for Cdc14 in mitogen-activated protein kinase signaling, the DNA damage response, and metabolism, whereas interactions of the target of rapamycin complex 1 (TORC1) uncovered new effector kinases in nitrogen and carbon metabolism. An extensive backbone of kinase-kinase interactions cross-connects the proteome and may serve to coordinate diverse cellular responses. PMID:20489023

NPPD: A Protein-Protein Docking Scoring Function Based on Dyadic Differences in Networks of Hydrophobic and Hydrophilic Amino Acid Residues

Directory of Open Access Journals (Sweden)

Edward S. C. Shih

2015-03-01

Full Text Available Protein-protein docking (PPD predictions usually rely on the use of a scoring function to rank docking models generated by exhaustive sampling. To rank good models higher than bad ones, a large number of scoring functions have been developed and evaluated, but the methods used for the computation of PPD predictions remain largely unsatisfactory. Here, we report a network-based PPD scoring function, the NPPD, in which the network consists of two types of network nodes, one for hydrophobic and the other for hydrophilic amino acid residues, and the nodes are connected when the residues they represent are within a certain contact distance. We showed that network parameters that compute dyadic interactions and those that compute heterophilic interactions of the amino acid networks thus constructed allowed NPPD to perform well in a benchmark evaluation of 115 PPD scoring functions, most of which, unlike NPPD, are based on some sort of protein-protein interaction energy. We also showed that NPPD was highly complementary to these energy-based scoring functions, suggesting that the combined use of conventional scoring functions and NPPD might significantly improve the accuracy of current PPD predictions.

Chaperone-protease networks in mitochondrial protein homeostasis.

Science.gov (United States)

Voos, Wolfgang

2013-02-01

As essential organelles, mitochondria are intimately integrated into the metabolism of a eukaryotic cell. The maintenance of the functional integrity of the mitochondrial proteome, also termed protein homeostasis, is facing many challenges both under normal and pathological conditions. First, since mitochondria are derived from bacterial ancestor cells, the proteins in this endosymbiotic organelle have a mixed origin. Only a few proteins are encoded on the mitochondrial genome, most genes for mitochondrial proteins reside in the nuclear genome of the host cell. This distribution requires a complex biogenesis of mitochondrial proteins, which are mostly synthesized in the cytosol and need to be imported into the organelle. Mitochondrial protein biogenesis usually therefore comprises complex folding and assembly processes to reach an enzymatically active state. In addition, specific protein quality control (PQC) processes avoid an accumulation of damaged or surplus polypeptides. Mitochondrial protein homeostasis is based on endogenous enzymatic components comprising a diverse set of chaperones and proteases that form an interconnected functional network. This review describes the different types of mitochondrial proteins with chaperone functions and covers the current knowledge of their roles in protein biogenesis, folding, proteolytic removal and prevention of aggregation, the principal reactions of protein homeostasis. This article is part of a Special Issue entitled: Protein Import and Quality Control in Mitochondria and Plastids. Copyright © 2012 Elsevier B.V. All rights reserved.

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

OpenAIRE

Junge, Alexander; Refsgaard, Jan Christian; Garde, Christian; Pan, Xiaoyong; Santos Delgado, Alberto; Anthon, Christian; Alkan, Ferhat; von Mering, Christian; Workman, Christopher; Jensen, Lars Juhl; Gorodkin, Jan

2015-01-01

Non-coding RNAs (ncRNAs) fulfill a diverse set of biological functions relying on interactions with other molecular entities. The advent of new experimental and computational approaches makes it possible to study ncRNAs and their associations on an unprecedented scale. We present RAIN (RNA 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 int...

An attempt to understand glioma stem cell biology through centrality analysis of a protein interaction network.

Science.gov (United States)

Mallik, Mrinmay Kumar

2018-02-07

Biological networks can be analyzed using "Centrality Analysis" to identify the more influential nodes and interactions in the network. This study was undertaken to create and visualize a biological network comprising of protein-protein interactions (PPIs) amongst proteins which are preferentially over-expressed in glioma cancer stem cell component (GCSC) of glioblastomas as compared to the glioma non-stem cancer cell (GNSC) component and then to analyze this network through centrality analyses (CA) in order to identify the essential proteins in this network and their interactions. In addition, this study proposes a new centrality analysis method pertaining exclusively to transcription factors (TFs) and interactions amongst them. Moreover the relevant molecular functions, biological processes and biochemical pathways amongst these proteins were sought through enrichment analysis. A protein interaction network was created using a list of proteins which have been shown to be preferentially expressed or over-expressed in GCSCs isolated from glioblastomas as compared to the GNSCs. This list comprising of 38 proteins, created using manual literature mining, was submitted to the Reactome FIViz tool, a web based application integrated into Cytoscape, an open source software platform for visualizing and analyzing molecular interaction networks and biological pathways to produce the network. This network was subjected to centrality analyses utilizing ranked lists of six centrality measures using the FIViz application and (for the first time) a dedicated centrality analysis plug-in ; CytoNCA. The interactions exclusively amongst the transcription factors were nalyzed through a newly proposed centrality analysis method called "Gene Expression Associated Degree Centrality Analysis (GEADCA)". Enrichment analysis was performed using the "network function analysis" tool on Reactome. The CA was able to identify a small set of proteins with consistently high centrality ranks that

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.

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

Energy Technology Data Exchange (ETDEWEB)

Pei, Guangsheng; Chen, Lei; Wang, Jiangxin; Qiao, Jianjun, E-mail: jianjunq@tju.edu.cn; Zhang, Weiwen, E-mail: jianjunq@tju.edu.cn [Laboratory of Synthetic Microbiology, School of Chemical Engineering and Technology, Tianjin University, Tianjin (China); Key Laboratory of Systems Bioengineering, Ministry of Education of China, Tianjin (China); SynBio Research Platform, Collaborative Innovation Center of Chemical Science and Engineering, Tianjin (China)

2014-11-03

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.

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

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.

Mining protein interactomes to improve their reliability and support the advancement of network medicine

Directory of Open Access Journals (Sweden)

Gregorio eAlanis-Lobato

2015-09-01

Full Text Available 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 aetiology. 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.

RRW: repeated random walks on genome-scale protein networks for local cluster discovery

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Can Tolga

2009-09-01

Full Text Available Abstract Background We propose an efficient and biologically sensitive algorithm based on repeated random walks (RRW for discovering functional modules, e.g., complexes and pathways, within large-scale protein networks. Compared to existing cluster identification techniques, RRW implicitly makes use of network topology, edge weights, and long range interactions between proteins. Results We apply the proposed technique on a functional network of yeast genes and accurately identify statistically significant clusters of proteins. We validate the biological significance of the results using known complexes in the MIPS complex catalogue database and well-characterized biological processes. We find that 90% of the created clusters have the majority of their catalogued proteins belonging to the same MIPS complex, and about 80% have the majority of their proteins involved in the same biological process. We compare our method to various other clustering techniques, such as the Markov Clustering Algorithm (MCL, and find a significant improvement in the RRW clusters' precision and accuracy values. Conclusion RRW, which is a technique that exploits the topology of the network, is more precise and robust in finding local clusters. In addition, it has the added flexibility of being able to find multi-functional proteins by allowing overlapping clusters.

