WorldWideScience

Sample records for adaptor proteins networks

  1. The fifth adaptor protein complex.

    OpenAIRE

    Jennifer Hirst; Barlow, Lael D.; Gabriel Casey Francisco; Sahlender, Daniela A.; Seaman, Matthew N.J.; Dacks, Joel B.; Robinson, Margaret S.

    2011-01-01

    Adaptor protein (AP) complexes sort cargo into vesicles for transport from one membrane compartment of the cell to another. Four distinct AP complexes have been identified, which are present in most eukaryotes. We report the existence of a fifth AP complex, AP-5. Tagged AP-5 localises to a late endosomal compartment in HeLa cells. AP-5 does not associate with clathrin and is insensitive to brefeldin A. Knocking down AP-5 subunits interferes with the trafficking of the cation-independent manno...

  2. The Fifth Adaptor Protein Complex

    OpenAIRE

    Hirst, Jennifer; D. Barlow, Lael; Francisco, Gabriel Casey; Sahlender, Daniela A.; Seaman, Matthew N.J.; Dacks, Joel B.; Robinson, Margaret S.

    2011-01-01

    Adaptor protein (AP) complexes sort cargo into vesicles for transport from one membrane compartment of the cell to another. Four distinct AP complexes have been identified, which are present in most eukaryotes. We report the existence of a fifth AP complex, AP-5. Tagged AP-5 localises to a late endosomal compartment in HeLa cells. AP-5 does not associate with clathrin and is insensitive to brefeldin A. Knocking down AP-5 subunits interferes with the trafficking of the cation-independent manno...

  3. The fifth adaptor protein complex.

    Directory of Open Access Journals (Sweden)

    Jennifer Hirst

    2011-10-01

    Full Text Available Adaptor protein (AP complexes sort cargo into vesicles for transport from one membrane compartment of the cell to another. Four distinct AP complexes have been identified, which are present in most eukaryotes. We report the existence of a fifth AP complex, AP-5. Tagged AP-5 localises to a late endosomal compartment in HeLa cells. AP-5 does not associate with clathrin and is insensitive to brefeldin A. Knocking down AP-5 subunits interferes with the trafficking of the cation-independent mannose 6-phosphate receptor and causes the cell to form swollen endosomal structures with emanating tubules. AP-5 subunits can be found in all five eukaryotic supergroups, but they have been co-ordinately lost in many organisms. Concatenated phylogenetic analysis provides robust resolution, for the first time, into the evolutionary order of emergence of the adaptor subunit families, showing AP-3 as the basal complex, followed by AP-5, AP-4, and AP-1 and AP-2. Thus, AP-5 is an evolutionarily ancient complex, which is involved in endosomal sorting, and which has links with hereditary spastic paraplegia.

  4. Adaptor protein complexes and intracellular transport

    OpenAIRE

    2014-01-01

    The AP (adaptor protein) complexes are heterotetrameric protein complexes that mediate intracellular membrane trafficking along endocytic and secretory transport pathways. There are five different AP complexes: AP-1, AP-2 and AP-3 are clathrin-associated complexes; whereas AP-4 and AP-5 are not. These five AP complexes localize to different intracellular compartments and mediate membrane trafficking in distinct pathways. They recognize and concentrate cargo proteins into vesicular carriers th...

  5. Yeast Golgi-localized, γ-Ear–containing, ADP-Ribosylation Factor-binding Proteins Are but Adaptor Protein-1 Is Not Required for Cell-free Transport of Membrane Proteins from the Trans-Golgi Network to the Prevacuolar Compartment

    OpenAIRE

    Abazeed, Mohamed E.; Fuller, Robert S.

    2008-01-01

    Golgi-localized, γ-Ear–containing, ADP-ribosylation factor-binding proteins (GGAs) and adaptor protein-1 (AP-1) mediate clathrin-dependent trafficking of transmembrane proteins between the trans-Golgi network (TGN) and endosomes. In yeast, the vacuolar sorting receptor Vps10p follows a direct pathway from the TGN to the late endosome/prevacuolar compartment (PVC), whereas, the processing protease Kex2p partitions between the direct pathway and an indirect pathway through the early endosome. T...

  6. FDDI network test adaptor error injection circuit

    Science.gov (United States)

    Eckenrode, Thomas (Inventor); Stauffer, David R. (Inventor); Stempski, Rebecca (Inventor)

    1994-01-01

    An apparatus for injecting errors into a FDDI token ring network is disclosed. The error injection scheme operates by fooling a FORMAC into thinking it sent a real frame of data. This is done by using two RAM buffers. The RAM buffer normally accessed by the RBC/DPC becomes a SHADOW RAM during error injection operation. A dummy frame is loaded into the shadow RAM in order to fool the FORMAC. This data is just like the data that would be used if sending a normal frame, with the restriction that it must be shorter than the error injection data. The other buffer, the error injection RAM, contains the error injection frame. The error injection data is sent out to the media by switching a multiplexor. When the FORMAC is done transmitting the data, the multiplexor is switched back to the normal mode. Thus, the FORMAC is unaware of what happened and the token ring remains operational.

  7. XB130: A novel adaptor protein in cancer signal transduction

    Science.gov (United States)

    ZHANG, RUIYAO; ZHANG, JINGYAO; WU, QIFEI; MENG, FANDI; LIU, CHANG

    2016-01-01

    Adaptor proteins are functional proteins that contain two or more protein-binding modules to link signaling proteins together, which affect cell growth and shape and have no enzymatic activity. The actin filament-associated protein (AFAP) family is an important member of the adaptor proteins, including AFAP1, AFAP1L1 and AFAP1L2/XB130. AFAP1 and AFAP1L1 share certain common characteristics and function as an actin-binding protein and a cSrc-activating protein. XB130 exhibits certain unique features in structure and function. The mRNA of XB130 is expressed in human spleen, thyroid, kidney, brain, lung, pancreas, liver, colon and stomach, and the most prominent disease associated with XB130 is cancer. XB130 has a controversial effect on cancer. Studies have shown that XB130 can promote cancer progression and downregulation of XB130-reduced growth of tumors derived from certain cell lines. A higher mRNA level of XB130 was shown to be associated with a better survival in non-small cell lung cancer. Previous studies have shown that XB130 can regulate cell growth, migration and invasion and possibly has the effect through the cAMP-cSrc-phosphoinositide 3-kinase/Akt pathway. Except for cancer, XB130 is also associated with other pathological or physiological procedures, such as airway repair and regeneration. PMID:26998266

  8. Negative regulation of lymphocyte activation by the adaptor protein LAX.

    Science.gov (United States)

    Zhu, Minghua; Granillo, Olivia; Wen, Renren; Yang, Kaiyong; Dai, Xuezhi; Wang, Demin; Zhang, Weiguo

    2005-05-01

    The membrane-associated adaptor protein LAX is a linker for activation of T cells (LAT)-like molecule that is expressed in lymphoid tissues. Upon stimulation of T or B cells, it is phosphorylated and interacts with Grb2 and the p85 subunit of PI3K. LAX, however, is not capable of replacing LAT in the TCR signaling pathway. In this study we report that upon T or B cell activation, the LAX protein was up-regulated dramatically. Although disruption of the LAX gene by homologous recombination had no major impact on lymphocyte development, it caused a significant reduction in CD23 expression on mature B cells. Interestingly, naive LAX(-/-) mice had spontaneous germinal center formation. Compared with normal T and B cells, LAX(-/-) T and B cells were hyperresponsive and had enhanced calcium flux, protein tyrosine phosphorylation, MAPK and Akt activation, and cell survival upon engagement of the T or B AgRs. Our data demonstrate that LAX functions as a negative regulator in lymphocyte signaling.

  9. Structure of the periplasmic adaptor protein from a major facilitator superfamily (MFS) multidrug efflux pump.

    Science.gov (United States)

    Hinchliffe, Philip; Greene, Nicholas P; Paterson, Neil G; Crow, Allister; Hughes, Colin; Koronakis, Vassilis

    2014-08-25

    Periplasmic adaptor proteins are key components of bacterial tripartite efflux pumps. The 2.85 Å resolution structure of an MFS (major facilitator superfamily) pump adaptor, Aquifex aeolicus EmrA, shows linearly arranged α-helical coiled-coil, lipoyl, and β-barrel domains, but lacks the fourth membrane-proximal domain shown in other pumps to interact with the inner membrane transporter. The adaptor α-hairpin, which binds outer membrane TolC, is exceptionally long at 127 Å, and the β-barrel contains a conserved disordered loop. The structure extends the view of adaptors as flexible, modular components that mediate diverse pump assembly, and suggests that in MFS tripartite pumps a hexamer of adaptors could provide a periplasmic seal. PMID:24996185

  10. Structure of the periplasmic adaptor protein from a major facilitator superfamily (MFS) multidrug efflux pump

    OpenAIRE

    Hinchliffe, Philip; Greene, Nicholas P.; Paterson, Neil G.; Crow, Allister; Hughes, Colin; Koronakis, Vassilis

    2014-01-01

    Periplasmic adaptor proteins are key components of bacterial tripartite efflux pumps. The 2.85 Å resolution structure of an MFS (major facilitator superfamily) pump adaptor, Aquifex aeolicus EmrA, shows linearly arranged α-helical coiled-coil, lipoyl, and β-barrel domains, but lacks the fourth membrane-proximal domain shown in other pumps to interact with the inner membrane transporter. The adaptor α-hairpin, which binds outer membrane TolC, is exceptionally long at 127 Å, and the β-barrel co...

  11. Autoinhibition of Mint1 adaptor protein regulates amyloid precursor protein binding and processing

    OpenAIRE

    Matos, Maria F.; Xu, Yibin; Dulubova, Irina; Otwinowski, Zbyszek; Richardson, John M.; Tomchick, Diana R.; Rizo, Josep; Ho, Angela

    2012-01-01

    Mint adaptor proteins bind to the amyloid precursor protein (APP) and regulate APP processing associated with Alzheimer’s disease; however, the molecular mechanisms underlying Mint regulation in APP binding and processing remain unclear. Biochemical, biophysical, and cellular experiments now show that the Mint1 phosphotyrosine binding (PTB) domain that binds to APP is intramolecularly inhibited by the adjacent C-terminal linker region. The crystal structure of a C-terminally extended Mint1 PT...

  12. The Emerging and Diverse Roles of Src-Like Adaptor Proteins in Health and Disease

    Directory of Open Access Journals (Sweden)

    Nikolett Marton

    2015-01-01

    Full Text Available Although Src-like adaptor proteins (SLAP-1 and SLAP-2 were mainly studied in lymphocytes, where they act as negative regulators and provide fine control of receptor signaling, recently, several other functions of these proteins were discovered. In addition to the well-characterized immunoregulatory functions, SLAP proteins appear to have an essential role in the pathogenesis of type I hypersensitivity, osteoporosis, and numerous malignant diseases. Both adaptor proteins are expressed in a wide variety of tissues, where they have mostly inhibitory effects on multiple intracellular signaling pathways. In this review, we summarize the diverse effects of SLAP proteins.

  13. Molecular protein adaptor with genetically encoded interaction sites guiding the hierarchical assembly of plasmonically active nanoparticle architectures

    Science.gov (United States)

    Schreiber, Andreas; Huber, Matthias C.; Cölfen, Helmut; Schiller, Stefan M.

    2015-03-01

    The control over the defined assembly of nano-objects with nm-precision is important to create systems and materials with enhanced properties, for example, metamaterials. In nature, the precise assembly of inorganic nano-objects with unique features, for example, magnetosomes, is accomplished by efficient and reliable recognition schemes involving protein effectors. Here we present a molecular approach using protein-based ‘adaptors/connectors’ with genetically encoded interaction sites to guide the assembly and functionality of different plasmonically active gold nanoparticle architectures (AuNP). The interaction of the defined geometricaly shaped protein adaptors with the AuNP induces the self-assembly of nanoarchitectures ranging from AuNP encapsulation to one-dimensional chain-like structures, complex networks and stars. Synthetic biology and bionanotechnology are applied to co-translationally encode unnatural amino acids as additional site-specific modification sites to generate functionalized biohybrid nanoarchitectures. This protein adaptor-based nano-object assembly approach might be expanded to other inorganic nano-objects creating biohybrid materials with unique electronic, photonic, plasmonic and magnetic properties.

  14. Distinct adaptor proteins assist exit of Kre2-family proteins from the yeast ER

    Directory of Open Access Journals (Sweden)

    Yoichi Noda

    2014-07-01

    Full Text Available The Svp26 protein of S. cerevisiae is an ER- and Golgi-localized integral membrane protein with 4 potential membrane-spanning domains. It functions as an adaptor protein that facilitates the ER exit of Ktr3, a mannosyltransferase required for biosynthesis of O-linked oligosaccharides, and the ER exit of Mnn2 and Mnn5, mannosyltransferases, which participate in the biosynthesis of N-linked oligosaccharides. Ktr3 belongs to the Kre2 family, which consists of 9 members of type-II membrane proteins sharing sequence similarities. In this report, we examined all Kre2 family members and found that the Golgi localizations of two others, Kre2 and Ktr1, were dependent on Svp26 by immunofluorescence microscopy and cell fractionations in sucrose density gradients. We show that Svp26 functions in facilitating the ER exit of Kre2 and Ktr1 by an in vitro COPII budding assay. Golgi localization of Ktr4 was not dependent on Svp26. Screening null mutants of the genes encoding abundant COPII membrane proteins for those showing mislocalization of Ktr4 in the ER revealed that Erv41 and Erv46 are required for the correct Golgi localization of Ktr4. We provide biochemical evidence that the Erv41-Erv46 complex functions as an adaptor protein for ER exit of Ktr4. This is the first demonstration of the molecular function of this evolutionally conserved protein complex. The domain switching experiments show that the lumenal domain of Ktr4 is responsible for recognition by the Erv41-Erv46 complex. Thus, ER exit of Kre2-family proteins is dependent on distinct adaptor proteins and our results provide new insights into the traffic of Kre2-family mannosyltransferases.

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

    Science.gov (United States)

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

    2016-03-01

    Nuclear export factor 1 (NXF1) exports mRNA to the cytoplasm after recruitment to mRNA by specific adaptor proteins. How and why cells use numerous different export adaptors is poorly understood. Here we critically evaluate members of the SR protein family (SRSF1-7) for their potential to act as NXF1 adaptors that couple pre-mRNA processing to mRNA export. Consistent with this proposal, >1000 endogenous mRNAs required individual SR proteins for nuclear export in vivo. To address the mechanism, transcriptome-wide RNA-binding profiles of NXF1 and SRSF1-7 were determined in parallel by individual-nucleotide-resolution UV cross-linking and immunoprecipitation (iCLIP). Quantitative comparisons of RNA-binding sites showed that NXF1 and SR proteins bind mRNA targets at adjacent sites, indicative of cobinding. SRSF3 emerged as the most potent NXF1 adaptor, conferring sequence specificity to RNA binding by NXF1 in last exons. Interestingly, SRSF3 and SRSF7 were shown to bind different sites in last exons and regulate 3' untranslated region length in an opposing manner. Both SRSF3 and SRSF7 promoted NXF1 recruitment to mRNA. Thus, SRSF3 and SRSF7 couple alternative splicing and polyadenylation to NXF1-mediated mRNA export, thereby controlling the cytoplasmic abundance of transcripts with alternative 3' ends. PMID:26944680

  16. Yeast Golgi-localized, gamma-Ear-containing, ADP-ribosylation factor-binding proteins are but adaptor protein-1 is not required for cell-free transport of membrane proteins from the trans-Golgi network to the prevacuolar compartment.

    Science.gov (United States)

    Abazeed, Mohamed E; Fuller, Robert S

    2008-11-01

    Golgi-localized, gamma-Ear-containing, ADP-ribosylation factor-binding proteins (GGAs) and adaptor protein-1 (AP-1) mediate clathrin-dependent trafficking of transmembrane proteins between the trans-Golgi network (TGN) and endosomes. In yeast, the vacuolar sorting receptor Vps10p follows a direct pathway from the TGN to the late endosome/prevacuolar compartment (PVC), whereas, the processing protease Kex2p partitions between the direct pathway and an indirect pathway through the early endosome. To examine the roles of the Ggas and AP-1 in TGN-PVC transport, we used a cell-free assay that measures delivery to the PVC of either Kex2p or a chimeric protein (K-V), in which the Vps10p cytosolic tail replaces the Kex2p tail. Either antibody inhibition or dominant-negative Gga2p completely blocked K-V transport but only partially blocked Kex2p transport. Deletion of APL2, encoding the beta subunit of AP-1, did not affect K-V transport but partially blocked Kex2p transport. Residual Kex2p transport seen with apl2Delta membranes was insensitive to dominant-negative Gga2p, suggesting that the apl2Delta mutation causes Kex2p to localize to a compartment that precludes Gga-dependent trafficking. These results suggest that yeast Ggas facilitate the specific and direct delivery of Vps10p and Kex2p from the TGN to the PVC and that AP-1 modulates Kex2p trafficking through a distinct pathway, presumably involving the early endosome. PMID:18784256

  17. Yeast Golgi-localized, γ-Ear–containing, ADP-Ribosylation Factor-binding Proteins Are but Adaptor Protein-1 Is Not Required for Cell-free Transport of Membrane Proteins from the Trans-Golgi Network to the Prevacuolar Compartment

    Science.gov (United States)

    Abazeed, Mohamed E.

    2008-01-01

    Golgi-localized, γ-Ear–containing, ADP-ribosylation factor-binding proteins (GGAs) and adaptor protein-1 (AP-1) mediate clathrin-dependent trafficking of transmembrane proteins between the trans-Golgi network (TGN) and endosomes. In yeast, the vacuolar sorting receptor Vps10p follows a direct pathway from the TGN to the late endosome/prevacuolar compartment (PVC), whereas, the processing protease Kex2p partitions between the direct pathway and an indirect pathway through the early endosome. To examine the roles of the Ggas and AP-1 in TGN–PVC transport, we used a cell-free assay that measures delivery to the PVC of either Kex2p or a chimeric protein (K-V), in which the Vps10p cytosolic tail replaces the Kex2p tail. Either antibody inhibition or dominant-negative Gga2p completely blocked K-V transport but only partially blocked Kex2p transport. Deletion of APL2, encoding the β subunit of AP-1, did not affect K-V transport but partially blocked Kex2p transport. Residual Kex2p transport seen with apl2Δ membranes was insensitive to dominant-negative Gga2p, suggesting that the apl2Δ mutation causes Kex2p to localize to a compartment that precludes Gga-dependent trafficking. These results suggest that yeast Ggas facilitate the specific and direct delivery of Vps10p and Kex2p from the TGN to the PVC and that AP-1 modulates Kex2p trafficking through a distinct pathway, presumably involving the early endosome. PMID:18784256

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

    Lifescience Database Archive (English)

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

  19. PIP2: choreographer of actin-adaptor proteins in the HIV-1 dance

    Science.gov (United States)

    Rocha-Perugini, Vera; Gordon-Alonso, Mónica; Sánchez-Madrid, Francisco

    2014-01-01

    The actin cytoskeleton plays a key role during the replication cycle of human immunodeficiency virus-1 (HIV-1). HIV-1 infection is affected by cellular proteins that influence the clustering of viral receptors or the subcortical actin cytoskeleton. Several of these actin-adaptor proteins are controlled by the second messenger phosphatidylinositol 4,5-biphosphate (PIP2), an important regulator of actin organization. PIP2 production is induced by HIV-1 attachment and facilitates viral infection. However, the importance of PIP2 in regulating cytoskeletal proteins and thus HIV-1 infection has been overlooked. This review examines recent reports describing the roles played by actin-adaptor proteins during HIV-1 infection of CD4+ T cells, highlighting the influence of the signaling lipid PIP2 in this process. PMID:24768560

  20. Chromatin Adaptor Brd4 Modulates E2 Transcription Activity and Protein Stability*

    OpenAIRE

    Lee, A-Young; Chiang, Cheng-Ming

    2009-01-01

    Brd4 is a chromatin adaptor containing tandem bromodomains binding to acetylated histone H3 and H4. Although Brd4 has been implicated in the transcriptional control of papillomavirus-encoded E2 protein, it is unclear how Brd4 regulates E2 function and whether the involvement of Brd4 in transactivation and transrepression is common to different types of E2 proteins. Using DNase I footprinting performed with in vitro reconstituted human papillomavirus (HPV) chromatin and...

  1. Role of SRC-like adaptor protein (SLAP) in immune and malignant cell signaling.

    Science.gov (United States)

    Kazi, Julhash U; Kabir, Nuzhat N; Rönnstrand, Lars

    2015-07-01

    SRC-like adaptor protein (SLAP) is an adaptor protein structurally similar to the SRC family protein kinases. Like SRC, SLAP contains an SH3 domain followed by an SH2 domain but the kinase domain has been replaced by a unique C-terminal region. SLAP is expressed in a variety of cell types. Current studies suggest that it regulates signaling of various cell surface receptors including the B cell receptor, the T cell receptor, cytokine receptors and receptor tyrosine kinases which are important regulator of immune and cancer cell signaling. SLAP targets receptors, or its associated components, by recruiting the ubiquitin machinery and thereby destabilizing signaling. SLAP directs receptors to ubiquitination-mediated degradation and controls receptors turnover as well as signaling. Thus, SLAP appears to be an important component in regulating signal transduction required for immune and malignant cells.

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

    Directory of Open Access Journals (Sweden)

    Ebbe Toftgaard Poulsen

    2015-12-01

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

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

    Science.gov (United States)

    Velazquez, Laura

    2012-12-01

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

  4. Science Signaling Podcast for 12 July 2016: Adaptor proteins limit signaling.

    Science.gov (United States)

    Wiley, H Steven; VanHook, Annalisa M

    2016-01-01

    This Podcast features an interview with Steven Wiley, senior author of a Research Article that appears in the 12 July 2016 issue of Science Signaling, about how the abundance of adaptor proteins and feedback regulators affect the flow of information downstream of the epidermal growth factor receptor (EGFR). Information flows through a signaling pathway by sequential interactions between core components of the pathway, many of which have enzymatic activity. Adaptor proteins do not directly participate in relaying the signal and do not have enzymatic activity, but are important for signaling because they facilitate interactions between the core components. Using quantitative methods, Shi et al demonstrated that core components of the EGFR pathway were highly abundant in both normal cells and cancer cells. However, adaptor proteins were present in much lower abundance in both cell types, indicating that it is the abundance of these proteins that limit signaling downstream of EGFR. The authors also found that differences in EGFR signaling between different cell types likely resulted from the variable abundance of feedback regulators.Listen to Podcast. PMID:27405978

  5. Selective autophagy of non-ubiquitylated targets in plants: looking for cognate receptor/adaptor proteins

    Directory of Open Access Journals (Sweden)

    Vasko eVeljanovski

    2014-06-01

    Full Text Available Cellular homeostasis is essential for the physiology of eukaryotic cells. Eukaryotic cells, including plant cells, utilize two main pathways to adjust the level of cytoplasmic components, namely the proteasomal and the lysosomal/vacuolar pathways. Macroautophagy is a lysosomal/vacuolar pathway which, until recently, was thought to be non-specific and a bulk degradation process. However, selective autophagy which can be activated in the cell under various physiological conditions, involves the specific degradation of defined macromolecules or organelles by a conserved molecular mechanism. For this process to be efficient, the mechanisms underlying the recognition and selection of the cargo to be engulfed by the double-membrane autophagosome are critical, and not yet well understood. Ubiquitin (poly-ubiquitin conjugation to the target appears to be a conserved ligand mechanism in many types of selective autophagy, and defined receptors/adaptors recognizing and regulating the autophagosomal capture of the ubiquitylated target have been characterized. However, non-proteinaceous and non-ubiquitylated cargoes are also selectively degraded by this pathway. This ubiquitin-independent selective autophagic pathway also involves receptor and/or adaptor proteins linking the cargo to the autophagic machinery. Some of these receptor/adaptor proteins including accessory autophagy-related (Atg and non-Atg proteins have been described in yeast and animal cells but not yet in plants. In this review we discuss the ubiquitin-independent cargo selection mechanisms in selective autophagy degradation of organelles and macromolecules and speculate on potential plant receptor/adaptor proteins.

  6. Versatile modes of peptide recognition by the AAA+ adaptor protein SspB

    Energy Technology Data Exchange (ETDEWEB)

    Levchenko, Igor; Grant, Robert A.; Flynn, Julia M.; Sauer, Robert T.; Baker, Tania A. (MIT)

    2010-07-19

    Energy-dependent proteases often rely on adaptor proteins to modulate substrate recognition. The SspB adaptor binds peptide sequences in the stress-response regulator RseA and in ssrA-tagged proteins and delivers these molecules to the AAA+ ClpXP protease for degradation. The structure of SspB bound to an ssrA peptide is known. Here, we report the crystal structure of a complex between SspB and its recognition peptide in RseA. Notably, the RseA sequence is positioned in the peptide-binding groove of SspB in a direction opposite to the ssrA peptide, the two peptides share only one common interaction with the adaptor, and the RseA interaction site is substantially larger than the overlapping ssrA site. This marked diversity in SspB recognition of different target proteins indicates that it is capable of highly flexible and dynamic substrate delivery.

  7. Molecular physiology of the tensin brotherhood of integrin adaptor proteins.

    Science.gov (United States)

    Haynie, Donald T

    2014-07-01

    Numerous proteins have been identified as constituents of the adhesome, the totality of molecular components in the supramolecular assemblies known as focal adhesions, fibrillar adhesions and other kinds of adhesive contact. The transmembrane receptor proteins called integrins are pivotal adhesome members, providing a physical link between the extracellular matrix (ECM) and the actin cytoskeleton. Tensins are ever more widely investigated intracellular adhesome constituents. Involved in cell attachment and migration, cytoskeleton reorganization, signal transduction and other processes relevant to cancer research, tensins have recently been linked to functional properties of deleted in liver cancer 1 (DLC1) and a mitogen-activated protein kinases (MAPK), to cell migration in breast cancer, and to metastasis suppression in the kidney. Tensins are close relatives of phosphatase homolog/tensin homolog (PTEN), an extensively studied tumor suppressor. Such findings are recasting the earlier vision of tensin (TNS) as an actin-filament (F-actin) capping protein in a different light. This critical review aims to summarize current knowledge on tensins and thus to highlight key points concerning the expression, structure, function, and evolution of the various members of the TNS brotherhood. Insight is sought by comparisons with homologous proteins. Some historical points are added for perspective. PMID:24634006

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

    NARCIS (Netherlands)

    M.A. Schlager (Max)

    2010-01-01

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

  9. Surfactant Protein A Enhances Constitutive Immune Functions of Clathrin Heavy Chain and Clathrin Adaptor Protein 2.

    Science.gov (United States)

    Moulakakis, Christina; Steinhäuser, Christine; Biedziak, Dominika; Freundt, Katja; Reiling, Norbert; Stamme, Cordula

    2016-07-01

    NF-κB transcription factors are key regulators of pulmonary inflammatory disorders and repair. Constitutive lung cell type- and microenvironment-specific NF-κB/inhibitor κBα (IκB-α) regulation, however, is poorly understood. Surfactant protein (SP)-A provides both a critical homeostatic and lung defense control, in part by immune instruction of alveolar macrophages (AMs) via clathrin-mediated endocytosis. The central endocytic proteins, clathrin heavy chain (CHC) and the clathrin adaptor protein (AP) complex AP2, have pivotal alternative roles in cellular homeostasis that are endocytosis independent. Here, we dissect endocytic from alternative functions of CHC, the α-subunit of AP2, and dynamin in basal and SP-A-modified LPS signaling of macrophages. As revealed by pharmacological inhibition and RNA interference in primary AMs and RAW264.7 macrophages, respectively, CHC and α-adaptin, but not dynamin, prevent IκB-α degradation and TNF-α release, independent of their canonical role in membrane trafficking. Kinetics studies employing confocal microscopy, Western analysis, and immunomagnetic sorting revealed that SP-A transiently enhances the basal protein expression of CHC and α-adaptin, depending on early activation of protein kinase CK2 (former casein kinase II) and Akt1 in primary AMs from rats, SP-A(+/+), and SP-A(-/-) mice, as well as in vivo when intratracheally administered to SP-A(+/+) mice. Constitutive immunomodulation by SP-A, but not SP-A-mediated inhibition of LPS-induced NF-κB activity and TNF-α release, requires CHC, α-adaptin, and dynamin. Our data demonstrate that endocytic proteins constitutively restrict NF-κB activity in macrophages and provide evidence that SP-A enhances the immune regulatory capacity of these proteins, revealing a previously unknown pathway of microenvironment-specific NF-κB regulation in the lung. PMID:26771574

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

    Science.gov (United States)

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

    2014-03-01

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

  11. Chimeric adaptor proteins translocate diverse type VI secretion system effectors in Vibrio cholerae.

    Science.gov (United States)

    Unterweger, Daniel; Kostiuk, Benjamin; Ötjengerdes, Rina; Wilton, Ashley; Diaz-Satizabal, Laura; Pukatzki, Stefan

    2015-08-13

    Vibrio cholerae is a diverse species of Gram-negative bacteria, commonly found in the aquatic environment and the causative agent of the potentially deadly disease cholera. These bacteria employ a type VI secretion system (T6SS) when they encounter prokaryotic and eukaryotic competitors. This contractile puncturing device translocates a set of effector proteins into neighboring cells. Translocated effectors are toxic unless the targeted cell produces immunity proteins that bind and deactivate incoming effectors. Comparison of multiple V. cholerae strains indicates that effectors are encoded in T6SS effector modules on mobile genetic elements. We identified a diverse group of chimeric T6SS adaptor proteins required for the translocation of diverse effectors encoded in modules. An example for a T6SS effector that requires T6SS adaptor protein 1 (Tap-1) is TseL found in pandemic V. cholerae O1 serogroup strains and other clinical isolates. We propose a model in which Tap-1 is required for loading TseL onto the secretion apparatus. After T6SS-mediated TseL export is completed, Tap-1 is retained in the bacterial cell to load other T6SS machines.

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

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    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.

  13. The Influences of Connectors and Adaptors to Fiber-To-The-Home Network Performance

    Directory of Open Access Journals (Sweden)

    Mohammad S. Ab-Rahman

    2012-01-01

    Full Text Available Problem statement: The reliability of the entire communications network was dependent on the reliability of each single element. Connector was important devices that can affect the performance of the fiber communication. There were a large number of issues that affect the performance of fiber optic connectors in todays networks. These factors were increasingly as data rates, the number of wavelengths and transmission distances continue to escalate. Approach: Therefore this study was carried out to test on the influence of connectors and adapters to the performance of the optical network. Initially the actual attenuation of connector and adaptor were tested by using multifunction loss tester. The first two 1 m corning optical fibers with a connector at each end are measured. Then, both the 1 m corning optical fibers were joined together by an adaptor and connected to the Multifunction loss tester. Three types of wavelength are used as the source to test the attenuation of the fiber which is 1310, 1490-1550 nm. In order to measure the Bit Error Rate (BER and the power loss in optical fiber communication, a simple simulation was carried out by using software opti sys. Results: The attenuation on the connector was caused mainly by existence of impurities in the connector, less perfect connection, scattering of beam and others. These causes the parameter such as power received, Q-factor, minimum BER and also the eye-height to change. Changes in these parameters also affect the performance at the user end. It was very critical that causes of attenuation to be eliminated. Conclusion/Recommendations: From the result it can be concluded that, the greater the attenuation, the greater the decrease in power received. It also affects the Q-factor of the system where as the attenuation increase, the maximum Q-factor decreases. As for the minimum BER, minimum BER changes as the attenuation increase initially, after a maximum value it decreases as the

  14. Src-like-adaptor protein (SLAP) differentially regulates normal and oncogenic c-Kit signaling.

    Science.gov (United States)

    Kazi, Julhash U; Agarwal, Shruti; Sun, Jianmin; Bracco, Enrico; Rönnstrand, Lars

    2014-02-01

    The Src-like-adaptor protein (SLAP) is an adaptor protein sharing considerable structural homology with Src. SLAP is expressed in a variety of cells and regulates receptor tyrosine kinase signaling by direct association. In this report, we show that SLAP associates with both wild-type and oncogenic c-Kit (c-Kit-D816V). The association involves the SLAP SH2 domain and receptor phosphotyrosine residues different from those mediating Src interaction. Association of SLAP triggers c-Kit ubiquitylation which, in turn, is followed by receptor degradation. Although SLAP depletion potentiates c-Kit downstream signaling by stabilizing the receptor, it remains non-functional in c-Kit-D816V signaling. Ligand-stimulated c-Kit or c-Kit-D816V did not alter membrane localization of SLAP. Interestingly oncogenic c-Kit-D816V, but not wild-type c-Kit, phosphorylates SLAP on residues Y120, Y258 and Y273. Physical interaction between c-Kit-D816V and SLAP is mandatory for the phosphorylation to take place. Although tyrosine-phosphorylated SLAP does not affect c-Kit-D816V signaling, mutation of these tyrosine sites to phenylalanine can restore SLAP activity. Taken together the data demonstrate that SLAP negatively regulates wild-type c-Kit signaling, but not its oncogenic counterpart, indicating a possible mechanism by which the oncogenic c-Kit bypasses the normal cellular negative feedback control.