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

proteins. Despite the value of BioGRID for studying protein-protein interactions, there is a need for manual curation of these interactions in order to remove false positives. RESULTS: Here we describe an annotated reconstruction of the protein-protein interactions around four key nutrient......) and for all the interactions between them (edges). The annotated information is readily available utilizing the functionalities of network modelling tools such as Cytoscape and CellDesigner. CONCLUSIONS: The reported fully annotated interaction model serves as a platform for integrated systems biology studies...

Supervised maximum-likelihood weighting of composite protein networks for complex prediction

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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

Using sequence similarity networks for visualization of relationships across diverse protein superfamilies.

Directory of Open Access Journals (Sweden)

Holly J Atkinson

Full Text Available The dramatic increase in heterogeneous types of biological data--in particular, the abundance of new protein sequences--requires fast and user-friendly methods for organizing this information in a way that enables functional inference. The most widely used strategy to link sequence or structure to function, homology-based function prediction, relies on the fundamental assumption that sequence or structural similarity implies functional similarity. New tools that extend this approach are still urgently needed to associate sequence data with biological information in ways that accommodate the real complexity of the problem, while being accessible to experimental as well as computational biologists. To address this, we have examined the application of sequence similarity networks for visualizing functional trends across protein superfamilies from the context of sequence similarity. Using three large groups of homologous proteins of varying types of structural and functional diversity--GPCRs and kinases from humans, and the crotonase superfamily of enzymes--we show that overlaying networks with orthogonal information is a powerful approach for observing functional themes and revealing outliers. In comparison to other primary methods, networks provide both a good representation of group-wise sequence similarity relationships and a strong visual and quantitative correlation with phylogenetic trees, while enabling analysis and visualization of much larger sets of sequences than trees or multiple sequence alignments can easily accommodate. We also define important limitations and caveats in the application of these networks. As a broadly accessible and effective tool for the exploration of protein superfamilies, sequence similarity networks show great potential for generating testable hypotheses about protein structure-function relationships.

Using sequence similarity networks for visualization of relationships across diverse protein superfamilies.

Science.gov (United States)

Atkinson, Holly J; Morris, John H; Ferrin, Thomas E; Babbitt, Patricia C

2009-01-01

The dramatic increase in heterogeneous types of biological data--in particular, the abundance of new protein sequences--requires fast and user-friendly methods for organizing this information in a way that enables functional inference. The most widely used strategy to link sequence or structure to function, homology-based function prediction, relies on the fundamental assumption that sequence or structural similarity implies functional similarity. New tools that extend this approach are still urgently needed to associate sequence data with biological information in ways that accommodate the real complexity of the problem, while being accessible to experimental as well as computational biologists. To address this, we have examined the application of sequence similarity networks for visualizing functional trends across protein superfamilies from the context of sequence similarity. Using three large groups of homologous proteins of varying types of structural and functional diversity--GPCRs and kinases from humans, and the crotonase superfamily of enzymes--we show that overlaying networks with orthogonal information is a powerful approach for observing functional themes and revealing outliers. In comparison to other primary methods, networks provide both a good representation of group-wise sequence similarity relationships and a strong visual and quantitative correlation with phylogenetic trees, while enabling analysis and visualization of much larger sets of sequences than trees or multiple sequence alignments can easily accommodate. We also define important limitations and caveats in the application of these networks. As a broadly accessible and effective tool for the exploration of protein superfamilies, sequence similarity networks show great potential for generating testable hypotheses about protein structure-function relationships.

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.

Pitch adaptors of the ATLAS-SCT Endcap detector modules

International Nuclear Information System (INIS)

Ullan, M; Lozano, M; Campabadal, F; Fleta, C; Pellegrini, G; Garcia, C; Gonzalez, F

2007-01-01

Interconnection between detectors and electronics in modern High Energy Physics has become an issue of difficult solution due to the need to integrate both parts in the same module and the need for a low mass, simple connection. The Endcap section of the Semiconductor Tracker (SCT) of the ATLAS experiment at CERN has adopted the solution of using interface devices called pitch adaptors or fan-ins that, mounted on the modules, and using automatic wire bonding, connect the detector's multiple channels to the front-end electronics, adapting their different designs (pad pitch, dimensions, position). This paper describes the characteristics of these devices, the qualification tests that they have been submitted to, and the final results of their fabrication including quality assurance procedures

Differential splicing of the apoptosis-associated speck like protein containing a caspase recruitment domain (ASC regulates inflammasomes

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Rojanasakul Yon

2010-05-01

Full Text Available Abstract Background The apoptotic speck-like protein containing a caspase recruitment domain (ASC is the essential adaptor protein for caspase 1 mediated interleukin (IL-1β and IL-18 processing in inflammasomes. It bridges activated Nod like receptors (NLRs, which are a family of cytosolic pattern recognition receptors of the innate immune system, with caspase 1, resulting in caspase 1 activation and subsequent processing of caspase 1 substrates. Hence, macrophages from ASC deficient mice are impaired in their ability to produce bioactive IL-1β. Furthermore, we recently showed that ASC translocates from the nucleus to the cytosol in response to inflammatory stimulation in order to promote an inflammasome response, which triggers IL-1β processing and secretion. However, the precise regulation of inflammasomes at the level of ASC is still not completely understood. In this study we identified and characterized three novel ASC isoforms for their ability to function as an inflammasome adaptor. Methods To establish the ability of ASC and ASC isoforms as functional inflammasome adaptors, IL-1β processing and secretion was investigated by ELISA in inflammasome reconstitution assays, stable expression in THP-1 and J774A1 cells, and by restoring the lack of endogenous ASC in mouse RAW264.7 macrophages. In addition, the localization of ASC and ASC isoforms was determined by immunofluorescence staining. Results The three novel ASC isoforms, ASC-b, ASC-c and ASC-d display unique and distinct capabilities to each other and to full length ASC in respect to their function as an inflammasome adaptor, with one of the isoforms even showing an inhibitory effect. Consistently, only the activating isoforms of ASC, ASC and ASC-b, co-localized with NLRP3 and caspase 1, while the inhibitory isoform ASC-c, co-localized only with caspase 1, but not with NLRP3. ASC-d did not co-localize with NLRP3 or with caspase 1 and consistently lacked the ability to function as an

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.

Evolution of a G protein-coupled receptor response by mutations in regulatory network interactions

DEFF Research Database (Denmark)

Di Roberto, Raphaël B; Chang, Belinda; Trusina, Ala

2016-01-01

All cellular functions depend on the concerted action of multiple proteins organized in complex networks. To understand how selection acts on protein networks, we used the yeast mating receptor Ste2, a pheromone-activated G protein-coupled receptor, as a model system. In Saccharomyces cerevisiae......, Ste2 is a hub in a network of interactions controlling both signal transduction and signal suppression. Through laboratory evolution, we obtained 21 mutant receptors sensitive to the pheromone of a related yeast species and investigated the molecular mechanisms behind this newfound sensitivity. While...... demonstrate that a new receptor-ligand pair can evolve through network-altering mutations independently of receptor-ligand binding, and suggest a potential role for such mutations in disease....

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.

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......-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...