  15. 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.

  16. A role for adaptor protein-3 complex in the organization of the endocytic pathway in Dictyostelium.

    Science.gov (United States)

    Charette, Steve J; Mercanti, Valentina; Letourneur, François; Bennett, Nelly; Cosson, Pierre

    2006-11-01

    Dictyostelium discoideum cells continuously internalize extracellular material, which accumulates in well-characterized endocytic vacuoles. In this study, we describe a new endocytic compartment identified by the presence of a specific marker, the p25 protein. This compartment presents features reminiscent of mammalian recycling endosomes: it is localized in the pericentrosomal region but distinct from the Golgi apparatus. It specifically contains surface proteins that are continuously endocytosed but rapidly recycled to the cell surface and thus absent from maturing endocytic compartments. We evaluated the importance of each clathrin-associated adaptor complex in establishing a compartmentalized endocytic system by studying the phenotype of the corresponding mutants. In knockout cells for mu3, a subunit of the AP-3 clathrin-associated complex, membrane proteins normally restricted to p25-positive endosomes were mislocalized to late endocytic compartments. Our results suggest that AP-3 plays an essential role in the compartmentalization of the endocytic pathway in Dictyostelium. PMID:17010123

  17. 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....../ CD3gamma molecules independently of S126. An acidic amino acid is required at position 127 and a leucine (L) is required at position 131, whereas the requirements for position 132 are more relaxed. The spacing between aspartic acid 127 (D127) and L131 is crucial for the function of the motif in vivo...... subunit clusters of differentiation (CD)3gamma. Thus, phosphorylation of CD3gamma serine 126 (S126) causes a downregulation of the TCR. In this study, we have analyzed the CD3gamma internalization motif in three different systems in parallel: in the context of the complete multimeric TCR; in monomeric CD4...

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

    Science.gov (United States)

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

    2016-07-15

    Th17 cells have been casually associated to the pathogenesis of autoimmune disease. We have previously demonstrated that Rai/ShcC, a member of the Shc family of adaptor proteins, negatively regulates Th17 cell differentiation and lupus autoimmunity. In this study, we have investigated the pathogenic outcome of the Th17 bias associated with Rai deficiency on multiple sclerosis development, using the experimental autoimmune encephalomyelitis (EAE) mouse model. We found that, unexpectedly, EAE was less severe in Rai(-/-) mice compared with their wild-type counterparts despite an enhanced generation of myelin-specific Th17 cells that infiltrated into the CNS. Nevertheless, when adoptively transferred into immunodeficient Rai(+/+) mice, these cells promoted a more severe disease compared with wild-type encephalitogenic Th17 cells. This paradoxical phenotype was caused by a dampened inflammatory response of astrocytes, which were found to express Rai, to IL-17. The results provide evidence that Rai plays opposite roles in Th17 cell differentiation and astrocyte activation, with the latter dominant over the former in EAE, highlighting this adaptor as a potential novel target for the therapy of multiple sclerosis. PMID:27288534

  19. Molecular basis of substrate selection by the N-end rule adaptor protein ClpS

    Energy Technology Data Exchange (ETDEWEB)

    Román-Hernández, Giselle; Grant, Robert A.; Sauer, Robert T.; Baker, Tania A.; (HHMI)

    2009-06-19

    The N-end rule is a conserved degradation pathway that relates the stability of a protein to its N-terminal amino acid. Here, we present crystal structures of ClpS, the bacterial N-end rule adaptor, alone and engaged with peptides containing N-terminal phenylalanine, leucine, and tryptophan. These structures, together with a previous structure of ClpS bound to an N-terminal tyrosine, illustrate the molecular basis of recognition of the complete set of primary N-end rule amino acids. In each case, the alpha-amino group and side chain of the N-terminal residue are the major determinants of recognition. The binding pocket for the N-end residue is preformed in the free adaptor, and only small adjustments are needed to accommodate N-end rule residues having substantially different sizes and shapes. M53A ClpS is known to mediate degradation of an expanded repertoire of substrates, including those with N-terminal valine or isoleucine. A structure of Met53A ClpS engaged with an N-end rule tryptophan reveals an essentially wild-type mechanism of recognition, indicating that the Met(53) side chain directly enforces specificity by clashing with and excluding beta-branched side chains. Finally, experimental and structural data suggest mechanisms that make proteins with N-terminal methionine bind very poorly to ClpS, explaining why these high-abundance proteins are not degraded via the N-end rule pathway in the cell.

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

    Directory of Open Access Journals (Sweden)

    Rynditch A. V.

    2012-12-01

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

  1. 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.

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

    Science.gov (United States)

    Balasubramaniam, Vinod R M T; Hong Wai, Tham; Ario Tejo, Bimo; Omar, Abdul Rahman; Syed Hassan, Sharifah

    2013-01-01

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

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

    Science.gov (United States)

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

    2008-10-17

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

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

    Directory of Open Access Journals (Sweden)

    Petr eDraber

    2012-01-01

    Full Text Available Aggregation of the high-affinity IgE receptor (FcεRI initiates a cascade of signaling events leading to release of preformed inflammatory and allergy mediators and de novo synthesis and secretion of cytokines and other compounds. The first biochemically well defined step of this signaling cascade is tyrosine phosphorylation of the FcεRI subunits by Src family kinase Lyn, followed by recruitment and activation of Syk kinase. Activity of Syk is decisive for the formation of multicomponent signaling assemblies, the signalosomes, in the vicinity of the receptors. Formation of the signalosomes is dependent on the presence of transmembrane adaptor proteins (TRAPs. These proteins are characterized by a short extracellular domain, a single transmembrane domain and a cytoplasmic tail with various motifs serving as anchors for cytoplasmic signaling molecules. In mast cells five TRAPs have been identified (LAT, NTAL, LAX, PAG and GAPT; engagement of four of them (LAT, NTAL, LAX and PAG in FcεRI signaling has been documented. Here we discuss recent progress in the understanding of how TRAPs affect FcεRI-mediated mast cell signaling. The combined data indicate that individual TRAPs have irreplaceable roles in important signaling events such as calcium response, degranulation, cytokines production and chemotaxis.

  5. Novel isoform of adaptor protein ITSN1 forms homodimers via its C-terminus

    Directory of Open Access Journals (Sweden)

    Skrypkina I. Ya.

    2011-06-01

    Full Text Available Aim. Previously we have identified a novel isoform of endocytic adaptor protein ITSN1 designated as ITSN122a. Western blot revealed two immunoreactive bands of 120 and 250 kDa that corresponded to ITSN1-22a. The goal of this study was to investigate the possibility of dimer formation by the novel isoform. Methods. Dimerization ability of ITSN1-22a was tested by immunoprecipitation and subsequent Western blot analysis. To specify the region responsible for dimerization, site-directed mutagenesis and truncation analysis were carried out. Inhibition of endocytosis by potassium depletion and EGF stimulation of HEK293 were performed. Results. We have found that ITSN1-22a forms dimers in HEK293 cells. The dimerization of ITSN1-22a was mediated by C-terminal domain. We showed that cysteines C1016 and C1019 were involved in homodimerization. Inhibition of clathrin-mediated endocytosis and mitogen stimulation did not affect ITSN1-22a dimer formation. Conclusions. ITSN1-22a is the only one known ITSN1 isoform, which is capable to form homodimers via disulphide bonds. This could be important for the formation of protein complexes containing ITSN1 molecules.

  6. Impairment of dendritic cell functions in patients with adaptor protein-3 complex deficiency.

    Science.gov (United States)

    Prandini, Alberto; Salvi, Valentina; Colombo, Francesca; Moratto, Daniele; Lorenzi, Luisa; Vermi, William; De Francesco, Maria Antonia; Notarangelo, Lucia Dora; Porta, Fulvio; Plebani, Alessandro; Facchetti, Fabio; Sozzani, Silvano; Badolato, Raffaele

    2016-06-30

    Hermansky-Pudlak syndrome type 2 (HPS2) is a primary immunodeficiency due to adaptor protein-3 (AP-3) complex deficiency. HPS2 patients present neutropenia, partial albinism, and impaired lysosomal vesicles formation in hematopoietic cells. Given the role of dendritic cells (DCs) in the immune response, we studied monocyte-derived DCs (moDCs) and plasmacytoid DCs (pDCs) in two HPS2 siblings. Mature HPS2 moDCs showed impaired expression of CD83 and DC-lysosome-associated membrane protein (LAMP), low levels of MIP1-β/CCL4, MIG/CXCL9, and severe defect of interleukin-12 (IL-12) secretion. DCs in lymph-node biopsies from the same patients showed a diffuse cytoplasm reactivity in a large fraction of DC-LAMP(+) cells, instead of the classical dot-like stain. In addition, analysis of pDC-related functions of blood-circulating mononuclear cells revealed reduced interferon-α secretion in response to herpes simplex virus-1 (HSV-1), whereas granzyme-B induction upon IL-3/IL-10 stimulation was normal. Finally, T-cell costimulatory activity, as measured by mixed lymphocyte reaction assay, was lower in patients, suggesting that function and maturation of DCs is abnormal in patients with HPS2.

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

    Science.gov (United States)

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

    2012-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Chia-Yi Yu

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

  9. Adaptor protein LNK is a negative regulator of brain neural stem cell proliferation after stroke.

    Science.gov (United States)

    Ahlenius, Henrik; Devaraju, Karthikeyan; Monni, Emanuela; Oki, Koichi; Wattananit, Somsak; Darsalia, Vladimer; Iosif, Robert E; Torper, Olof; Wood, James C; Braun, Sebastian; Jagemann, Lucas; Nuber, Ulrike A; Englund, Elisabet; Jacobsen, Sten-Eirik W; Lindvall, Olle; Kokaia, Zaal

    2012-04-11

    Ischemic stroke causes transient increase of neural stem and progenitor cell (NSPC) proliferation in the subventricular zone (SVZ), and migration of newly formed neuroblasts toward the damaged area where they mature to striatal neurons. The molecular mechanisms regulating this plastic response, probably involved in structural reorganization and functional recovery, are poorly understood. The adaptor protein LNK suppresses hematopoietic stem cell self-renewal, but its presence and role in the brain are poorly understood. Here we demonstrate that LNK is expressed in NSPCs in the adult mouse and human SVZ. Lnk(-/-) mice exhibited increased NSPC proliferation after stroke, but not in intact brain or following status epilepticus. Deletion of Lnk caused increased NSPC proliferation while overexpression decreased mitotic activity of these cells in vitro. We found that Lnk expression after stroke increased in SVZ through the transcription factors STAT1/3. LNK attenuated insulin-like growth factor 1 signaling by inhibition of AKT phosphorylation, resulting in reduced NSPC proliferation. Our findings identify LNK as a stroke-specific, endogenous negative regulator of NSPC proliferation, and suggest that LNK signaling is a novel mechanism influencing plastic responses in postischemic brain. PMID:22496561

  10. Mint3/X11γ Is an ADP-Ribosylation Factor-dependent Adaptor that Regulates the Traffic of the Alzheimer's Precursor Protein from the Trans-Golgi Network

    OpenAIRE

    Shrivastava-Ranjan, Punya; Faundez, Victor; Fang, Guofu; Rees, Howard; Lah, James J.; Allan I Levey; Kahn, Richard A.

    2008-01-01

    β-Amyloid peptides (Aβ) are the major component of plaques in brains of Alzheimer's patients, and are they derived from the proteolytic processing of the β-amyloid precursor protein (APP). The movement of APP between organelles is highly regulated, and it is tightly connected to its processing by secretases. We proposed previously that transport of APP within the cell is mediated in part through its sorting into Mint/X11-containing carriers. To test our hypothesis, we purified APP-containing ...

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

    NARCIS (Netherlands)

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

    2008-01-01

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

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

    DEFF Research Database (Denmark)

    Su, J; Batzer, A; Sap, J

    1994-01-01

    -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......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...... links a receptor tyrosine phosphatase with a key component of a central cellular signalling pathway and provides a basis for addressing R-PTP-alpha function....

  13. Molecular basis for the specific recognition of the metazoan cyclic GMP-AMP by the innate immune adaptor protein STING.

    Science.gov (United States)

    Shi, Heping; Wu, Jiaxi; Chen, Zhijian J; Chen, Chuo

    2015-07-21

    Cyclic GMP-AMP containing a unique combination of mixed phosphodiester linkages (2'3'-cGAMP) is an endogenous second messenger molecule that activates the type-I IFN pathway upon binding to the homodimer of the adaptor protein STING on the surface of endoplasmic reticulum membrane. However, the preferential binding of the asymmetric ligand 2'3'-cGAMP to the symmetric dimer of STING represents a physicochemical enigma. Here we show that 2'3'-cGAMP, but not its linkage isomers, adopts an organized free-ligand conformation that resembles the STING-bound conformation and pays low entropy and enthalpy costs in converting into the active conformation. Our results demonstrate that analyses of free-ligand conformations can be as important as analyses of protein conformations in understanding protein-ligand interactions.

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

    DEFF Research Database (Denmark)

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

    1996-01-01

    Receptor protein-tyrosine phosphatase RPTPalpha is found associated in vivo with the adaptor protein Grb2. Formation of this complex, which contains no detectable levels of Sos, is known to depend on a C-terminal phosphorylated tyrosine residue (Tyr798) in RPTPalpha and on the Src homology (SH) 2...

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

    DEFF Research Database (Denmark)

    Barres, Romain; Grémeaux, Thierry; Gual, Philippe;

    2006-01-01

    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...

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

    Directory of Open Access Journals (Sweden)

    Marks David R

    2009-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Daniel Pérez-Núñez

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

  18. Disruption of adaptor protein 2mu (AP-2mu) in cochlear hair cells impairs vesicle reloading of synaptic release sites and hearing

    NARCIS (Netherlands)

    Jung, S.; Maritzen, T.; Wichmann, C.; Jing, Z.; Neef, A.; Revelo, N.H.; Al-Moyed, H.; Meese, S.; Wojcik, S.M.; Panou, I.; Bulut, H.; Schu, P.; Ficner, R.; Reisinger, E.; Rizzoli, S.O.; Neef, J.; Strenzke, N.; Haucke, V.; Moser, T.

    2015-01-01

    Active zones (AZs) of inner hair cells (IHCs) indefatigably release hundreds of vesicles per second, requiring each release site to reload vesicles at tens per second. Here, we report that the endocytic adaptor protein 2mu (AP-2mu) is required for release site replenishment and hearing. We show that

  19. 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

    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.

  20. Adaptor protein complexes AP-1 and AP-3 are required by the HHV-7 Immunoevasin U21 for rerouting of class I MHC molecules to the lysosomal compartment.

    Directory of Open Access Journals (Sweden)

    Lisa A Kimpler

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

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

    Science.gov (United States)

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

    2009-03-20

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

  2. A Cyclic di-GMP-binding Adaptor Protein Interacts with Histidine Kinase to Regulate Two-component Signaling.

    Science.gov (United States)

    Xu, Linghui; Venkataramani, Prabhadevi; Ding, Yichen; Liu, Yang; Deng, Yinyue; Yong, Grace Lisi; Xin, Lingyi; Ye, Ruijuan; Zhang, Lianhui; Yang, Liang; Liang, Zhao-Xun

    2016-07-29

    The bacterial messenger cyclic di-GMP (c-di-GMP) binds to a diverse range of effectors to exert its biological effect. Despite the fact that free-standing PilZ proteins are by far the most prevalent c-di-GMP effectors known to date, their physiological function and mechanism of action remain largely unknown. Here we report that the free-standing PilZ protein PA2799 from the opportunistic pathogen Pseudomonas aeruginosa interacts directly with the hybrid histidine kinase SagS. We show that PA2799 (named as HapZ: histidine kinase associated PilZ) binds directly to the phosphoreceiver (REC) domain of SagS, and that the SagS-HapZ interaction is further enhanced at elevated c-di-GMP concentration. We demonstrate that binding of HapZ to SagS inhibits the phosphotransfer between SagS and the downstream protein HptB in a c-di-GMP-dependent manner. In accordance with the role of SagS as a motile-sessile switch and biofilm growth factor, we show that HapZ impacts surface attachment and biofilm formation most likely by regulating the expression of a large number of genes. The observations suggest a previously unknown mechanism whereby c-di-GMP mediates two-component signaling through a PilZ adaptor protein.