Treating the Synapse in Major Psychiatric Disorders: The Role of Postsynaptic Density Network in Dopamine-Glutamate Interplay and Psychopharmacologic Drugs Molecular Actions

Directory of Open Access Journals (Sweden)

Carmine Tomasetti

2017-01-01

Full Text Available Dopamine-glutamate interplay dysfunctions have been suggested as pathophysiological key determinants of major psychotic disorders, above all schizophrenia and mood disorders. For the most part, synaptic interactions between dopamine and glutamate signaling pathways take part in the postsynaptic density, a specialized ultrastructure localized under the membrane of glutamatergic excitatory synapses. Multiple proteins, with the role of adaptors, regulators, effectors, and scaffolds compose the postsynaptic density network. They form structural and functional crossroads where multiple signals, starting at membrane receptors, are received, elaborated, integrated, and routed to appropriate nuclear targets. Moreover, transductional pathways belonging to different receptors may be functionally interconnected through postsynaptic density molecules. Several studies have demonstrated that psychopharmacologic drugs may differentially affect the expression and function of postsynaptic genes and proteins, depending upon the peculiar receptor profile of each compound. Thus, through postsynaptic network modulation, these drugs may induce dopamine-glutamate synaptic remodeling, which is at the basis of their long-term physiologic effects. In this review, we will discuss the role of postsynaptic proteins in dopamine-glutamate signals integration, as well as the peculiar impact of different psychotropic drugs used in clinical practice on postsynaptic remodeling, thereby trying to point out the possible future molecular targets of “synapse-based” psychiatric therapeutic strategies.

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.

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.

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

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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.

Exploring the Ligand-Protein Networks in Traditional Chinese Medicine: Current Databases, Methods, and Applications

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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.

Parallel protein secondary structure prediction based on neural networks.

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Zhong, Wei; Altun, Gulsah; Tian, Xinmin; Harrison, Robert; Tai, Phang C; Pan, Yi

2004-01-01

Protein secondary structure prediction has a fundamental influence on today's bioinformatics research. In this work, binary and tertiary classifiers of protein secondary structure prediction are implemented on Denoeux belief neural network (DBNN) architecture. Hydrophobicity matrix, orthogonal matrix, BLOSUM62 and PSSM (position specific scoring matrix) are experimented separately as the encoding schemes for DBNN. The experimental results contribute to the design of new encoding schemes. New binary classifier for Helix versus not Helix ( approximately H) for DBNN produces prediction accuracy of 87% when PSSM is used for the input profile. The performance of DBNN binary classifier is comparable to other best prediction methods. The good test results for binary classifiers open a new approach for protein structure prediction with neural networks. Due to the time consuming task of training the neural networks, Pthread and OpenMP are employed to parallelize DBNN in the hyperthreading enabled Intel architecture. Speedup for 16 Pthreads is 4.9 and speedup for 16 OpenMP threads is 4 in the 4 processors shared memory architecture. Both speedup performance of OpenMP and Pthread is superior to that of other research. With the new parallel training algorithm, thousands of amino acids can be processed in reasonable amount of time. Our research also shows that hyperthreading technology for Intel architecture is efficient for parallel biological algorithms.

A conserved inter-domain communication mechanism regulates the ATPase activity of the AAA-protein Drg1

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Prattes, M.; Loibl, M.; Zisser, G.; Luschnig, D.; Kappel, L.; Rossler, I.; Grassegger, M.; Hromic, A.; Krieger, E.; Gruber, K.; Pertschy, B.; Bergler, H.

2017-01-01

AAA-ATPases fulfil essential roles in different cellular pathways and often act in form of hexameric complexes. Interaction with pathway-specific substrate and adaptor proteins recruits them to their targets and modulates their catalytic activity. This substrate dependent regulation of ATP

A Bipartite Network-based Method for Prediction of Long Non-coding RNA–protein Interactions

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Mengqu Ge

2016-02-01

Full Text Available As one large class of non-coding RNAs (ncRNAs, long ncRNAs (lncRNAs have gained considerable attention in recent years. Mutations and dysfunction of lncRNAs have been implicated in human disorders. Many lncRNAs exert their effects through interactions with the corresponding RNA-binding proteins. Several computational approaches have been developed, but only few are able to perform the prediction of these interactions from a network-based point of view. Here, we introduce a computational method named lncRNA–protein bipartite network inference (LPBNI. LPBNI aims to identify potential lncRNA–interacting proteins, by making full use of the known lncRNA–protein interactions. Leave-one-out cross validation (LOOCV test shows that LPBNI significantly outperforms other network-based methods, including random walk (RWR and protein-based collaborative filtering (ProCF. Furthermore, a case study was performed to demonstrate the performance of LPBNI using real data in predicting potential lncRNA–interacting proteins.

In-silico studies of neutral drift for functional protein interaction networks

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Ali, Md Zulfikar; Wingreen, Ned S.; Mukhopadhyay, Ranjan

We have developed a minimal physically-motivated model of protein-protein interaction networks. Our system consists of two classes of enzymes, activators (e.g. kinases) and deactivators (e.g. phosphatases), and the enzyme-mediated activation/deactivation rates are determined by sequence-dependent binding strengths between enzymes and their targets. The network is evolved by introducing random point mutations in the binding sequences where we assume that each new mutation is either fixed or entirely lost. We apply this model to studies of neutral drift in networks that yield oscillatory dynamics, where we start, for example, with a relatively simple network and allow it to evolve by adding nodes and connections while requiring that dynamics be conserved. Our studies demonstrate both the importance of employing a sequence-based evolutionary scheme and the relative rapidity (in evolutionary time) for the redistribution of function over new nodes via neutral drift. Surprisingly, in addition to this redistribution time we discovered another much slower timescale for network evolution, reflecting hidden order in sequence space that we interpret in terms of sparsely connected domains.

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

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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.

The proto-oncogene product p120CBL and the adaptor proteins CRKL and c-CRK link c-ABL, p190BCR/ABL and p210BCR/ABL to the phosphatidylinositol-3' kinase pathway.

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Sattler, M; Salgia, R; Okuda, K; Uemura, N; Durstin, M A; Pisick, E; Xu, G; Li, J L; Prasad, K V; Griffin, J D

1996-02-15

Chronic myelogenous leukemia (CML) and some acute lymphoblastic leukemias (ALL) are caused by the t(9;22) chromosome translocation, which produces the constitutively activated BCR/ABL tyrosine kinase. When introduced into factor dependent hematopoietic cell lines, BCR/ABL induces the tyrosine phosphorylation of many cellular proteins. One prominent BCR/ABL substrate is p120CBL, the cellular homolog of the v-Cbl oncoprotein. In an effort to understand the possible contribution of p120CBL to transformation by BCR/ABL, we looked for cellular proteins which associate with p120CBL in hematopoietic cell lines transformed by BCR/ABL. In addition to p210BCR/ABL and c-ABL, p120CBL coprecipitated with an 85 kDa phosphoprotein, which was identified as the p85 subunit of PI3K. Anti-p120CBL immunoprecipitates from BCR/ABL-transformed, but not from untransformed, cell lines contained PI3K lipid kinase activity. Interestingly, the adaptor proteins CRKL and c-CRK were also found in these complexes. In vitro binding studies indicated that the SH2 domains of CRKL and c-CRK bound directly to p120CBL, while the SH3 domains of c-CRK and CRKL bound to BCR/ABL and c-ABL. The N-terminal and the C-terminal SH2 and the SH3 domain of p85PI3K bound directly in vitro to p120CBL. The ABL-SH2, but not ABL-SH3, could also bind to p120CBL. These data suggest that BCR/ABL may induce the formation of multimeric complexes of signaling proteins which include p120CBL, PI3K, c-CRK or CRKL, c-ABL and BCR/ABL itself.

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

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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.

Protein secondary structure prediction using modular reciprocal bidirectional recurrent neural networks.

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Babaei, Sepideh; Geranmayeh, Amir; Seyyedsalehi, Seyyed Ali

2010-12-01

The supervised learning of recurrent neural networks well-suited for prediction of protein secondary structures from the underlying amino acids sequence is studied. Modular reciprocal recurrent neural networks (MRR-NN) are proposed to model the strong correlations between adjacent secondary structure elements. Besides, a multilayer bidirectional recurrent neural network (MBR-NN) is introduced to capture the long-range intramolecular interactions between amino acids in formation of the secondary structure. The final modular prediction system is devised based on the interactive integration of the MRR-NN and the MBR-NN structures to arbitrarily engage the neighboring effects of the secondary structure types concurrent with memorizing the sequential dependencies of amino acids along the protein chain. The advanced combined network augments the percentage accuracy (Q₃) to 79.36% and boosts the segment overlap (SOV) up to 70.09% when tested on the PSIPRED dataset in three-fold cross-validation. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

Adaptor protein SH2-B linking receptor-tyrosine kinase and Akt promotes adipocyte differentiation by regulating peroxisome proliferator-activated receptor gamma messenger ribonucleic acid levels.

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Yoshiga, Daigo; Sato, Naoichi; Torisu, Takehiro; Mori, Hiroyuki; Yoshida, Ryoko; Nakamura, Seiji; Takaesu, Giichi; Kobayashi, Takashi; Yoshimura, Akihiko

2007-05-01

Adipocyte differentiation is regulated by insulin and IGF-I, which transmit signals by activating their receptor tyrosine kinase. SH2-B is an adaptor protein containing pleckstrin homology and Src homology 2 (SH2) domains that have been implicated in insulin and IGF-I receptor signaling. In this study, we found a strong link between SH2-B levels and adipogenesis. The fat mass and expression of adipogenic genes including peroxisome proliferator-activated receptor gamma (PPARgamma) were reduced in white adipose tissue of SH2-B-/- mice. Reduced adipocyte differentiation of SH2-B-deficient mouse embryonic fibroblasts (MEFs) was observed in response to insulin and dexamethasone, whereas retroviral SH2-B overexpression enhanced differentiation of 3T3-L1 preadipocytes to adipocytes. SH2-B overexpression enhanced mRNA level of PPARgamma in 3T3-L1 cells, whereas PPARgamma levels were reduced in SH2-B-deficient MEFs in response to insulin. SH2-B-mediated up-regulation of PPARgamma mRNA was blocked by a phosphatidylinositol 3-kinase inhibitor, but not by a MAPK kinase inhibitor. Insulin-induced Akt activation and the phosphorylation of forkhead transcription factor (FKHR/Foxo1), a negative regulator of PPARgamma transcription, were up-regulated by SH2-B overexpression, but reduced in SH2-B-deficient MEFs. These data indicate that SH2-B is a key regulator of adipogenesis both in vivo and in vitro by regulating the insulin/IGF-I receptor-Akt-Foxo1-PPARgamma pathway.

A combinatorial approach to detect coevolved amino acid networks in protein families of variable divergence.

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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.

Vaccinia Virus Immunomodulator A46: A Lipid and Protein-Binding Scaffold for Sequestering Host TIR-Domain Proteins.

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Sofiya Fedosyuk

2016-12-01

Full Text Available Vaccinia virus interferes with early events of the activation pathway of the transcriptional factor NF-kB by binding to numerous host TIR-domain containing adaptor proteins. We have previously determined the X-ray structure of the A46 C-terminal domain; however, the structure and function of the A46 N-terminal domain and its relationship to the C-terminal domain have remained unclear. Here, we biophysically characterize residues 1-83 of the N-terminal domain of A46 and present the X-ray structure at 1.55 Å. Crystallographic phases were obtained by a recently developed ab initio method entitled ARCIMBOLDO_BORGES that employs tertiary structure libraries extracted from the Protein Data Bank; data analysis revealed an all β-sheet structure. This is the first such structure solved by this method which should be applicable to any protein composed entirely of β-sheets. The A46(1-83 structure itself is a β-sandwich containing a co-purified molecule of myristic acid inside a hydrophobic pocket and represents a previously unknown lipid-binding fold. Mass spectrometry analysis confirmed the presence of long-chain fatty acids in both N-terminal and full-length A46; mutation of the hydrophobic pocket reduced the lipid content. Using a combination of high resolution X-ray structures of the N- and C-terminal domains and SAXS analysis of full-length protein A46(1-240, we present here a structural model of A46 in a tetrameric assembly. Integrating affinity measurements and structural data, we propose how A46 simultaneously interferes with several TIR-domain containing proteins to inhibit NF-κB activation and postulate that A46 employs a bipartite binding arrangement to sequester the host immune adaptors TRAM and MyD88.

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

KAUST Repository

Cannistraci, Carlo; Alanis Lobato, Gregorio; Ravasi, Timothy

2013-01-01

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

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

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2012-09-01

phosphoinositide 3-kinase; PR: progesterone receptor; Rac1: ras-related C3 botulinum toxin substrate 1; RLU: relative luciferase units; RNAi: RNA...which Crk proteins are overexpressed.   11   The molecular events contributing to development of the basal subtype of breast cancer are still...the structural organization of Crk proteins. Despite a high degree of homology within the functional domains of CrkII and CrkL, the linker regions

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

Visualization of protein interaction networks: problems and solutions

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Agapito Giuseppe

2013-01-01

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

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

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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.

Knowledge base and neural network approach for protein secondary structure prediction.

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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.

Classification of Beta-lactamases and penicillin binding proteins using ligand-centric network models.

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Hakime Öztürk

Full Text Available β-lactamase mediated antibiotic resistance is an important health issue and the discovery of new β-lactam type antibiotics or β-lactamase inhibitors is an area of intense research. Today, there are about a thousand β-lactamases due to the evolutionary pressure exerted by these ligands. While β-lactamases hydrolyse the β-lactam ring of antibiotics, rendering them ineffective, Penicillin-Binding Proteins (PBPs, which share high structural similarity with β-lactamases, also confer antibiotic resistance to their host organism by acquiring mutations that allow them to continue their participation in cell wall biosynthesis. In this paper, we propose a novel approach to include ligand sharing information for classifying and clustering β-lactamases and PBPs in an effort to elucidate the ligand induced evolution of these β-lactam binding proteins. We first present a detailed summary of the β-lactamase and PBP families in the Protein Data Bank, as well as the compounds they bind to. Then, we build two different types of networks in which the proteins are represented as nodes, and two proteins are connected by an edge with a weight that depends on the number of shared identical or similar ligands. These models are analyzed under three different edge weight settings, namely unweighted, weighted, and normalized weighted. A detailed comparison of these six networks showed that the use of ligand sharing information to cluster proteins resulted in modules comprising proteins with not only sequence similarity but also functional similarity. Consideration of ligand similarity highlighted some interactions that were not detected in the identical ligand network. Analysing the β-lactamases and PBPs using ligand-centric network models enabled the identification of novel relationships, suggesting that these models can be used to examine other protein families to obtain information on their ligand induced evolutionary paths.