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

    Institute of Scientific and Technical Information of China (English)

    va Korpos; Ferenc Dek; Ibolya Kiss

    2015-01-01

    The extracellular matrix (ECM) performs essential functions in the differentiation, maintenance and remodeling of tissues during development and regeneration, and it undergoes dynamic chang-es 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 junc-tion 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.

  4. A Cyclic di-GMP-binding Adaptor Protein Interacts with Histidine Kinase to Regulate Two-component Signaling.

    Science.gov (United States)

    Xu, Linghui; Venkataramani, Prabhadevi; Ding, Yichen; Liu, Yang; Deng, Yinyue; Yong, Grace Lisi; Xin, Lingyi; Ye, Ruijuan; Zhang, Lianhui; Yang, Liang; Liang, Zhao-Xun

    2016-07-29

    The bacterial messenger cyclic di-GMP (c-di-GMP) binds to a diverse range of effectors to exert its biological effect. Despite the fact that free-standing PilZ proteins are by far the most prevalent c-di-GMP effectors known to date, their physiological function and mechanism of action remain largely unknown. Here we report that the free-standing PilZ protein PA2799 from the opportunistic pathogen Pseudomonas aeruginosa interacts directly with the hybrid histidine kinase SagS. We show that PA2799 (named as HapZ: histidine kinase associated PilZ) binds directly to the phosphoreceiver (REC) domain of SagS, and that the SagS-HapZ interaction is further enhanced at elevated c-di-GMP concentration. We demonstrate that binding of HapZ to SagS inhibits the phosphotransfer between SagS and the downstream protein HptB in a c-di-GMP-dependent manner. In accordance with the role of SagS as a motile-sessile switch and biofilm growth factor, we show that HapZ impacts surface attachment and biofilm formation most likely by regulating the expression of a large number of genes. The observations suggest a previously unknown mechanism whereby c-di-GMP mediates two-component signaling through a PilZ adaptor protein. PMID:27231351

  5. 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.

  6. The cytoskeleton adaptor protein ankyrin-1 is upregulated by p53 following DNA damage and alters cell migration.

    Science.gov (United States)

    Hall, A E; Lu, W-T; Godfrey, J D; Antonov, A V; Paicu, C; Moxon, S; Dalmay, T; Wilczynska, A; Muller, P A J; Bushell, M

    2016-01-01

    The integrity of the genome is maintained by a host of surveillance and repair mechanisms that are pivotal for cellular function. The tumour suppressor protein p53 is a major component of the DNA damage response pathway and plays a vital role in the maintenance of cell-cycle checkpoints. Here we show that a microRNA, miR-486, and its host gene ankyrin-1 (ANK1) are induced by p53 following DNA damage. Strikingly, the cytoskeleton adaptor protein ankyrin-1 was induced over 80-fold following DNA damage. ANK1 is upregulated in response to a variety of DNA damage agents in a range of cell types. We demonstrate that miR-486-5p is involved in controlling G1/S transition following DNA damage, whereas the induction of the ankyrin-1 protein alters the structure of the actin cytoskeleton and sustains limited cell migration during DNA damage. Importantly, we found that higher ANK1 expression correlates with decreased survival in cancer patients. Thus, these observations highlight ANK1 as an important effector downstream of the p53 pathway. PMID:27054339

  7. Syk Kinase-Coupled C-type Lectin Receptors Engage Protein Kinase C-δ to Elicit Card9 Adaptor-Mediated Innate Immunity

    OpenAIRE

    Strasser, Dominikus; Neumann, Konstantin; Bergmann, Hanna; Marakalala, Mohlopheni J.; Guler, Reto; Rojowska, Anna; Hopfner, Karl-Peter; Brombacher, Frank; Urlaub, Henning; Baier, Gottfried; Brown, Gordon D.; Leitges, Michael; Ruland, Jürgen

    2012-01-01

    Summary C-type lectin receptors (CLRs) that couple with the kinase Syk are major pattern recognition receptors for the activation of innate immunity and host defense. CLRs recognize fungi and other forms of microbial or sterile danger, and they induce inflammatory responses through the adaptor protein Card9. The mechanisms relaying CLR proximal signals to the core Card9 module are unknown. Here we demonstrated that protein kinase C-δ (PKCδ) was activated upon Dectin-1-Syk signaling, mediated ...

  8. The membrane-associated adaptor protein DOK5 is upregulated in systemic sclerosis and associated with IGFBP-5-induced fibrosis.

    Directory of Open Access Journals (Sweden)

    Hidekata Yasuoka

    Full Text Available Systemic sclerosis (SSc is characterized by excessive fibrosis of the skin and internal organs due to fibroblast proliferation and excessive production of extracellular matrix (ECM. We have shown that insulin-like growth factor binding protein (IGFBP-5 plays an important role in the development of fibrosis in vitro, ex vivo, and in vivo. We identified a membrane-associated adaptor protein, downstream of tyrosine kinase/docking protein (DOK5, as an IGFBP-5-regulated target gene using gene expression profiling of primary fibroblasts expressing IGFBP-5. DOK5 is a tyrosine kinase substrate associated with intracellular signaling. Our objective was to determine the role of DOK5 in the pathogenesis of SSc and specifically in IGFBP-5-induced fibrosis. DOK5 mRNA and protein levels were increased in vitro by endogenous and exogenous IGFBP-5 in primary human fibroblasts. DOK5 upregulation required activation of the mitogen-activated protein kinase (MAPK signaling cascade. Further, IGFBP-5 triggered nuclear translocation of DOK5. DOK5 protein levels were also increased in vivo in mouse skin and lung by IGFBP-5. To determine the effect of DOK5 on fibrosis, DOK5 was expressed ex vivo in human skin in organ culture. Expression of DOK5 in human skin resulted in a significant increase in dermal thickness. Lastly, levels of DOK5 were compared in primary fibroblasts and lung tissues of patients with SSc and healthy donors. Both DOK5 mRNA and protein levels were significantly increased in fibroblasts and skin tissues of patients with SSc compared with those of healthy controls, as well as in lung tissues of SSc patients. Our findings suggest that IGFBP-5 induces its pro-fibrotic effects, at least in part, via DOK5. Furthermore, IGFBP-5 and DOK5 are both increased in SSc fibroblasts and tissues and may thus be acting in concert to promote fibrosis.

  9. Positive and negative regulation of FcepsilonRI-mediated signaling by the adaptor protein LAB/NTAL.

    Science.gov (United States)

    Zhu, Minghua; Liu, Yan; Koonpaew, Surapong; Granillo, Olivia; Zhang, Weiguo

    2004-10-18

    Linker for activation of B cells (LAB, also called NTAL; a product of wbscr5 gene) is a newly identified transmembrane adaptor protein that is expressed in B cells, NK cells, and mast cells. Upon BCR activation, LAB is phosphorylated and interacts with Grb2. LAB is capable of rescuing thymocyte development in LAT-deficient mice. To study the in vivo function of LAB, LAB-deficient mice were generated. Although disruption of the Lab gene did not affect lymphocyte development, it caused mast cells to be hyperresponsive to stimulation via the FcepsilonRI, evidenced by enhanced Erk activation, calcium mobilization, degranulation, and cytokine production. These data suggested that LAB negatively regulates mast cell function. However, mast cells that lacked both linker for activation of T cells (LAT) and LAB proteins had a more severe block in FcepsilonRI-mediated signaling than LAT(-/-) mast cells, demonstrating that LAB also shares a redundant function with LAT to play a positive role in FcepsilonRI-mediated signaling.

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

    Directory of Open Access Journals (Sweden)

    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.

  11. 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. PMID:24297163

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

    Directory of Open Access Journals (Sweden)

    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.

  13. Early Loss of Telomerase Action in Yeast Creates a Dependence on the DNA Damage Response Adaptor Proteins.

    Science.gov (United States)

    Jay, Kyle A; Smith, Dana L; Blackburn, Elizabeth H

    2016-07-15

    Telomeres cap the ends of chromosomes, protecting them from degradation and inappropriate DNA repair processes that can lead to genomic instability. A short telomere elicits increased telomerase action on itself that replenishes telomere length, thereby stabilizing the telomere. In the prolonged absence of telomerase activity in dividing cells, telomeres eventually become critically short, inducing a permanent cell cycle arrest (senescence). We recently showed that even early after telomerase inactivation (ETI), yeast cells have accelerated mother cell aging and mildly perturbed cell cycles. Here, we show that the complete disruption of DNA damage response (DDR) adaptor proteins in ETI cells causes severe growth defects. This synthetic-lethality phenotype was as pronounced as that caused by extensive DNA damage in wild-type cells but showed genetic dependencies distinct from such damage and was completely alleviated by SML1 deletion, which increases deoxynucleoside triphosphate (dNTP) pools. Our results indicated that these deleterious effects in ETI cells cannot be accounted for solely by the slow erosion of telomeres due to incomplete replication that leads to senescence. We propose that normally occurring telomeric DNA replication stress is resolved by telomerase activity and the DDR in two parallel pathways and that deletion of Sml1 prevents this stress. PMID:27161319

  14. Nuclear IKKbeta is an adaptor protein for IkappaBalpha ubiquitination and degradation in UV-induced NF-kappaB activation.

    Science.gov (United States)

    Tsuchiya, Yoshihiro; Asano, Tomoichiro; Nakayama, Keiko; Kato, Tomohisa; Karin, Michael; Kamata, Hideaki

    2010-08-27

    Proinflammatory cytokines activate NF-kappaB using the IkappaB kinase (IKK) complex that phosphorylates inhibitory proteins (IkappaBs) at N-terminal sites resulting in their ubiquitination and degradation in the cytoplasm. Although ultraviolet (UV) irradiation does not lead to IKK activity, it activates NF-kappaB by an unknown mechanism through IkappaBalpha degradation without N-terminal phosphorylation. Here, we describe an adaptor function of nuclear IKKbeta in UV-induced IkappaBalpha degradation. UV irradiation induces the nuclear translocation of IkappaBalpha and association with IKKbeta, which constitutively interacts with beta-TrCP through heterogeneous ribonucleoprotein-U (hnRNP-U) leading to IkappaBalpha ubiquitination and degradation. Furthermore, casein kinase 2 (CK2) and p38 associate with IKKbeta and promote IkappaBalpha degradation by phosphorylation at C-terminal sites. Thus, nuclear IKKbeta acts as an adaptor protein for IkappaBalpha degradation in UV-induced NF-kappaB activation. NF-kappaB activated by the nuclear IKKbeta adaptor protein suppresses anti-apoptotic gene expression and promotes UV-induced cell death.

  15. A combinatorial F box protein directed pathway controls TRAF adaptor stability to regulate inflammation

    OpenAIRE

    Chen, Bill B; Coon, Tiffany A.; Glasser, Jennifer R; McVerry, Bryan J.; Zhao, Jing; Zhao, Yutong; Zou, Chunbin; Ellis, Bryon; Sciurba, Frank C.; Zhang, Yingze; Mallampalli, Rama K.

    2013-01-01

    Uncontrolled activation of tumor necrosis factor receptor-associated factor (TRAF) proteins may result in profound tissue injury by linking surface signals to cytokine release. Here we show that a ubiquitin E3 ligase component, Fbxo3, potently stimulates cytokine secretion from human inflammatory cells by destabilizing a sentinel TRAF inhibitor, Fbxl2. Fbxo3 and TRAF protein in circulation positively correlated with cytokine responses in septic subjects and we furthermore identified a hypofun...

  16. CD2v interacts with Adaptor Protein AP-1 during African swine fever infection

    OpenAIRE

    Pérez-Núñez, Daniel; García-Urdiales, Eduardo; Martínez Bonet, Marta; Nogal París, María Luisa; Barroso, Susana; Revilla, Yolanda; Madrid, Ricardo

    2015-01-01

    African swine fever virus (ASFV) CD2v protein is believed to be involved in virulence enhancement, viral hemadsorption, and pathogenesis, although the molecular mechanisms of the function of this viral protein are still not fully understood. Here we describe that CD2v localized around viral factories during ASFV infection, suggesting a role in the generation and/or dynamics of these viral structures and hence in disturbing cellular traffic. We show that CD2v targeted the regulatory trans-Golg...

  17. Molecular analysis of the prostacyclin receptor's interaction with the PDZ1 domain of its adaptor protein PDZK1.

    Directory of Open Access Journals (Sweden)

    Gabriel Birrane

    Full Text Available The prostanoid prostacyclin, or prostaglandin I2, plays an essential role in many aspects of cardiovascular disease. The actions of prostacyclin are mainly mediated through its activation of the prostacyclin receptor or, in short, the IP. In recent studies, the cytoplasmic carboxy-terminal domain of the IP was shown to bind several PDZ domains of the multi-PDZ adaptor PDZK1. The interaction between the two proteins was found to enhance cell surface expression of the IP and to be functionally important in promoting prostacyclin-induced endothelial cell migration and angiogenesis. To investigate the interaction of the IP with the first PDZ domain (PDZ1 of PDZK1, we generated a nine residue peptide (KK(411IAACSLC(417 containing the seven carboxy-terminal amino acids of the IP and measured its binding affinity to a recombinant protein corresponding to PDZ1 by isothermal titration calorimetry. We determined that the IP interacts with PDZ1 with a binding affinity of 8.2 µM. Using the same technique, we also determined that the farnesylated form of carboxy-terminus of the IP does not bind to PDZ1. To understand the molecular basis of these findings, we solved the high resolution crystal structure of PDZ1 bound to a 7-residue peptide derived from the carboxy-terminus of the non-farnesylated form of IP ((411IAACSLC(417. Analysis of the structure demonstrates a critical role for the three carboxy-terminal amino acids in establishing a strong interaction with PDZ1 and explains the inability of the farnesylated form of IP to interact with the PDZ1 domain of PDZK1 at least in vitro.

  18. A combinatorial F box protein directed pathway controls TRAF adaptor stability to regulate inflammation.

    Science.gov (United States)

    Chen, Bill B; Coon, Tiffany A; Glasser, Jennifer R; McVerry, Bryan J; Zhao, Jing; Zhao, Yutong; Zou, Chunbin; Ellis, Bryon; Sciurba, Frank C; Zhang, Yingze; Mallampalli, Rama K

    2013-05-01

    Uncontrolled activation of tumor necrosis factor receptor-associated factor (TRAF) proteins may result in profound tissue injury by linking surface signals to cytokine release. Here we show that a ubiquitin E3 ligase component, Fbxo3, potently stimulates cytokine secretion from human inflammatory cells by destabilizing a sentinel TRAF inhibitor, Fbxl2. Fbxo3 and TRAF protein in circulation positively correlated with cytokine responses in subjects with sepsis, and we identified a polymorphism in human Fbxo3, with one variant being hypofunctional. A small-molecule inhibitor targeting Fbxo3 was sufficient to lessen severity of cytokine-driven inflammation in several mouse disease models. These studies identified a pathway of innate immunity that may be useful to detect subjects with altered immune responses during critical illness or provide a basis for therapeutic intervention targeting TRAF protein abundance. PMID:23542741

  19. Multiple upstream signals converge on the adaptor protein Mst50 in Magnaporthe grisea

    OpenAIRE

    G. Park; Xue, C.; X. Zhao; Kim, Y.; Orbach, M.; Xu, J.R.

    2006-01-01

    Rice blast fungus ( Magnaporthe grisea) forms a highly specialized infection structure for plant penetration, the appressorium, the formation and growth of which are regulated by the Mst11- Mst7- Pmk1 mitogen- activated protein kinase cascade. We characterized the MST50 gene that directly interacts with both MST11 and MST7. Similar to the mst11 mutant, the mst50 mutant was defective in appressorium formation, sens...

  20. A Novel Interaction of the Catalytic Subunit of Protein Phosphatase 2A with the Adaptor Protein CIN85 Suppresses Phosphatase Activity and Facilitates Platelet Outside-in αIIbβ3 Integrin Signaling.