Identification of Top-ranked Proteins within a Directional Protein Interaction Network using the PageRank Algorithm: Applications in Humans and Plants.

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Li, Xiu-Qing; Xing, Tim; Du, Donglei

2016-01-01

Somatic mutation of signal transduction genes or key nodes of the cellular protein network can cause severe diseases in humans but can sometimes genetically improve plants, likely because growth is determinate in animals but indeterminate in plants. This article reviews protein networks; human protein ranking; the mitogen-activated protein kinase (MAPK) and insulin (phospho- inositide 3kinase [PI3K]/phosphatase and tensin homolog [PTEN]/protein kinase B [AKT]) signaling pathways; human diseases caused by somatic mutations to the PI3K/PTEN/ AKT pathway; use of the MAPK pathway in plant molecular breeding; and protein domain evolution. Casitas B-lineage lymphoma (CBL), PTEN, MAPK1 and PIK3CA are among PIK3CA the top-ranked proteins in directional rankings. Eight proteins (ACVR1, CDC42, RAC1, RAF1, RHOA, TGFBR1, TRAF2, and TRAF6) are ranked in the top 50 key players in both signal emission and signal reception and in interaction with many other proteins. Top-ranked proteins likely have major impacts on the network function. Such proteins are targets for drug discovery, because their mutations are implicated in various cancers and overgrowth syndromes. Appropriately managing food intake may help reduce the growth of tumors or malformation of tissues. The role of the protein kinase C/ fatty acid synthase pathway in fat deposition in PTEN/PI3K patients should be investigated. Both the MAPK and insulin signaling pathways exist in plants, and MAPK pathway engineering can improve plant tolerance to biotic and abiotic stresses such as salinity.

From protein-protein interactions to protein co-expression networks: a new perspective to evaluate large-scale proteomic data.

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Vella, Danila; Zoppis, Italo; Mauri, Giancarlo; Mauri, Pierluigi; Di Silvestre, Dario

2017-12-01

The reductionist approach of dissecting biological systems into their constituents has been successful in the first stage of the molecular biology to elucidate the chemical basis of several biological processes. This knowledge helped biologists to understand the complexity of the biological systems evidencing that most biological functions do not arise from individual molecules; thus, realizing that the emergent properties of the biological systems cannot be explained or be predicted by investigating individual molecules without taking into consideration their relations. Thanks to the improvement of the current -omics technologies and the increasing understanding of the molecular relationships, even more studies are evaluating the biological systems through approaches based on graph theory. Genomic and proteomic data are often combined with protein-protein interaction (PPI) networks whose structure is routinely analyzed by algorithms and tools to characterize hubs/bottlenecks and topological, functional, and disease modules. On the other hand, co-expression networks represent a complementary procedure that give the opportunity to evaluate at system level including organisms that lack information on PPIs. Based on these premises, we introduce the reader to the PPI and to the co-expression networks, including aspects of reconstruction and analysis. In particular, the new idea to evaluate large-scale proteomic data by means of co-expression networks will be discussed presenting some examples of application. Their use to infer biological knowledge will be shown, and a special attention will be devoted to the topological and module analysis.

Revisiting date and party hubs: novel approaches to role assignment in protein interaction networks.

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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.

DeepQA: improving the estimation of single protein model quality with deep belief networks.

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Cao, Renzhi; Bhattacharya, Debswapna; Hou, Jie; Cheng, Jianlin

2016-12-05

Protein quality assessment (QA) useful for ranking and selecting protein models has long been viewed as one of the major challenges for protein tertiary structure prediction. Especially, estimating the quality of a single protein model, which is important for selecting a few good models out of a large model pool consisting of mostly low-quality models, is still a largely unsolved problem. We introduce a novel single-model quality assessment method DeepQA based on deep belief network that utilizes a number of selected features describing the quality of a model from different perspectives, such as energy, physio-chemical characteristics, and structural information. The deep belief network is trained on several large datasets consisting of models from the Critical Assessment of Protein Structure Prediction (CASP) experiments, several publicly available datasets, and models generated by our in-house ab initio method. Our experiments demonstrate that deep belief network has better performance compared to Support Vector Machines and Neural Networks on the protein model quality assessment problem, and our method DeepQA achieves the state-of-the-art performance on CASP11 dataset. It also outperformed two well-established methods in selecting good outlier models from a large set of models of mostly low quality generated by ab initio modeling methods. DeepQA is a useful deep learning tool for protein single model quality assessment and protein structure prediction. The source code, executable, document and training/test datasets of DeepQA for Linux is freely available to non-commercial users at http://cactus.rnet.missouri.edu/DeepQA/ .

MUFOLD-SS: New deep inception-inside-inception networks for protein secondary structure prediction.

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Fang, Chao; Shang, Yi; Xu, Dong

2018-05-01

Protein secondary structure prediction can provide important information for protein 3D structure prediction and protein functions. Deep learning offers a new opportunity to significantly improve prediction accuracy. In this article, a new deep neural network architecture, named the Deep inception-inside-inception (Deep3I) network, is proposed for protein secondary structure prediction and implemented as a software tool MUFOLD-SS. The input to MUFOLD-SS is a carefully designed feature matrix corresponding to the primary amino acid sequence of a protein, which consists of a rich set of information derived from individual amino acid, as well as the context of the protein sequence. Specifically, the feature matrix is a composition of physio-chemical properties of amino acids, PSI-BLAST profile, and HHBlits profile. MUFOLD-SS is composed of a sequence of nested inception modules and maps the input matrix to either eight states or three states of secondary structures. The architecture of MUFOLD-SS enables effective processing of local and global interactions between amino acids in making accurate prediction. In extensive experiments on multiple datasets, MUFOLD-SS outperformed the best existing methods and other deep neural networks significantly. MUFold-SS can be downloaded from http://dslsrv8.cs.missouri.edu/~cf797/MUFoldSS/download.html. © 2018 Wiley Periodicals, Inc.

Sumoylation Promotes the Stability of the DNA Sensor cGAS and the Adaptor STING to Regulate the Kinetics of Response to DNA Virus.

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Hu, Ming-Ming; Yang, Qing; Xie, Xue-Qin; Liao, Chen-Yang; Lin, Heng; Liu, Tian-Tian; Yin, Lei; Shu, Hong-Bing

2016-09-20

During viral infection, sensing of cytosolic DNA by the cyclic GMP-AMP synthase (cGAS) activates the adaptor protein STING and triggers an antiviral response. Little is known about the mechanisms that determine the kinetics of activation and deactivation of the cGAS-STING pathway, ensuring effective but controlled innate antiviral responses. Here we found that the ubiquitin ligase Trim38 targets cGas for sumoylation in uninfected cells and during the early phase of viral infection. Sumoylation of cGas prevented its polyubiquitination and degradation. Trim38 also sumoylated Sting during the early phase of viral infection, promoting both Sting activation and protein stability. In the late phase of infection, cGas and Sting were desumoylated by Senp2 and subsequently degraded via proteasomal and chaperone-mediated autophagy pathways, respectively. Our findings reveal an essential role for Trim38 in the innate immune response to DNA virus and provide insight into the mechanisms that ensure optimal activation and deactivation of the cGAS-STING pathway. Copyright © 2016 Elsevier Inc. All rights reserved.

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.

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.

Prediction of the Ebola Virus Infection Related Human Genes Using Protein-Protein Interaction Network.

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Cao, HuanHuan; Zhang, YuHang; Zhao, Jia; Zhu, Liucun; Wang, Yi; Li, JiaRui; Feng, Yuan-Ming; Zhang, Ning

2017-01-01

Ebola hemorrhagic fever (EHF) is caused by Ebola virus (EBOV). It is reported that human could be infected by EBOV with a high fatality rate. However, association factors between EBOV and host still tend to be ambiguous. According to the "guilt by association" (GBA) principle, proteins interacting with each other are very likely to function similarly or the same. Based on this assumption, we tried to obtain EBOV infection-related human genes in a protein-protein interaction network using Dijkstra algorithm. We hope it could contribute to the discovery of novel effective treatments. Finally, 15 genes were selected as potential EBOV infection-related human genes. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

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.

A mathematical model for generating bipartite graphs and its application to protein networks

Science.gov (United States)

Nacher, J. C.; Ochiai, T.; Hayashida, M.; Akutsu, T.

2009-12-01

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.

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.

The Fanconi anemia gene product FANCF is a flexible adaptor protein.

NARCIS (Netherlands)

Leveille, F.; Blom, E.; Medhurst, A.L. dr.; Bier, P; Laghmani, elH; Johnson, M.; Rooimans, M.A.; Sobeck, A; Waisfisz, Q.; Arwert, F.; Patel, KJ; Hoatlin, M.E.; Joenje, H.; Winter, de J.P.

2004-01-01

The Fanconi anemia (FA) protein FANCF is an essential component of a nuclear core complex that protects the genome against chromosomal instability, but the specific function of FANCF is still poorly understood. Based upon the homology between human and Xenopus laevis FANCF, we carried out an

Fascin- and α-Actinin-Bundled Networks Contain Intrinsic Structural Features that Drive Protein Sorting.

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Winkelman, Jonathan D; Suarez, Cristian; Hocky, Glen M; Harker, Alyssa J; Morganthaler, Alisha N; Christensen, Jenna R; Voth, Gregory A; Bartles, James R; Kovar, David R

2016-10-24

Cells assemble and maintain functionally distinct actin cytoskeleton networks with various actin filament organizations and dynamics through the coordinated action of different sets of actin-binding proteins. The biochemical and functional properties of diverse actin-binding proteins, both alone and in combination, have been increasingly well studied. Conversely, how different sets of actin-binding proteins properly sort to distinct actin filament networks in the first place is not nearly as well understood. Actin-binding protein sorting is critical for the self-organization of diverse dynamic actin cytoskeleton networks within a common cytoplasm. Using in vitro reconstitution techniques including biomimetic assays and single-molecule multi-color total internal reflection fluorescence microscopy, we discovered that sorting of the prominent actin-bundling proteins fascin and α-actinin to distinct networks is an intrinsic behavior, free of complicated cellular signaling cascades. When mixed, fascin and α-actinin mutually exclude each other by promoting their own recruitment and inhibiting recruitment of the other, resulting in the formation of distinct fascin- or α-actinin-bundled domains. Subdiffraction-resolution light microscopy and negative-staining electron microscopy revealed that fascin domains are densely packed, whereas α-actinin domains consist of widely spaced parallel actin filaments. Importantly, other actin-binding proteins such as fimbrin and espin show high specificity between these two bundle types within the same reaction. Here we directly observe that fascin and α-actinin intrinsically segregate to discrete bundled domains that are specifically recognized by other actin-binding proteins. Copyright © 2016 Elsevier Ltd. All rights reserved.

Multisite tyrosine phosphorylation of the N-terminus of Mint1/X11α by Src kinase regulates the trafficking of amyloid precursor protein.

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Dunning, Christopher J R; Black, Hannah L; Andrews, Katie L; Davenport, Elizabeth C; Conboy, Michael; Chawla, Sangeeta; Dowle, Adam A; Ashford, David; Thomas, Jerry R; Evans, Gareth J O

2016-05-01

Mint/X11 is one of the four neuronal trafficking adaptors that interact with amyloid precursor protein (APP) and are linked with its cleavage to generate β-amyloid peptide, a key player in the pathology of Alzheimer's disease. How APP switches between adaptors at different stages of the secretory pathway is poorly understood. Here, we show that tyrosine phosphorylation of Mint1 regulates the destination of APP. A canonical SH2-binding motif ((202) YEEI) was identified in the N-terminus of Mint1 that is phosphorylated on tyrosine by C-Src and recruits the active kinase for sequential phosphorylation of further tyrosines (Y191 and Y187). A single Y202F mutation in the Mint1 N-terminus inhibits C-Src binding and tyrosine phosphorylation. Previous studies observed that co-expression of wild-type Mint1 and APP causes accumulation of APP in the trans-Golgi. Unphosphorylatable Mint1 (Y202F) or pharmacological inhibition of Src reduced the accumulation of APP in the trans-Golgi of heterologous cells. A similar result was observed in cultured rat hippocampal neurons where Mint1(Y202F) permitted the trafficking of APP to more distal neurites than the wild-type protein. These data underline the importance of the tyrosine phosphorylation of Mint1 as a critical switch for determining the destination of APP. The regulation of amyloid precursor protein (APP) trafficking is poorly understood. We have discovered that the APP adapter, Mint1, is phosphorylated by C-Src kinase. Mint1 causes APP accumulation in the trans-Golgi network, whereas inhibition of Src or mutation of Mint1-Y202 permits APP recycling. The phosphorylation status of Mint1 could impact on the pathological trafficking of APP in Alzheimer's disease. © 2016 The Authors. Journal of Neurochemistry published by John Wiley & Sons Ltd on behalf of International Society for Neurochemistry.

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

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

The origin of polynucleotide-directed protein synthesis

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Orgel, Leslie E.

1989-01-01

If protein synthesis evolved in an RNA world it was probably preceded by simpler processes by means of which interaction with amino acids conferred selective advantage on replicating RNA molecules. It is suggested that at first the simple attachment of amino acids to the 2'(3') termini of RNA templates favored initiation of replication at the end of the template rather than at internal positions. The second stage in the evolution of protein synthesis would probably have been the association of pairs of charged RNA adaptors in such a way as to favor noncoded formation of peptides. Only after this process had become efficient could coded synthesis have begun.

Evaluation of clustering algorithms for protein-protein interaction networks

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van Helden Jacques

2006-11-01

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

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.

Improving Protein Fold Recognition by Deep Learning Networks

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Jo, Taeho; Hou, Jie; Eickholt, Jesse; Cheng, Jianlin

2015-12-01

For accurate recognition of protein folds, a deep learning network method (DN-Fold) was developed to predict if a given query-template protein pair belongs to the same structural fold. The input used stemmed from the protein sequence and structural features extracted from the protein pair. We evaluated the performance of DN-Fold along with 18 different methods on Lindahl’s benchmark dataset and on a large benchmark set extracted from SCOP 1.75 consisting of about one million protein pairs, at three different levels of fold recognition (i.e., protein family, superfamily, and fold) depending on the evolutionary distance between protein sequences. The correct recognition rate of ensembled DN-Fold for Top 1 predictions is 84.5%, 61.5%, and 33.6% and for Top 5 is 91.2%, 76.5%, and 60.7% at family, superfamily, and fold levels, respectively. We also evaluated the performance of single DN-Fold (DN-FoldS), which showed the comparable results at the level of family and superfamily, compared to ensemble DN-Fold. Finally, we extended the binary classification problem of fold recognition to real-value regression task, which also show a promising performance. DN-Fold is freely available through a web server at http://iris.rnet.missouri.edu/dnfold.