    Science.gov (United States)

    Khatlani, Tanvir; Pradhan, Subhashree; Da, Qi; Shaw, Tanner; Buchman, Vladimir L; Cruz, Miguel A; Vijayan, K Vinod

    2016-08-12

    The transduction of signals generated by protein kinases and phosphatases are critical for the ability of integrin αIIbβ3 to support stable platelet adhesion and thrombus formation. Unlike kinases, it remains unclear how serine/threonine phosphatases engage the signaling networks that are initiated following integrin ligation. Because protein-protein interactions form the backbone of signal transduction, we searched for proteins that interact with the catalytic subunit of protein phosphatase 2A (PP2Ac). In a yeast two-hybrid study, we identified a novel interaction between PP2Ac and an adaptor protein CIN85 (Cbl-interacting protein of 85 kDa). Truncation and alanine mutagenesis studies revealed that PP2Ac binds to the P3 block ((396)PAIPPKKPRP(405)) of the proline-rich region in CIN85. The interaction of purified PP2Ac with CIN85 suppressed phosphatase activity. Human embryonal kidney 293 αIIbβ3 cells overexpressing a CIN85 P3 mutant, which cannot support PP2Ac binding, displayed decreased adhesion to immobilized fibrinogen. Platelets contain the ∼85 kDa CIN85 protein along with the PP2Ac-CIN85 complex. A myristylated cell-permeable peptide derived from residues 395-407 of CIN85 protein (P3 peptide) disrupted the platelet PP2Ac-CIN85 complex and decreased αIIbβ3 signaling dependent functions such as platelet spreading on fibrinogen and thrombin-mediated fibrin clot retraction. In a phospho-profiling study P3 peptide treated platelets also displayed decreased phosphorylation of several signaling proteins including Src and GSK3β. Taken together, these data support a role for the novel PP2Ac-CIN85 complex in supporting integrin-dependent platelet function by dampening the phosphatase activity. PMID:27334924

  1. Structural and Functional Characterization of Cargo-Binding Sites on the μ4-Subunit of Adaptor Protein Complex 4

    Science.gov (United States)

    Ross, Breyan H.; Lin, Yimo; Corales, Esteban A.; Burgos, Patricia V.; Mardones, Gonzalo A.

    2014-01-01

    Adaptor protein (AP) complexes facilitate protein trafficking by playing key roles in the selection of cargo molecules to be sorted in post-Golgi compartments. Four AP complexes (AP-1 to AP-4) contain a medium-sized subunit (μ1-μ4) that recognizes YXXØ-sequences (Ø is a bulky hydrophobic residue), which are sorting signals in transmembrane proteins. A conserved, canonical region in μ subunits mediates recognition of YXXØ-signals by means of a critical aspartic acid. Recently we found that a non-canonical YXXØ-signal on the cytosolic tail of the Alzheimer's disease amyloid precursor protein (APP) binds to a distinct region of the μ4 subunit of the AP-4 complex. In this study we aimed to determine the functionality of both binding sites of μ4 on the recognition of the non-canonical YXXØ-signal of APP. We found that substitutions in either binding site abrogated the interaction with the APP-tail in yeast-two hybrid experiments. Further characterization by isothermal titration calorimetry showed instead loss of binding to the APP signal with only the substitution R283D at the non-canonical site, in contrast to a decrease in binding affinity with the substitution D190A at the canonical site. We solved the crystal structure of the C-terminal domain of the D190A mutant bound to this non-canonical YXXØ-signal. This structure showed no significant difference compared to that of wild-type μ4. Both differential scanning fluorimetry and limited proteolysis analyses demonstrated that the D190A substitution rendered μ4 less stable, suggesting an explanation for its lower binding affinity to the APP signal. Finally, in contrast to overexpression of the D190A mutant, and acting in a dominant-negative manner, overexpression of μ4 with either a F255A or a R283D substitution at the non-canonical site halted APP transport at the Golgi apparatus. Together, our analyses support that the functional recognition of the non-canonical YXXØ-signal of APP is limited to the non

  2. Invertebrate and vertebrate class III myosins interact with MORN repeat-containing adaptor proteins.

    Directory of Open Access Journals (Sweden)

    Kirk L Mecklenburg

    Full Text Available In Drosophila photoreceptors, the NINAC-encoded myosin III is found in a complex with a small, MORN-repeat containing, protein Retinophilin (RTP. Expression of these two proteins in other cell types showed NINAC myosin III behavior is altered by RTP. NINAC deletion constructs were used to map the RTP binding site within the proximal tail domain of NINAC. In vertebrates, the RTP ortholog is MORN4. Co-precipitation experiments demonstrated that human MORN4 binds to human myosin IIIA (MYO3A. In COS7 cells, MORN4 and MYO3A, but not MORN4 and MYO3B, co-localize to actin rich filopodia extensions. Deletion analysis mapped the MORN4 binding to the proximal region of the MYO3A tail domain. MYO3A dependent MORN4 tip localization suggests that MYO3A functions as a motor that transports MORN4 to the filopodia tips and MORN4 may enhance MYO3A tip localization by tethering it to the plasma membrane at the protrusion tips. These results establish conserved features of the RTP/MORN4 family: they bind within the tail domain of myosin IIIs to control their behavior.

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

    DEFF Research Database (Denmark)

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

    2005-01-01

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

  4. Palmitoylation of protease-activated receptor-1 regulates adaptor protein complex-2 and -3 interaction with tyrosine-based motifs and endocytic sorting.

    Science.gov (United States)

    Canto, Isabel; Trejo, JoAnn

    2013-05-31

    Protease-activated receptor-1 (PAR1) is a G protein-coupled receptor for the coagulant protease thrombin. Thrombin binds to and cleaves the N terminus of PAR1, generating a new N terminus that functions as a tethered ligand that cannot diffuse away. In addition to rapid desensitization, PAR1 trafficking is critical for the regulation of cellular responses. PAR1 displays constitutive and agonist-induced internalization. Constitutive internalization of unactivated PAR1 is mediated by the clathrin adaptor protein complex-2 (AP-2), which binds to a distal tyrosine-based motif localized within the C-terminal tail (C-tail) domain. Once internalized, PAR1 is sorted from endosomes to lysosomes via AP-3 interaction with a second C-tail tyrosine motif proximal to the transmembrane domain. However, the regulatory processes that control adaptor protein recognition of PAR1 C-tail tyrosine-based motifs are not known. Here, we report that palmitoylation of PAR1 is critical for regulating proper utilization of tyrosine-based motifs and endocytic sorting. We show that PAR1 is basally palmitoylated at highly conserved C-tail cysteines. A palmitoylation-deficient PAR1 mutant is competent to signal and exhibits a marked increase in constitutive internalization and lysosomal degradation compared with wild type receptor. Intriguingly, enhanced constitutive internalization of PAR1 is mediated by AP-2 and requires the proximal tyrosine-based motif rather than the distal tyrosine motif used by wild type receptor. Moreover, palmitoylation-deficient PAR1 displays increased degradation that is mediated by AP-3. These findings suggest that palmitoylation of PAR1 regulates appropriate utilization of tyrosine-based motifs by adaptor proteins and endocytic trafficking, processes that are critical for maintaining appropriate expression of PAR1 at the cell surface. PMID:23580642

  5. The adaptor protein DCAF7 mediates the interaction of the adenovirus E1A oncoprotein with the protein kinases DYRK1A and HIPK2.

    Science.gov (United States)

    Glenewinkel, Florian; Cohen, Michael J; King, Cason R; Kaspar, Sophie; Bamberg-Lemper, Simone; Mymryk, Joe S; Becker, Walter

    2016-01-01

    DYRK1A is a constitutively active protein kinase that has a critical role in growth and development which functions by regulating cell proliferation, differentiation and survival. DCAF7 (also termed WDR68 or HAN11) is a cellular binding partner of DYRK1A and also regulates signalling by the protein kinase HIPK2. DCAF7 is an evolutionarily conserved protein with a single WD40 repeat domain and has no catalytic activity. We have defined a DCAF7 binding motif of 12 amino acids in the N-terminal domain of class 1 DYRKs that is functionally conserved in DYRK1 orthologs from Xenopus, Danio rerio and the slime mold Dictyostelium discoideum. A similar sequence was essential for DCAF7 binding to HIPK2, whereas the closely related HIPK1 family member did not bind DCAF7. Immunoprecipitation and pulldown experiments identified DCAF7 as an adaptor for the association of the adenovirus E1A protein with DYRK1A and HIPK2. Furthermore, DCAF7 was required for the hyperphosphorylation of E1A in DYRK1A or HIPK2 overexpressing cells. Our results characterize DCAF7 as a substrate recruiting subunit of DYRK1A and HIPK2 and suggest that it is required for the negative effect of DYRK1A on E1A-induced oncogenic transformation. PMID:27307198

  6. Phosphorylation of APP-CTF-AICD domains and interaction with adaptor proteins: signal transduction and/or transcriptional role--relevance for Alzheimer pathology.

    Science.gov (United States)

    Schettini, Gennaro; Govoni, Stefano; Racchi, Marco; Rodriguez, Guido

    2010-12-01

    In recent decades, the study of the amyloid precursor protein (APP) and of its proteolytic products carboxy terminal fragment (CTF), APP intracellular C-terminal domain (AICD) and amyloid beta has been mostly focussed on the role of APP as a producer of the toxic amyloid beta peptide. Here, we reconsider the role of APP suggesting, in a provocative way, the protein as a central player in a putative signalling pathway. We highlight the presence in the cytosolic tail of APP of the YENPTY motif which is typical of tyrosine kinase receptors, the phosphorylation of the tyrosine, serine and threonine residues, the kinases involved and the interaction with intracellular adaptor proteins. In particular, we examine the interaction with Shc and Grb2 regulators, which through the activation of Ras proteins elicit downstream signalling events such as the MAPK pathway. The review also addresses the interaction of APP, CTFs and AICD with other adaptor proteins and in particular with Fe65 for nuclear transcriptional activity and the importance of phosphorylation for sorting the secretases involved in the amyloidogenic or non-amyloidogenic pathways. We provide a novel perspective on Alzheimer's disease pathogenesis, focussing on the perturbation of the physiological activities of APP-CTFs and AICD as an alternative perspective from that which normally focuses on the accumulation of neurotoxic proteolytic fragments. PMID:21039524

  7. Involvement of β3A Subunit of Adaptor Protein-3 in Intracellular Trafficking of Receptor-like Protein Tyrosine Phosphatase PCP-2

    Institute of Scientific and Technical Information of China (English)

    Hui DONG; Hong YUAN; Weirong JIN; Yan SHEN; Xiaojing XU; Hongyang WANG

    2007-01-01

    PCP-2 is a human receptor-like protein tyrosine phosphatase and a member of the MAM domain family cloned in human pancreatic adenocarcinoma cells. Previous studies showed that PCP-2 directly interacted with β-catenin through the juxtamembrane domain, dephosphorylated β-catenin and played an important role in the regulation of cell adhesion. Recent study showed that PCP-2 was also involved in the repression of β-catenin-induced transcriptional activity. Here we describe the interactions of PCP-2 with the β3A subunit of adaptor protein (AP)-3 and sorting nexin (SNX) 3. These protein complexes were detected using the yeast two-hybrid assay with the juxtamembrane and membrane-proximal catalytic domain of PCP-2 as "bait". Both AP-3 and SNX3 are molecules involved in intracellular trafficking of membrane receptors. The association between the β3A subunit of AP-3 and PCP-2 was further confirmed in mammalian cells. Our results suggested a possible mechanism of intracellular trafficking of PCP-2 mediated by AP-3 and SNX3 which might participate in the regulation of PCP-2 functions.

  8. The Adaptor Protein Myd88 Is a Key Signaling Molecule in the Pathogenesis of Irinotecan-Induced Intestinal Mucositis.

    Directory of Open Access Journals (Sweden)

    Deysi V T Wong

    Full Text Available Intestinal mucositis is a common side effect of irinotecan-based anticancer regimens. Mucositis causes cell damage, bacterial/endotoxin translocation and production of cytokines including IL-1 and IL-18. These molecules and toll-like receptors (TLRs activate a common signaling pathway that involves the Myeloid Differentiation adaptor protein, MyD88, whose role in intestinal mucositis is unknown. Then, we evaluated the involvement of TLRs and MyD88 in the pathogenesis of irinotecan-induced intestinal mucositis. MyD88-, TLR2- or TLR9-knockout mice and C57BL/6 (WT mice were given either saline or irinotecan (75 mg/kg, i.p. for 4 days. On day 7, animal survival, diarrhea and bacteremia were assessed, and following euthanasia, samples of the ileum were obtained for morphometric analysis, myeloperoxidase (MPO assay and measurement of pro-inflammatory markers. Irinotecan reduced the animal survival (50% and induced a pronounced diarrhea, increased bacteremia, neutrophil accumulation in the intestinal tissue, intestinal damage and more than twofold increased expression of MyD88 (200%, TLR9 (400%, TRAF6 (236%, IL-1β (405%, IL-18 (365%, COX-2 (2,777% and NF-κB (245% in the WT animals when compared with saline-injected group (P<0.05. Genetic deletion of MyD88, TLR2 or TLR9 effectively controlled the signs of intestinal injury when compared with irinotecan-administered WT controls (P<0.05. In contrast to the MyD88-/- and TLR2-/- mice, the irinotecan-injected TLR9-/- mice showed a reduced survival, a marked diarrhea and an enhanced expression of IL-18 versus irinotecan-injected WT controls. Additionally, the expression of MyD88 was reduced in the TLR2-/- or TLR9-/- mice. This study shows a critical role of the MyD88-mediated TLR2 and TLR9 signaling in the pathogenesis of irinotecan-induced intestinal mucositis.

  9. The crucial role of the MyD88 adaptor protein in the inflammatory response induced by Bothrops atrox venom.

    Science.gov (United States)

    Moreira, Vanessa; Teixeira, Catarina; Borges da Silva, Henrique; D'Império Lima, Maria Regina; Dos-Santos, Maria Cristina

    2013-06-01

    Most snake accidents in North Brazil are attributed to Bothrops atrox, a snake species of the Viperidae family whose venom simultaneously induces local and systemic effects in the victims. The former are clinically more important than the latter, as they cause severe tissue lesions associated with strong inflammatory responses. Although several studies have shown that inflammatory mediators are produced in response to B. atrox venom (BaV), there is little information concerning the molecular pathways involved in innate immune system signaling. Myeloid differentiation factor 88 (MyD88) is an adaptor molecule responsible for transmitting intracellular signals from most toll-like receptors (TLRs) after they interact with pathogen-associated molecular patterns (PAMPs) or other stimuli such as endogenous damage-associated molecular patterns (DAMPs). The MyD88-dependent pathway leads to activation of transcription factors, which in turn induce synthesis of inflammatory mediators such as eicosanoids, cytokines and chemokines. The aim of this study was to investigate the involvement of MyD88 on the acute inflammatory response induced by BaV. Wild-type (WT) C57BL/6 mice and MyD88 knockout (MyD88(-/-)) mice were intraperitoneally injected with BaV. Compared to WT mice, MyD88(-/-) animals showed an impaired inflammatory response to BaV, with lower influx of polymorphonuclear and mononuclear cells to the peritoneal cavity. Furthermore, peritoneal leukocytes from BaV-injected MyD88(-/-) mice did not induce COX-2 or LTB4 protein expression and released low concentrations of PGE2. These mice also failed to produce Th1 and Th17 cytokines and CCL-2, but IL-10 levels were similar to those of BaV-injected WT mice. Our results indicate that MyD88 signaling is required for activation of the inflammatory response elicited by BaV, raising the possibility of developing new therapeutic targets to treat Bothrops sp. poisoning. PMID:23474268

  10. Impaired Lysosomal Integral Membrane Protein 2-dependent Peroxiredoxin 6 Delivery to Lamellar Bodies Accounts for Altered Alveolar Phospholipid Content in Adaptor Protein-3-deficient pearl Mice.