Improving Protein Fold Recognition by Deep Learning Networks.

Science.gov (United States)

Jo, Taeho; Hou, Jie; Eickholt, Jesse; Cheng, Jianlin

2015-12-04

For accurate recognition of protein folds, a deep learning network method (DN-Fold) was developed to predict if a given query-template protein pair belongs to the same structural fold. The input used stemmed from the protein sequence and structural features extracted from the protein pair. We evaluated the performance of DN-Fold along with 18 different methods on Lindahl's benchmark dataset and on a large benchmark set extracted from SCOP 1.75 consisting of about one million protein pairs, at three different levels of fold recognition (i.e., protein family, superfamily, and fold) depending on the evolutionary distance between protein sequences. The correct recognition rate of ensembled DN-Fold for Top 1 predictions is 84.5%, 61.5%, and 33.6% and for Top 5 is 91.2%, 76.5%, and 60.7% at family, superfamily, and fold levels, respectively. We also evaluated the performance of single DN-Fold (DN-FoldS), which showed the comparable results at the level of family and superfamily, compared to ensemble DN-Fold. Finally, we extended the binary classification problem of fold recognition to real-value regression task, which also show a promising performance. DN-Fold is freely available through a web server at http://iris.rnet.missouri.edu/dnfold.

Efficient and accurate Greedy Search Methods for mining functional modules in protein interaction networks.

Science.gov (United States)

He, Jieyue; Li, Chaojun; Ye, Baoliu; Zhong, Wei

2012-06-25

Most computational algorithms mainly focus on detecting highly connected subgraphs in PPI networks as protein complexes but ignore their inherent organization. Furthermore, many of these algorithms are computationally expensive. However, recent analysis indicates that experimentally detected protein complexes generally contain Core/attachment structures. In this paper, a Greedy Search Method based on Core-Attachment structure (GSM-CA) is proposed. The GSM-CA method detects densely connected regions in large protein-protein interaction networks based on the edge weight and two criteria for determining core nodes and attachment nodes. The GSM-CA method improves the prediction accuracy compared to other similar module detection approaches, however it is computationally expensive. Many module detection approaches are based on the traditional hierarchical methods, which is also computationally inefficient because the hierarchical tree structure produced by these approaches cannot provide adequate information to identify whether a network belongs to a module structure or not. In order to speed up the computational process, the Greedy Search Method based on Fast Clustering (GSM-FC) is proposed in this work. The edge weight based GSM-FC method uses a greedy procedure to traverse all edges just once to separate the network into the suitable set of modules. The proposed methods are applied to the protein interaction network of S. cerevisiae. Experimental results indicate that many significant functional modules are detected, most of which match the known complexes. Results also demonstrate that the GSM-FC algorithm is faster and more accurate as compared to other competing algorithms. Based on the new edge weight definition, the proposed algorithm takes advantages of the greedy search procedure to separate the network into the suitable set of modules. Experimental analysis shows that the identified modules are statistically significant. The algorithm can reduce the

Usher syndrome protein network functions in the retina and their relation to other retinal ciliopathies.

Science.gov (United States)

Sorusch, Nasrin; Wunderlich, Kirsten; Bauss, Katharina; Nagel-Wolfrum, Kerstin; Wolfrum, Uwe

2014-01-01

The human Usher syndrome (USH) is the most frequent cause of combined hereditary deaf-blindness. USH is genetically and clinically heterogeneous: 15 chromosomal loci assigned to 3 clinical types, USH1-3. All USH1 and 2 proteins are organized into protein networks by the scaffold proteins harmonin (USH1C), whirlin (USH2D) and SANS (USH1G). This has contributed essentially to our current understanding of the USH protein function in the eye and the ear and explains why defects in proteins of different families cause very similar phenotypes. Ongoing in depth analyses of USH protein networks in the eye indicated cytoskeletal functions as well as roles in molecular transport processes and ciliary cargo delivery in photoreceptor cells. The analysis of USH protein networks revealed molecular links of USH to other ciliopathies, including non-syndromic inner ear defects and isolated retinal dystrophies but also to kidney diseases and syndromes like the Bardet-Biedl syndrome. These findings provide emerging evidence that USH is a ciliopathy molecularly related to other ciliopathies, which opens an avenue for common therapy strategies to treat these diseases.

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

Science.gov (United States)

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

2018-03-19

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

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.

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.

Integrative Identification of Arabidopsis Mitochondrial Proteome and Its Function Exploitation through Protein Interaction Network

Science.gov (United States)

Cui, Jian; Liu, Jinghua; Li, Yuhua; Shi, Tieliu

2011-01-01

Mitochondria are major players on the production of energy, and host several key reactions involved in basic metabolism and biosynthesis of essential molecules. Currently, the majority of nucleus-encoded mitochondrial proteins are unknown even for model plant Arabidopsis. We reported a computational framework for predicting Arabidopsis mitochondrial proteins based on a probabilistic model, called Naive Bayesian Network, which integrates disparate genomic data generated from eight bioinformatics tools, multiple orthologous mappings, protein domain properties and co-expression patterns using 1,027 microarray profiles. Through this approach, we predicted 2,311 candidate mitochondrial proteins with 84.67% accuracy and 2.53% FPR performances. Together with those experimental confirmed proteins, 2,585 mitochondria proteins (named CoreMitoP) were identified, we explored those proteins with unknown functions based on protein-protein interaction network (PIN) and annotated novel functions for 26.65% CoreMitoP proteins. Moreover, we found newly predicted mitochondrial proteins embedded in particular subnetworks of the PIN, mainly functioning in response to diverse environmental stresses, like salt, draught, cold, and wound etc. Candidate mitochondrial proteins involved in those physiological acitivites provide useful targets for further investigation. Assigned functions also provide comprehensive information for Arabidopsis mitochondrial proteome. PMID:21297957

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.

The ability to store energy in pea protein gels is set by network dimensions smaller than 50 nm

NARCIS (Netherlands)

Munialo, C.D.; Linden, van der E.; Jongh, de H.H.J.

2014-01-01

The objective of this study was to identify which length scales set the ability to elastically store energy in pea protein network structures. Various network structures were obtained frompea proteins by varying the pH and salt conditions during gel formation. The coarseness of the network structure

Classification of protein-protein interaction full-text documents using text and citation network features.

Science.gov (United States)

Kolchinsky, Artemy; Abi-Haidar, Alaa; Kaur, Jasleen; Hamed, Ahmed Abdeen; Rocha, Luis M

2010-01-01

We participated (as Team 9) in the Article Classification Task of the Biocreative II.5 Challenge: binary classification of full-text documents relevant for protein-protein interaction. We used two distinct classifiers for the online and offline challenges: 1) the lightweight Variable Trigonometric Threshold (VTT) linear classifier we successfully introduced in BioCreative 2 for binary classification of abstracts and 2) a novel Naive Bayes classifier using features from the citation network of the relevant literature. We supplemented the supplied training data with full-text documents from the MIPS database. The lightweight VTT classifier was very competitive in this new full-text scenario: it was a top-performing submission in this task, taking into account the rank product of the Area Under the interpolated precision and recall Curve, Accuracy, Balanced F-Score, and Matthew's Correlation Coefficient performance measures. The novel citation network classifier for the biomedical text mining domain, while not a top performing classifier in the challenge, performed above the central tendency of all submissions, and therefore indicates a promising new avenue to investigate further in bibliome informatics.

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.

Evidence for the interaction of the regulatory protein Ki-1/57 with p53 and its interacting proteins

International Nuclear Information System (INIS)

Nery, Flavia C.; Rui, Edmilson; Kuniyoshi, Tais M.; Kobarg, Joerg

2006-01-01

Ki-1/57 is a cytoplasmic and nuclear phospho-protein of 57 kDa and interacts with the adaptor protein RACK1, the transcription factor MEF2C, and the chromatin remodeling factor CHD3, suggesting that it might be involved in the regulation of transcription. Here, we describe yeast two-hybrid studies that identified a total of 11 proteins interacting with Ki-1/57, all of which interact or are functionally associated with p53 or other members of the p53 family of proteins. We further found that Ki-1/57 is able to interact with p53 itself in the yeast two-hybrid system when the interaction was tested directly. This interaction could be confirmed by pull down assays with purified proteins in vitro and by reciprocal co-immunoprecipitation assays from the human Hodgkin analogous lymphoma cell line L540. Furthermore, we found that the phosphorylation of p53 by PKC abolishes its interaction with Ki-1/57 in vitro

PRED-CLASS: cascading neural networks for generalized protein classification and genome-wide applications

OpenAIRE

Pasquier, Claude; Promponas, Vasilis; Hamodrakas, Stavros

2009-01-01

International audience; A cascading system of hierarchical, artificial neural networks (named PRED-CLASS) is presented for the generalized classification of proteins into four distinct classes-transmembrane, fibrous, globular, and mixed-from information solely encoded in their amino acid sequences. The architecture of the individual component networks is kept very simple, reducing the number of free parameters (network synaptic weights) for faster training, improved generalization, and the av...

Protein Kinase C Epsilon and Genetic Networks in Osteosarcoma Metastasis

Energy Technology Data Exchange (ETDEWEB)

Goudarzi, Atta, E-mail: atta.goudarzi@utoronto.ca [Department of Molecular Genetics, University of Toronto, 1 King’s College Circle, Toronto, ON M5S 1A8 (Canada); Samuel Lunenfeld Research Institute, Mount Sinai Hospital, 600 University Ave., Toronto, ON M5G 1X5 (Canada); Gokgoz, Nalan; Gill, Mona; Pinnaduwage, Dushanthi [Samuel Lunenfeld Research Institute, Mount Sinai Hospital, 600 University Ave., Toronto, ON M5G 1X5 (Canada); Merico, Daniele [The Centre for Applied Genomics, The Hospital for Sick Children, MaRS Centre-East Tower, 101 College Street Rm.14-701, Toronto, ON M5G 1L7 (Canada); Wunder, Jay S. [Samuel Lunenfeld Research Institute, Mount Sinai Hospital, 600 University Ave., Toronto, ON M5G 1X5 (Canada); Andrulis, Irene L. [Department of Molecular Genetics, University of Toronto, 1 King’s College Circle, Toronto, ON M5S 1A8 (Canada); Samuel Lunenfeld Research Institute, Mount Sinai Hospital, 600 University Ave., Toronto, ON M5G 1X5 (Canada)

2013-04-08

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.

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

Analysis of core-periphery organization in protein contact networks reveals groups of structurally and functionally critical residues.

Science.gov (United States)

Isaac, Arnold Emerson; Sinha, Sitabhra

2015-10-01

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 native states of 66 proteins (belonging to different families) in terms of their core-periphery organization. The resulting hierarchical classification of the amino acid constituents of a protein arranges the residues into successive layers - having higher core order - with increasing connection density, ranging from a sparsely linked periphery to a densely intra-connected core (distinct from the earlier concept of protein core defined in terms of the three-dimensional geometry of the native state, which has least solvent accessibility). Our results show that residues in the inner cores are more conserved than those at the periphery. Underlining the functional importance of the network core, we see that the receptor sites for known ligand molecules of most proteins occur in the innermost core. Furthermore, the association of residues with structural pockets and cavities in binding or active sites increases with the core order. 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. A publicly available Web resource for performing core-periphery analysis of any protein whose native state is known has been made available by us at http://www.imsc.res.in/ ~sitabhra/proteinKcore/index.html.

Duplicate retention in signalling proteins and constraints from network dynamics.

Science.gov (United States)

Soyer, O S; Creevey, C J

2010-11-01

Duplications are a major driving force behind evolution. Most duplicates are believed to fix through genetic drift, but it is not clear whether this process affects all duplications equally or whether there are certain gene families that are expected to show neutral expansions under certain circumstances. Here, we analyse the neutrality of duplications in different functional classes of signalling proteins based on their effects on response dynamics. We find that duplications involving intermediary proteins in a signalling network are neutral more often than those involving receptors. Although the fraction of neutral duplications in all functional classes increase with decreasing population size and selective pressure on dynamics, this effect is most pronounced for receptors, indicating a possible expansion of receptors in species with small population size. In line with such an expectation, we found a statistically significant increase in the number of receptors as a fraction of genome size in eukaryotes compared with prokaryotes. Although not confirmative, these results indicate that neutral processes can be a significant factor in shaping signalling networks and affect proteins from different functional classes differently. © 2010 The Authors. Journal Compilation © 2010 European Society For Evolutionary Biology.

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

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.

Binding of the cSH3 domain of Grb2 adaptor to two distinct RXXK motifs within Gab1 docker employs differential mechanisms.

Science.gov (United States)

McDonald, Caleb B; Seldeen, Kenneth L; Deegan, Brian J; Bhat, Vikas; Farooq, Amjad

2011-01-01

A ubiquitous component of cellular signaling machinery, Gab1 docker plays a pivotal role in routing extracellular information in the form of growth factors and cytokines to downstream targets such as transcription factors within the nucleus. Here, using isothermal titration calorimetry (ITC) in combination with macromolecular modeling (MM), we show that although Gab1 contains four distinct RXXK motifs, designated G1, G2, G3, and G4, only G1 and G2 motifs bind to the cSH3 domain of Grb2 adaptor and do so with distinct mechanisms. Thus, while the G1 motif strictly requires the PPRPPKP consensus sequence for high-affinity binding to the cSH3 domain, the G2 motif displays preference for the PXVXRXLKPXR consensus. Such sequential differences in the binding of G1 and G2 motifs arise from their ability to adopt distinct polyproline type II (PPII)- and 3(10) -helical conformations upon binding to the cSH3 domain, respectively. Collectively, our study provides detailed biophysical insights into a key protein-protein interaction involved in a diverse array of signaling cascades central to health and disease. Copyright © 2010 John Wiley & Sons, Ltd.

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/....