    Science.gov (United States)

    Kook, Seunghyi; Wang, Ping; Young, Lisa R; Schwake, Michael; Saftig, Paul; Weng, Xialian; Meng, Ying; Neculai, Dante; Marks, Michael S; Gonzales, Linda; Beers, Michael F; Guttentag, Susan

    2016-04-15

    The Hermansky Pudlak syndromes (HPS) constitute a family of disorders characterized by oculocutaneous albinism and bleeding diathesis, often associated with lethal lung fibrosis. HPS results from mutations in genes of membrane trafficking complexes that facilitate delivery of cargo to lysosome-related organelles. Among the affected lysosome-related organelles are lamellar bodies (LB) within alveolar type 2 cells (AT2) in which surfactant components are assembled, modified, and stored. AT2 from HPS patients and mouse models of HPS exhibit enlarged LB with increased phospholipid content, but the mechanism underlying these defects is unknown. We now show that AT2 in the pearl mouse model of HPS type 2 lacking the adaptor protein 3 complex (AP-3) fails to accumulate the soluble enzyme peroxiredoxin 6 (PRDX6) in LB. This defect reflects impaired AP-3-dependent trafficking of PRDX6 to LB, because pearl mouse AT2 cells harbor a normal total PRDX6 content. AP-3-dependent targeting of PRDX6 to LB requires the transmembrane protein LIMP-2/SCARB2, a known AP-3-dependent cargo protein that functions as a carrier for lysosomal proteins in other cell types. Depletion of LB PRDX6 in AP-3- or LIMP-2/SCARB2-deficient mice correlates with phospholipid accumulation in lamellar bodies and with defective intraluminal degradation of LB disaturated phosphatidylcholine. Furthermore, AP-3-dependent LB targeting is facilitated by protein/protein interaction between LIMP-2/SCARB2 and PRDX6 in vitro and in vivo Our data provide the first evidence for an AP-3-dependent cargo protein required for the maturation of LB in AT2 and suggest that the loss of PRDX6 activity contributes to the pathogenic changes in LB phospholipid homeostasis found HPS2 patients. PMID:26907692

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

    DEFF Research Database (Denmark)

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

    1996-01-01

    The serine protease thrombin activates G protein signaling systems that lead to Ras activation and, in certain cells, proliferation. Whereas the steps leading to Ras activation by G protein-coupled receptors are not well defined, the mechanisms of Ras activation by receptor tyrosine kinases have...... kinase activation, gene induction and cell growth. From these data, we conclude that Shc represents a crucial point of convergence between signaling pathways activated by receptor tyrosine kinases and G protein-coupled receptors....

  12. Analysis of Phosphorylation-dependent Protein Interactions of Adhesion and Degranulation Promoting Adaptor Protein (ADAP) Reveals Novel Interaction Partners Required for Chemokine-directed T cell Migration.

    Science.gov (United States)

    Kuropka, Benno; Witte, Amelie; Sticht, Jana; Waldt, Natalie; Majkut, Paul; Hackenberger, Christian P R; Schraven, Burkhart; Krause, Eberhard; Kliche, Stefanie; Freund, Christian

    2015-11-01

    Stimulation of T cells leads to distinct changes of their adhesive and migratory properties. Signal propagation from activated receptors to integrins depends on scaffolding proteins such as the adhesion and degranulation promoting adaptor protein (ADAP)(1). Here we have comprehensively investigated the phosphotyrosine interactome of ADAP in T cells and define known and novel interaction partners of functional relevance. While most phosphosites reside in unstructured regions of the protein, thereby defining classical SH2 domain interaction sites for master regulators of T cell signaling such as SLP76, Fyn-kinase, and NCK, other binding events depend on structural context. Interaction proteomics using different ADAP constructs comprising most of the known phosphotyrosine motifs as well as the structured domains confirm that a distinct set of proteins is attracted by pY571 of ADAP, including the ζ-chain-associated protein kinase of 70 kDa (ZAP70). The interaction of ADAP and ZAP70 is inducible upon stimulation either of the T cell receptor (TCR) or by chemokine. NMR spectroscopy reveals that the N-terminal SH2 domains within a ZAP70-tandem-SH2 construct is the major site of interaction with phosphorylated ADAP-hSH3(N) and microscale thermophoresis (MST) indicates an intermediate binding affinity (Kd = 2.3 μm). Interestingly, although T cell receptor dependent events such as T cell/antigen presenting cell (APC) conjugate formation and adhesion are not affected by mutation of Y571, migration of T cells along a chemokine gradient is compromised. Thus, although most phospho-sites in ADAP are linked to T cell receptor related functions we have identified a unique phosphotyrosine that is solely required for chemokine induced T cell behavior.

  13. The cell signaling adaptor protein EPS-8 is essential for C. elegans epidermal elongation and interacts with the ankyrin repeat protein VAB-19.

    Directory of Open Access Journals (Sweden)

    Mei Ding

    Full Text Available The epidermal cells of the C. elegans embryo undergo coordinated cell shape changes that result in the morphogenetic process of elongation. The cytoskeletal ankyrin repeat protein VAB-19 is required for cell shape changes and localizes to cell-matrix attachment structures. The molecular functions of VAB-19 in this process are obscure, as no previous interactors for VAB-19 have been described.In screens for VAB-19 binding proteins we identified the signaling adaptor EPS-8. Within C. elegans epidermal cells, EPS-8 and VAB-19 colocalize at cell-matrix attachment structures. The central domain of EPS-8 is necessary and sufficient for its interaction with VAB-19. eps-8 null mutants, like vab-19 mutants, are defective in epidermal elongation and in epidermal-muscle attachment. The eps-8 locus encodes two isoforms, EPS-8A and EPS-8B, that appear to act redundantly in epidermal elongation. The function of EPS-8 in epidermal development involves its N-terminal PTB and central domains, and is independent of its C-terminal SH3 and actin-binding domains. VAB-19 appears to act earlier in the biogenesis of attachment structures and may recruit EPS-8 to these structures.EPS-8 and VAB-19 define a novel pathway acting at cell-matrix attachments to regulate epithelial cell shape. This is the first report of a role for EPS-8 proteins in cell-matrix attachments. The existence of EPS-8B-like isoforms in Drosophila suggests this function of EPS-8 proteins could be conserved among other organisms.

  14. Structural basis for the recognition of the scaffold protein Frmpd4/Preso1 by the TPR domain of the adaptor protein LGN.

    Science.gov (United States)

    Takayanagi, Hiroki; Yuzawa, Satoru; Sumimoto, Hideki

    2015-02-01

    The adaptor protein LGN interacts via the N-terminal domain comprising eight tetratricopeptide-repeat (TPR) motifs with its partner proteins mInsc, NuMA, Frmpd1 and Frmpd4 in a mutually exclusive manner. Here, the crystal structure of the LGN TPR domain in complex with human Frmpd4 is described at 1.5 Å resolution. In the complex, the LGN-binding region of Frmpd4 (amino-acid residues 990-1011) adopts an extended structure that runs antiparallel to LGN along the concave surface of the superhelix formed by the TPR motifs. Comparison with the previously determined structures of the LGN-Frmpd1, LGN-mInsc and LGN-NuMA complexes reveals that these partner proteins interact with LGN TPR1-6 via a common core binding region with consensus sequence (E/Q)XEX4-5(E/D/Q)X1-2(K/R)X0-1(V/I). In contrast to Frmpd1, Frmpd4 makes additional contacts with LGN via regions N- and C-terminal to the core sequence. The N-terminal extension is replaced by a specific α-helix in mInsc, which drastically increases the direct contacts with LGN TPR7/8, consistent with the higher affinity of mInsc for LGN. A crystal structure of Frmpd4-bound LGN in an oxidized form is also reported, although oxidation does not appear to strongly affect the interaction with Frmpd4.

  15. 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.

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

    Directory of Open Access Journals (Sweden)

    А. V. Bazalii

    2015-10-01

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

  17. Crk adaptor protein-induced phosphorylation of Gab1 on tyrosine 307 via Src is important for organization of focal adhesions and enhanced cell migration

    Institute of Scientific and Technical Information of China (English)

    Takuya Watanabe; Masumi Tsuda; Yoshinori Makino; Tassos Konstantinou; Hiroshi Nishihara; Tokifumi Majima; Akio Minami; Stephan M Feller; Shinya Tanaka

    2009-01-01

    Upon growth factor stimulation, the scaffold protein, Gabl, is tyrosine phosphorylated and subsequently the adaptor protein, Crk, transmits signals from Gabl. We have previously shown that Crk overexpression, which is detectable in various human cancers, induces tyrosine phosphorylation of Gab1 without extraceilular stimuli. In the present study, the underlying mechanisms were further investigated. Mutational analyses of Crkll demonstrated that the SH2 domain, but not the SH3(N) or the regulatory Y221 residue of Crkll, is critical for the induction of Gabl-Y307 phosphorylation. SH2 mutation of Crkll also decreased the interaction with Gab1. In GST pull-down assay, Crk-SH2 bound to wild-type Gabl, whereas Crk-SH3(N) interacted with the Gabl mutant, which lacks the clus-tered tyrosine region (residues 242-410). Tyrosine phosphorylation of Gabl was induced by all Crk family proteins, but not other SH2-containing signalling adaptors. Src-family kinase inhibitor, PP2, abrogates Crk-induced tyrosine phosphorylations of Gabl. Y307 phosphorylation was undetectable in fibroblasts lacking Src, Yes, and Fyn, even upon overexpression of Crk, whereas cells lacking only Yes and Fyn still contained Gabl with phosphorylated Y307. Furthermore, Crk induced the phosphorylation of Src-Y416; accordingly the interaction between Crk and Csk was increased. The GabI-Y307F mutant failed to localize near the plasma membrane even upon HGF stimulation and decreased cell migration. Moreover, Gabl-Y307F disturbed the localization of Crk, FAK, and paxiilin, which are the typical components of focal adhesions. Taken together, these results indicate that Crk facilitates tyrosine phosphory-lation of Gabl-Y307 through Src, contributing to the organization of focal adhesions and enhanced cell migration, thereby possibly promoting human cancer development.

  18. RTK SLAP down: the emerging role of Src-like adaptor protein as a key player in receptor tyrosine kinase signaling.

    Science.gov (United States)

    Wybenga-Groot, Leanne E; McGlade, C Jane

    2015-02-01

    SLAP (Src like adaptor protein) contains adjacent Src homology 3 (SH3) and Src homology 2 (SH2) domains closely related in sequence to that of cytoplasmic Src family tyrosine kinases. Expressed most abundantly in the immune system, SLAP function has been predominantly studied in the context of lymphocyte signaling, where it functions in the Cbl dependent downregulation of antigen receptor signaling. However, accumulating evidence suggests that SLAP plays a role in the regulation of a broad range of membrane receptors including members of the receptor tyrosine kinase (RTK) family. In this review we highlight the role of SLAP in the ubiquitin dependent regulation of type III RTKs PDGFR, CSF-1R, KIT and Flt3, as well as Eph family RTKs. SLAP appears to bind activated type III and Eph RTKs via a conserved autophosphorylated juxtamembrane tyrosine motif in an SH2-dependent manner, suggesting that SLAP is important in regulating RTK signaling.

  19. Differential association of the Na+/H+ exchanger regulatory factor (NHERF) family of adaptor proteins with the raft- and the non-raft brush border membrane fractions of NHE3

    NARCIS (Netherlands)

    A. Sultan (Ayesha); M. Luo (Ma); Q. Yu (Qingbao); B. Riederer (Beat Michel); W. Xia (Weiliang); M. Chen (Mingmin); S. Lissner (Simone); J.E. Gessner (Johannes); M. Donowitz (Mark); C. Chris Yun (C.); H. deJonge (Hugo); G. Lamprecht (Georg); U. Seidler (Ursula)

    2013-01-01

    textabstractBackground/Aims: Trafficking, brush border membrane (BBM) retention, and signal-specific regulation of the Na+/H+ exchanger NHE3 is regulated by the Na+/H+ Exchanger Regulatory Factor (NHERF) family of PDZ-adaptor proteins, which enable the formation of multiprotein complexes. It is uncl

  20. Spectral affinity in protein networks

    OpenAIRE

    Teng Shang-Hua; Voevodski Konstantin; Xia Yu

    2009-01-01

    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...

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

    Science.gov (United States)

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

    2016-08-15

    The mitogen-activated protein kinase (MAPK) cascade is a highly conserved signaling module composed of MAPK kinase kinases (MAPKKKs), MAPK kinases (MAPKK) and MAPKs. The MAPKKK Mkh1 is an initiating kinase in Pmk1 MAPK signaling, which regulates cell integrity in fission yeast (Schizosaccharomyces pombe). Our genetic screen for regulators of Pmk1 signaling identified Shk1 kinase binding protein 5 (Skb5), an SH3-domain-containing adaptor protein. Here, we show that Skb5 serves as an inhibitor of Pmk1 MAPK signaling activation by downregulating Mkh1 localization to cell tips through its interaction with the SH3 domain. Consistent with this, the Mkh1(3PA) mutant protein, with impaired Skb5 binding, remained in the cell tips, even when Skb5 was overproduced. Intriguingly, Skb5 needs Mkh1 to localize to the growing ends as Mkh1 deletion and disruption of Mkh1 binding impairs Skb5 localization. Deletion of Pck2, an upstream activator of Mkh1, impaired the cell tip localization of Mkh1 and Skb5 as well as the Mkh1-Skb5 interaction. Interestingly, both Pck2 and Mkh1 localized to the cell tips at the G1/S phase, which coincided with Pmk1 MAPK activation. Taken together, Mkh1 localization to cell tips is important for transmitting upstream signaling to Pmk1, and Skb5 spatially regulates this process. PMID:27451356

  2. 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

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

    International Nuclear Information System (INIS)

    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 (HCO3-) exchange at the basolateral membrane of kidney α-intercalated cells. Impaired trafficking of kAE1 leads to defect of the Cl-/HCO3- 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.

  4. 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)

    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

  5. Involvement of Grb2 adaptor protein in nucleophosmin-anaplastic lymphoma kinase (NPM-ALK)-mediated signaling and anaplastic large cell lymphoma growth.

    Science.gov (United States)

    Riera, Ludovica; Lasorsa, Elena; Ambrogio, Chiara; Surrenti, Nadia; Voena, Claudia; Chiarle, Roberto

    2010-08-20

    Most anaplastic large cell lymphomas (ALCL) express oncogenic fusion proteins derived from chromosomal translocations or inversions of the anaplastic lymphoma kinase (ALK) gene. Frequently ALCL carry the t(2;5) translocation, which fuses the ALK gene to the nucleophosmin (NPM1) gene. The transforming activity mediated by NPM-ALK fusion induces different pathways that control proliferation and survival of lymphoma cells. Grb2 is an adaptor protein thought to play an important role in ALK-mediated transformation, but its interaction with NPM-ALK, as well as its function in regulating ALCL signaling pathways and cell growth, has never been elucidated. Here we show that active NPM-ALK, but not a kinase-dead mutant, bound and induced Grb2 phosphorylation in tyrosine 160. An intact SH3 domain at the C terminus of Grb2 was required for Tyr(160) phosphorylation. Furthermore, Grb2 did not bind to a single region but rather to different regions of NPM-ALK, mainly Tyr(152-156), Tyr(567), and a proline-rich region, Pro(415-417). Finally, shRNA knockdown experiments showed that Grb2 regulates primarily the NPM-ALK-mediated phosphorylation of SHP2 and plays a key role in ALCL cell growth.

  6. 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.

  7. Src-Like adaptor protein (SLAP) binds to the receptor tyrosine kinase Flt3 and modulates receptor stability and downstream signaling.

    Science.gov (United States)

    Kazi, Julhash U; Rönnstrand, Lars

    2012-01-01

    Fms-like tyrosine kinase 3 (Flt3) is an important growth factor receptor in hematopoiesis. Gain-of-function mutations of the receptor contribute to the transformation of acute myeloid leukemia (AML). Src-like adaptor protein (SLAP) is an interaction partner of the E3 ubiquitin ligase Cbl that can regulate receptor tyrosine kinases-mediated signal transduction. In this study, we analyzed the role of SLAP in signal transduction downstream of the type III receptor tyrosine kinase Flt3. The results show that upon ligand stimulation SLAP stably associates with Flt3 through multiple phosphotyrosine residues in Flt3. SLAP constitutively interacts with oncogenic Flt3-ITD and co-localizes with Flt3 near the cell membrane. This association initiates Cbl-dependent receptor ubiquitination and degradation. Depletion of SLAP expression by shRNA in Flt3-transfected Ba/F3 cells resulted in a weaker activation of FL-induced PI3K-Akt and MAPK signaling. Meta-analysis of microarray data from patient samples suggests that SLAP mRNA is differentially expressed in different cancers and its expression was significantly increased in patients carrying the Flt3-ITD mutation. Thus, our data suggest a novel role of SLAP in different cancers and in modulation of receptor tyrosine kinase signaling apart from its conventional role in regulation of receptor stability.

  8. Src-Like adaptor protein (SLAP binds to the receptor tyrosine kinase Flt3 and modulates receptor stability and downstream signaling.

    Directory of Open Access Journals (Sweden)

    Julhash U Kazi

    Full Text Available Fms-like tyrosine kinase 3 (Flt3 is an important growth factor receptor in hematopoiesis. Gain-of-function mutations of the receptor contribute to the transformation of acute myeloid leukemia (AML. Src-like adaptor protein (SLAP is an interaction partner of the E3 ubiquitin ligase Cbl that can regulate receptor tyrosine kinases-mediated signal transduction. In this study, we analyzed the role of SLAP in signal transduction downstream of the type III receptor tyrosine kinase Flt3. The results show that upon ligand stimulation SLAP stably associates with Flt3 through multiple phosphotyrosine residues in Flt3. SLAP constitutively interacts with oncogenic Flt3-ITD and co-localizes with Flt3 near the cell membrane. This association initiates Cbl-dependent receptor ubiquitination and degradation. Depletion of SLAP expression by shRNA in Flt3-transfected Ba/F3 cells resulted in a weaker activation of FL-induced PI3K-Akt and MAPK signaling. Meta-analysis of microarray data from patient samples suggests that SLAP mRNA is differentially expressed in different cancers and its expression was significantly increased in patients carrying the Flt3-ITD mutation. Thus, our data suggest a novel role of SLAP in different cancers and in modulation of receptor tyrosine kinase signaling apart from its conventional role in regulation of receptor stability.

  9. Activation of EphA receptors mediates the recruitment of the adaptor protein Slap, contributing to the downregulation of N-methyl-D-aspartate receptors.

    Science.gov (United States)

    Semerdjieva, Sophia; Abdul-Razak, Hayder H; Salim, Sharifah S; Yáñez-Muñoz, Rafael J; Chen, Philip E; Tarabykin, Victor; Alifragis, Pavlos

    2013-04-01

    Regulation of the activity of N-methyl-d-aspartate receptors (NMDARs) at glutamatergic synapses is essential for certain forms of synaptic plasticity underlying learning and memory and is also associated with neurotoxicity and neurodegenerative diseases. In this report, we investigate the role of Src-like adaptor protein (Slap) in NMDA receptor signaling. We present data showing that in dissociated neuronal cultures, activation of ephrin (Eph) receptors by chimeric preclustered eph-Fc ligands leads to recruitment of Slap and NMDA receptors at the sites of Eph receptor activation. Interestingly, our data suggest that prolonged activation of EphA receptors is as efficient in recruiting Slap and NMDA receptors as prolonged activation of EphB receptors. Using established heterologous systems, we examined whether Slap is an integral part of NMDA receptor signaling. Our results showed that Slap does not alter baseline activity of NMDA receptors and does not affect Src-dependent potentiation of NMDA receptor currents in Xenopus oocytes. We also demonstrate that Slap reduces excitotoxic cell death triggered by activation of NMDARs in HEK293 cells. Finally, we present evidence showing reduced levels of NMDA receptors in the presence of Slap occurring in an activity-dependent manner, suggesting that Slap is part of a mechanism that homeostatically modulates the levels of NMDA receptors.

  10. Increased abundance of the adaptor protein containing pleckstrin homology domain, phosphotyrosine binding domain and leucine zipper motif (APPL1) in patients with obesity and type 2 diabetes: evidence for altered adiponectin signalling

    OpenAIRE

    Holmes, R.M.; Yi, Z; De Filippis, E.; Berria, R.; S. Shahani; P. Sathyanarayana; Sherman, V.; K. Fujiwara; Meyer, C.; Christ-Roberts, C.; Hwang, H; Finlayson, J.; Dong, L. Q.; Mandarino, L. J.; Bajaj, M.

    2011-01-01

    Aims/hypothesis The adiponectin signalling pathway is largely unknown, but recently the adaptor protein containing pleckstrin homology domain, phosphotyrosine binding domain and leucine zipper motif (APPL1), has been shown to interact directly with adiponectin receptor (ADIPOR)1. APPL1 is present in C2C12 myoblasts and mouse skeletal muscle, but its presence in human skeletal muscle has not been investigated. Methods Samples from type 2 diabetic, and lean and non-diabetic obese participants w...

  11. The interaction of the cellular export adaptor protein Aly/REF with ICP27 contributes to the efficiency of herpes simplex virus 1 mRNA export.

    Science.gov (United States)

    Tian, Xiaochen; Devi-Rao, Gayathri; Golovanov, Alexander P; Sandri-Goldin, Rozanne M

    2013-07-01

    Herpes simplex virus 1 (HSV-1) protein ICP27 enables viral mRNA export by accessing the cellular mRNA export receptor TAP/NXF, which guides mRNA through the nuclear pore complex. ICP27 binds viral mRNAs and interacts with TAP/NXF, providing a link to the cellular mRNA export pathway. ICP27 also interacts with the mRNA export adaptor protein Aly/REF, which binds cellular mRNAs and also interacts with TAP/NXF. Studies using small interfering RNA (siRNA) knockdown indicated that Aly/REF is not required for cellular mRNA export, and similar knockdown studies during HSV-1 infection led us to conclude that Aly/REF may be dispensable for viral RNA export. Recently, the structural basis of the interaction of ICP27 with Aly/REF was elucidated at atomic resolution, and it was shown that three ICP27 residues, W105, R107, and L108, interface with the RNA recognition motif (RRM) domain of Aly/REF. Here, to determine the role the interaction of ICP27 and Aly/REF plays during infection, these residues were mutated to alanine, and a recombinant virus, WRL-A, was constructed. Virus production was reduced about 10-fold during WRL-A infection, and export of ICP27 protein and most viral mRNAs was less efficient. We conclude that interaction of ICP27 with Aly/REF contributes to efficient viral mRNA export.

  12. Protease-activated Receptor-4 Signaling and Trafficking Is Regulated by the Clathrin Adaptor Protein Complex-2 Independent of β-Arrestins.

    Science.gov (United States)

    Smith, Thomas H; Coronel, Luisa J; Li, Julia G; Dores, Michael R; Nieman, Marvin T; Trejo, JoAnn

    2016-08-26

    Protease-activated receptor-4 (PAR4) is a G protein-coupled receptor (GPCR) for thrombin and is proteolytically activated, similar to the prototypical PAR1. Due to the irreversible activation of PAR1, receptor trafficking is intimately linked to signal regulation. However, unlike PAR1, the mechanisms that control PAR4 trafficking are not known. Here, we sought to define the mechanisms that control PAR4 trafficking and signaling. In HeLa cells depleted of clathrin by siRNA, activated PAR4 failed to internalize. Consistent with clathrin-mediated endocytosis, expression of a dynamin dominant-negative K44A mutant also blocked activated PAR4 internalization. However, unlike most GPCRs, PAR4 internalization occurred independently of β-arrestins and the receptor's C-tail domain. Rather, we discovered a highly conserved tyrosine-based motif in the third intracellular loop of PAR4 and found that the clathrin adaptor protein complex-2 (AP-2) is important for internalization. Depletion of AP-2 inhibited PAR4 internalization induced by agonist. In addition, mutation of the critical residues of the tyrosine-based motif disrupted agonist-induced PAR4 internalization. Using Dami megakaryocytic cells, we confirmed that AP-2 is required for agonist-induced internalization of endogenous PAR4. Moreover, inhibition of activated PAR4 internalization enhanced ERK1/2 signaling, whereas Akt signaling was markedly diminished. These findings indicate that activated PAR4 internalization requires AP-2 and a tyrosine-based motif and occurs independent of β-arrestins, unlike most classical GPCRs. Moreover, these findings are the first to show that internalization of activated PAR4 is linked to proper ERK1/2 and Akt activation. PMID:27402844

  13. Spectral affinity in protein networks

    Directory of Open Access Journals (Sweden)

    Teng Shang-Hua

    2009-11-01

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

  14. Distinct in vitro interaction pattern of dopamine receptor subtypes with adaptor proteins involved in post-endocytotic receptor targeting

    DEFF Research Database (Denmark)

    Heydorn, Arne; Søndergaard, Birgitte P; Hadrup, Niels;

    2004-01-01

    The mechanisms underlying targeted sorting of endocytosed receptors for recycling to the plasma membrane or degradation in lysosomes are poorly understood. In this report, the C-terminal tails of the five dopamine receptors (D1-D5) were expressed as glutathione S-transferase (GST) fusion proteins...

  15. SmShb, the SH2-Containing Adaptor Protein B of Schistosoma mansoni Regulates Venus Kinase Receptor Signaling Pathways

    Science.gov (United States)

    Morel, Marion; Vanderstraete, Mathieu; Cailliau, Katia; Hahnel, Steffen; Grevelding, Christoph G.; Dissous, Colette

    2016-01-01

    Venus kinase receptors (VKRs) are invertebrate receptor tyrosine kinases (RTKs) formed by an extracellular Venus Fly Trap (VFT) ligand binding domain associated via a transmembrane domain with an intracellular tyrosine kinase (TK) domain. Schistosoma mansoni VKRs, SmVKR1 and SmVKR2, are both implicated in reproductive activities of the parasite. In this work, we show that the SH2 domain-containing protein SmShb is a partner of the phosphorylated form of SmVKR1. Expression of these proteins in Xenopus oocytes allowed us to demonstrate that the SH2 domain of SmShb interacts with the phosphotyrosine residue (pY979) located in the juxtamembrane region of SmVKR1. This interaction leads to phosphorylation of SmShb on tyrosines and promotes SmVKR1 signaling towards the JNK pathway. SmShb transcripts are expressed in all parasite stages and they were found in ovary and testes of adult worms, suggesting a possible colocalization of SmShb and SmVKR1 proteins. Silencing of SmShb in adult S. mansoni resulted in an accumulation of mature sperm in testes, indicating a possible role of SmShb in gametogenesis. PMID:27636711

  16. SmShb, the SH2-Containing Adaptor Protein B of Schistosoma mansoni Regulates Venus Kinase Receptor Signaling Pathways.

    Science.gov (United States)

    Morel, Marion; Vanderstraete, Mathieu; Cailliau, Katia; Hahnel, Steffen; Grevelding, Christoph G; Dissous, Colette

    2016-01-01

    Venus kinase receptors (VKRs) are invertebrate receptor tyrosine kinases (RTKs) formed by an extracellular Venus Fly Trap (VFT) ligand binding domain associated via a transmembrane domain with an intracellular tyrosine kinase (TK) domain. Schistosoma mansoni VKRs, SmVKR1 and SmVKR2, are both implicated in reproductive activities of the parasite. In this work, we show that the SH2 domain-containing protein SmShb is a partner of the phosphorylated form of SmVKR1. Expression of these proteins in Xenopus oocytes allowed us to demonstrate that the SH2 domain of SmShb interacts with the phosphotyrosine residue (pY979) located in the juxtamembrane region of SmVKR1. This interaction leads to phosphorylation of SmShb on tyrosines and promotes SmVKR1 signaling towards the JNK pathway. SmShb transcripts are expressed in all parasite stages and they were found in ovary and testes of adult worms, suggesting a possible colocalization of SmShb and SmVKR1 proteins. Silencing of SmShb in adult S. mansoni resulted in an accumulation of mature sperm in testes, indicating a possible role of SmShb in gametogenesis.

  17. The Mu subunit of Plasmodium falciparum clathrin-associated adaptor protein 2 modulates in vitro parasite response to artemisinin and quinine.

    Science.gov (United States)

    Henriques, Gisela; van Schalkwyk, Donelly A; Burrow, Rebekah; Warhurst, David C; Thompson, Eloise; Baker, David A; Fidock, David A; Hallett, Rachel; Flueck, Christian; Sutherland, Colin J

    2015-05-01

    The emergence of drug-resistant parasites is a serious threat faced by malaria control programs. Understanding the genetic basis of resistance is critical to the success of treatment and intervention strategies. A novel locus associated with antimalarial resistance, ap2-mu (encoding the mu chain of the adaptor protein 2 [AP2] complex), was recently identified in studies on the rodent malaria parasite Plasmodium chabaudi (pcap2-mu). Furthermore, analysis in Kenyan malaria patients of polymorphisms in the Plasmodium falciparum ap2-mu homologue, pfap2-mu, found evidence that differences in the amino acid encoded by codon 160 are associated with enhanced parasite survival in vivo following combination treatments which included artemisinin derivatives. Here, we characterize the role of pfap2-mu in mediating the in vitro antimalarial drug response of P. falciparum by generating transgenic parasites constitutively expressing codon 160 encoding either the wild-type Ser (Ser160) or the Asn mutant (160Asn) form of pfap2-mu. Transgenic parasites carrying the pfap2-mu 160Asn allele were significantly less sensitive to dihydroartemisinin using a standard 48-h in vitro test, providing direct evidence of an altered parasite response to artemisinin. Our data also provide evidence that pfap2-mu variants can modulate parasite sensitivity to quinine. No evidence was found that pfap2-mu variants contribute to the slow-clearance phenotype exhibited by P. falciparum in Cambodian patients treated with artesunate monotherapy. These findings provide compelling evidence that pfap2-mu can modulate P. falciparum responses to multiple drugs. We propose that this gene should be evaluated further as a potential molecular marker of antimalarial resistance.

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

    Science.gov (United States)

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

    2014-12-01

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

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

    DEFF Research Database (Denmark)

    Køhler, Julie Bonne

    and the specific molecular interactions and sequence of events linking sumoylation, ubiquitylation and substrate degradation, has been largely uncovered. Using the fission yeast model organism I here present evidence for a role of the Ufd1 (ubiquitinfusion degradation 1) protein, and by extension of the Cdc48-Ufd1...... other downstream fates. My work provides insight into how Cdc48-Ufd1-Npl4 also contributes to the processing of SUMO conjugates and suggests that at least some of these activities are coordinated with STUbL function. To gain insight into the sumoylated species regulated by Ufd1 and/or by STUbLs, I made......-Npl4 activities are coupled to dynamically regulate cellular processes....

  20. A combined LDL receptor/LDL receptor adaptor protein 1 mutation as the cause for severe familial hypercholesterolemia.

    Science.gov (United States)

    Soufi, Muhidien; Rust, Stephan; Walter, Michael; Schaefer, Juergen R

    2013-05-25

    Familial hypercholesterolemia (FH) results from impaired catabolism of plasma low density lipoproteins (LDL), thus leading to high cholesterol, atherosclerosis, and a high risk of premature myocardial infarction. FH is commonly caused by defects of the LDL receptor or its main ligand apoB, together mediating cellular uptake and clearance of plasma LDL. In some cases FH is inherited by mutations in the genes of PCSK9 and LDLRAP1 (ARH) in a dominant or recessive trait. The encoded proteins are required for LDL receptor stability and internalization within the LDLR pathway. To detect the underlying genetic defect in a family of Turkish descent showing unregular inheritance of severe FH, we screened the four candidate genes by denaturing gradient gel electrophoresis (DGGE) mutation analysis. We identified different combinatory mixtures of LDLR- and LDLRAP1-gene defects as the cause for severe familial hypercholesterolemia in this family. We also show for the first time that a heterozygous LDLR mutation combined with a homozygous LDLRAP1 mutation produces a more severe hypercholesterolemia phenotype in the same family than a homozygous LDLR mutation alone. PMID:23510778

  1. A Network Synthesis Model for Generating Protein Interaction Network Families

    OpenAIRE

    Sayed Mohammad Ebrahim Sahraeian; Byung-Jun Yoon

    2012-01-01

    In this work, we introduce a novel network synthesis model that can generate families of evolutionarily related synthetic protein-protein interaction (PPI) networks. Given an ancestral network, the proposed model generates the network family according to a hypothetical phylogenetic tree, where the descendant networks are obtained through duplication and divergence of their ancestors, followed by network growth using network evolution models. We demonstrate that this network synthesis model ca...

  2. Controlling allosteric networks in proteins

    Science.gov (United States)

    Dokholyan, Nikolay

    2013-03-01

    We present a novel methodology based on graph theory and discrete molecular dynamics simulations for delineating allosteric pathways in proteins. We use this methodology to uncover the structural mechanisms responsible for coupling of distal sites on proteins and utilize it for allosteric modulation of proteins. We will present examples where inference of allosteric networks and its rewiring allows us to ``rescue'' cystic fibrosis transmembrane conductance regulator (CFTR), a protein associated with fatal genetic disease cystic fibrosis. We also use our methodology to control protein function allosterically. We design a novel protein domain that can be inserted into identified allosteric site of target protein. Using a drug that binds to our domain, we alter the function of the target protein. We successfully tested this methodology in vitro, in living cells and in zebrafish. We further demonstrate transferability of our allosteric modulation methodology to other systems and extend it to become ligh-activatable.

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

    Directory of Open Access Journals (Sweden)

    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

  4. Protein evolution on a human signaling network

    OpenAIRE

    Purisima Enrico O; Cui Qinghua; Wang Edwin

    2009-01-01

    Abstract Background The architectural structure of cellular networks provides a framework for innovations as well as constraints for protein evolution. This issue has previously been studied extensively by analyzing protein interaction networks. However, it is unclear how signaling networks influence and constrain protein evolution and conversely, how protein evolution modifies and shapes the functional consequences of signaling networks. In this study, we constructed a human signaling networ...

  5. The Clathrin Adaptor AP-1A Mediates Basolateral Polarity

    OpenAIRE

    Gravotta, Diego; Carvajal-Gonzalez, Jose Maria; Mattera, Rafael; Deborde, Sylvie; Banfelder, Jason R.; Bonifacino, Juan S.; Rodriguez-Boulan, Enrique

    2012-01-01

    Clathrin and the epithelial-specific clathrin adaptor AP-1B mediate basolateral trafficking in epithelia. However, several epithelia lack AP-1B and mice knocked-out for AP-1B are viable, suggesting the existence of additional mechanisms that control basolateral polarity. Here, we demonstrate a distinct role of the ubiquitous clathrin adaptor AP-1A in basolateral protein sorting. Knock-down of AP-1A causes missorting of basolateral proteins in MDCK cells but only after knock-down of AP-1B, sug...

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

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    Marcos Rodrigo Alborghetti

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

  7. Preferential attachment in the protein network evolution

    OpenAIRE

    Eisenberg, Eli; Levanon, Erez Y.

    2003-01-01

    The Saccharomyces cerevisiae protein-protein interaction map, as well as many natural and man-made networks, shares the scale-free topology. The preferential attachment model was suggested as a generic network evolution model that yields this universal topology. However, it is not clear that the model assumptions hold for the protein interaction network. Using a cross genome comparison we show that (a) the older a protein, the better connected it is, and (b) The number of interactions a prote...

  8. The influenza virus protein PB1-F2 inhibits the induction of type I interferon at the level of the MAVS adaptor protein.

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    Zsuzsanna T Varga

    2011-06-01

    Full Text Available PB1-F2 is a 90 amino acid protein that is expressed from the +1 open reading frame in the PB1 gene of some influenza A viruses and has been shown to contribute to viral pathogenicity. Notably, a serine at position 66 (66S in PB1-F2 is known to increase virulence compared to an isogenic virus with an asparagine (66N at this position. Recently, we found that an influenza virus expressing PB1-F2 N66S suppresses interferon (IFN-stimulated genes in mice. To characterize this phenomenon, we employed several in vitro assays. Overexpression of the A/Puerto Rico/8/1934 (PR8 PB1-F2 protein in 293T cells decreased RIG-I mediated activation of an IFN-β reporter and secretion of IFN as determined by bioassay. Of note, the PB1-F2 N66S protein showed enhanced IFN antagonism activity compared to PB1-F2 wildtype. Similar observations were found in the context of viral infection with a PR8 PB1-F2 N66S virus. To understand the relationship between NS1, a previously described influenza virus protein involved in suppression of IFN synthesis, and PB1-F2, we investigated the induction of IFN when NS1 and PB1-F2 were co-expressed in an in vitro transfection system. In this assay we found that PB1-F2 N66S further reduced IFN induction in the presence of NS1. By inducing the IFN-β reporter at different levels in the signaling cascade, we found that PB1-F2 inhibited IFN production at the level of the mitochondrial antiviral signaling protein (MAVS. Furthermore, immunofluorescence studies revealed that PB1-F2 co-localizes with MAVS. In summary, we have characterized the anti-interferon function of PB1-F2 and we suggest that this activity contributes to the enhanced pathogenicity seen with PB1-F2 N66S- expressing influenza viruses.

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

    OpenAIRE

    Yang Zhihao; Lin Hongfei; Xu Bo

    2011-01-01

    Abstract Background Protein complexes can be identified from the protein interaction networks derived from experimental data sets. However, these analyses are challenging because of the presence of unreliable interactions and the complex connectivity of the network. The integration of protein-protein interactions with the data from other sources can be leveraged for improving the effectiveness of protein complexes detection algorithms. Methods We have developed novel semantic similarity metho...

  10. Deducing topology of protein-protein interaction networks from experimentally measured sub-networks

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    MacLellan W Robb

    2008-07-01

    Full Text Available Abstract Background Protein-protein interaction networks are commonly sampled using yeast two hybrid approaches. However, whether topological information reaped from these experimentally-measured sub-networks can be extrapolated to complete protein-protein interaction networks is unclear. Results By analyzing various experimental protein-protein interaction datasets, we found that they are not random samples of the parent networks. Based on the experimental bait-prey behaviors, our computer simulations show that these non-random sampling features may affect the topological information. We tested the hypothesis that a core sub-network exists within the experimentally sampled network that better maintains the topological characteristics of the parent protein-protein interaction network. We developed a method to filter the experimentally sampled network to result in a core sub-network that more accurately reflects the topology of the parent network. These findings have fundamental implications for large-scale protein interaction studies and for our understanding of the behavior of cellular networks. Conclusion The topological information from experimental measured networks network as is may not be the correct source for topological information about the parent protein-protein interaction network. We define a core sub-network that more accurately reflects the topology of the parent network.

  11. Hub Promiscuity in Protein-Protein Interaction Networks

    OpenAIRE

    Haruki Nakamura; Kengo Kinoshita; Ashwini Patil

    2010-01-01

    Hubs are proteins with a large number of interactions in a protein-protein interaction network. They are the principal agents in the interaction network and affect its function and stability. Their specific recognition of many different protein partners is of great interest from the structural viewpoint. Over the last few years, the structural properties of hubs have been extensively studied. We review the currently known features that are particular to hubs, possibly affecting their binding ...

  12. Geometric De-noising of Protein-Protein Interaction Networks

    OpenAIRE

    Kuchaiev, Oleksii; Rasajski, Marija; Higham, Desmond J.; Przul, Natasa; Przytycka, Teresa Maria

    2009-01-01

    Understanding complex networks of protein-protein interactions (PPIs) is one of the foremost challenges of the post-genomic era. Due to the recent advances in experimental bio-technology, including yeast-2-hybrid (Y2H), tandem affinity purification (TAP) and other high-throughput methods for protein-protein interaction (PPI) detection, huge amounts of PPI network data are becoming available. Of major concern, however, are the levels of noise and incompleteness. For example, for Y2H screens, i...

  13. Protein interaction networks from literature mining

    Science.gov (United States)

    Ihara, Sigeo

    2005-03-01

    The ability to accurately predict and understand physiological changes in the biological network system in response to disease or drug therapeutics is of crucial importance in life science. The extensive amount of gene expression data generated from even a single microarray experiment often proves difficult to fully interpret and comprehend the biological significance. An increasing knowledge of protein interactions stored in the PubMed database, as well as the advancement of natural language processing, however, makes it possible to construct protein interaction networks from the gene expression information that are essential for understanding the biological meaning. From the in house literature mining system we have developed, the protein interaction network for humans was constructed. By analysis based on the graph-theoretical characterization of the total interaction network in literature, we found that the network is scale-free and semantic long-ranged interactions (i.e. inhibit, induce) between proteins dominate in the total interaction network, reducing the degree exponent. Interaction networks generated based on scientific text in which the interaction event is ambiguously described result in disconnected networks. In contrast interaction networks based on text in which the interaction events are clearly stated result in strongly connected networks. The results of protein-protein interaction networks obtained in real applications from microarray experiments are discussed: For example, comparisons of the gene expression data indicative of either a good or a poor prognosis for acute lymphoblastic leukemia with MLL rearrangements, using our system, showed newly discovered signaling cross-talk.

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

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    Yang Zhihao

    2011-10-01

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

  15. How do oncoprotein mutations rewire protein-protein interaction networks?

    Science.gov (United States)

    Bowler, Emily H; Wang, Zhenghe; Ewing, Rob M

    2015-01-01

    The acquisition of mutations that activate oncogenes or inactivate tumor suppressors is a primary feature of most cancers. Mutations that directly alter protein sequence and structure drive the development of tumors through aberrant expression and modification of proteins, in many cases directly impacting components of signal transduction pathways and cellular architecture. Cancer-associated mutations may have direct or indirect effects on proteins and their interactions and while the effects of mutations on signaling pathways have been widely studied, how mutations alter underlying protein-protein interaction networks is much less well understood. Systematic mapping of oncoprotein protein interactions using proteomics techniques as well as computational network analyses is revealing how oncoprotein mutations perturb protein-protein interaction networks and drive the cancer phenotype. PMID:26325016

  16. Identifying hubs in protein interaction networks.

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    Ravishankar R Vallabhajosyula

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

  17. From networks of protein interactions to networks of functional dependencies

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    Luciani Davide

    2012-05-01

    Full Text Available Abstract Background As protein-protein interactions connect proteins that participate in either the same or different functions, networks of interacting and functionally annotated proteins can be converted into process graphs of inter-dependent function nodes (each node corresponding to interacting proteins with the same functional annotation. However, as proteins have multiple annotations, the process graph is non-redundant, if only proteins participating directly in a given function are included in the related function node. Results Reasoning that topological features (e.g., clusters of highly inter-connected proteins might help approaching structured and non-redundant understanding of molecular function, an algorithm was developed that prioritizes inclusion of proteins into the function nodes that best overlap protein clusters. Specifically, the algorithm identifies function nodes (and their mutual relations, based on the topological analysis of a protein interaction network, which can be related to various biological domains, such as cellular components (e.g., peroxisome and cellular bud or biological processes (e.g., cell budding of the model organism S. cerevisiae. Conclusions The method we have described allows converting a protein interaction network into a non-redundant process graph of inter-dependent function nodes. The examples we have described show that the resulting graph allows researchers to formulate testable hypotheses about dependencies among functions and the underlying mechanisms.

  18. The RA domain of Ste50 adaptor protein is required for delivery of Ste11 to the plasma membrane in the filamentous growth signaling pathway of the yeast Saccharomyces cerevisiae.

    Science.gov (United States)

    Truckses, Dagmar M; Bloomekatz, Joshua E; Thorner, Jeremy

    2006-02-01

    In Saccharomyces cerevisiae, pheromone response requires Ste5 scaffold protein, which ensures efficient G-protein-dependent recruitment of mitogen-activated protein kinase (MAPK) cascade components Ste11 (MAPK kinase kinase), Ste7 (MAPK kinase), and Fus3 (MAPK) to the plasma membrane for activation by Ste20 protein kinase. Ste20, which phosphorylates Ste11 to initiate signaling, is activated by binding to Cdc42 GTPase (membrane anchored via its C-terminal geranylgeranylation). Less clear is how activated and membrane-localized Ste20 contacts Ste11 to trigger invasive growth signaling, which also requires Ste7 and the MAPK Kss1, but not Ste5. Ste50 protein associates constitutively via an N-terminal sterile-alpha motif domain with Ste11, and this interaction is required for optimal invasive growth and hyperosmotic stress (high-osmolarity glycerol [HOG]) signaling but has a lesser role in pheromone response. We show that a conserved C-terminal, so-called "Ras association" (RA) domain in Ste50 is also essential for invasive growth and HOG signaling in vivo. In vitro the Ste50 RA domain is not able to associate with Ras2, but it does associate with Cdc42 and binds to a different face than does Ste20. RA domain function can be replaced by the nine C-terminal, plasma membrane-targeting residues (KKSKKCAIL) of Cdc42, and membrane-targeted Ste50 also suppresses the signaling deficiency of cdc42 alleles specifically defective in invasive growth. Thus, Ste50 serves as an adaptor to tether Ste11 to the plasma membrane and can do so via association with Cdc42, thereby permitting the encounter of Ste11 with activated Ste20. PMID:16428446

  19. NAPS: Network Analysis of Protein Structures.

    Science.gov (United States)

    Chakrabarty, Broto; Parekh, Nita

    2016-07-01

    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

  20. Finding local communities in protein networks

    OpenAIRE

    Teng Shang-Hua; Voevodski Konstantin; Xia Yu

    2009-01-01

    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 ne...

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

    Directory of Open Access Journals (Sweden)

    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

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

    OpenAIRE

    Xiaomin Wang; Zhengzhi Wang; Jun Ye

    2011-01-01

    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 use...

  3. 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

  4. The centrality of cancer proteins in human protein-protein interaction network: a revisit.

    Science.gov (United States)

    Xiong, Wei; Xie, Luyu; Zhou, Shuigeng; Liu, Hui; Guan, Jihong

    2014-01-01

    Topological analysis of protein-protein interaction (PPI) networks has been widely applied to the investigation on cancer mechanisms. However, there is still a debate on whether cancer proteins exhibit more topological centrality compared to the other proteins in the human PPI network. To resolve this debate, we first identified four sets of human proteins, and then mapped these proteins into the yeast PPI network by homologous genes. Finally, we compared these proteins' properties in human and yeast PPI networks. Experiments over two real datasets demonstrated that cancer proteins tend to have higher degree and smaller clustering coefficient than non-cancer proteins. Experimental results also validated that cancer proteins have larger betweenness centrality compared to the other proteins on the STRING dataset. However, on the BioGRID dataset, the average betweenness centrality of cancer proteins is larger than that of disease and control proteins, but smaller than that of essential proteins. PMID:24878726

  5. 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.

    Science.gov (United States)

    Hsieh, Yi-Wen; Chang, Chieh; Chuang, Chiou-Fen

    2012-01-01

    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.

  6. 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.

    Directory of Open Access Journals (Sweden)

    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.

  7. The cellular RNA export receptor TAP/NXF1 is required for ICP27-mediated export of herpes simplex virus 1 RNA, but the TREX complex adaptor protein Aly/REF appears to be dispensable.

    Science.gov (United States)

    Johnson, Lisa A; Li, Ling; Sandri-Goldin, Rozanne M

    2009-07-01

    Herpes simplex virus 1 (HSV-1) protein ICP27 has been shown to shuttle between the nucleus and cytoplasm and to bind viral RNA during infection. ICP27 was found to interact with the cellular RNA export adaptor protein Aly/REF, which is part of the TREX complex, and to relocalize Aly/REF to viral replication sites. ICP27 is exported to the cytoplasm through the export receptor TAP/NXF1, and ICP27 must be able to interact with TAP/NXF1 for efficient export of HSV-1 early and late transcripts. We examined the dynamics of ICP27 movement and its localization with respect to Aly/REF and TAP/NXF1 in living cells during viral infection. Recombinant viruses with a yellow fluorescent protein (YFP) tag on the N or C terminus of ICP27 were constructed. While the N-terminally tagged ICP27 virus behaved like wild-type HSV-1, the C-terminally tagged virus was defective in viral replication and gene expression, and ICP27 was confined to the nucleus, suggesting that the C-terminal YFP tag interfered with ICP27's C-terminal interactions, including the interaction with TAP/NXF1. To assess the role of Aly/REF and TAP/NXF1 in viral RNA export, these factors were knocked down using small interfering RNA. Knockdown of Aly/REF had little effect on the export of ICP27 or poly(A)(+) RNA during infection. In contrast, a decrease in TAP/NXF1 levels severely impaired export of ICP27 and poly(A)(+) RNA. We conclude that TAP/NXF1 is essential for ICP27-mediated export of RNA during HSV-1 infection, whereas Aly/REF may be dispensable.

  8. Reconstruction of human protein interolog network using evolutionary conserved network

    Directory of Open Access Journals (Sweden)

    Lin Chung-Yen

    2007-05-01

    Full Text Available Abstract Background The recent increase in the use of high-throughput two-hybrid analysis has generated large quantities of data on protein interactions. Specifically, the availability of information about experimental protein-protein interactions and other protein features on the Internet enables human protein-protein interactions to be computationally predicted from co-evolution events (interolog. This study also considers other protein interaction features, including sub-cellular localization, tissue-specificity, the cell-cycle stage and domain-domain combination. Computational methods need to be developed to integrate these heterogeneous biological data to facilitate the maximum accuracy of the human protein interaction prediction. Results This study proposes a relative conservation score by finding maximal quasi-cliques in protein interaction networks, and considering other interaction features to formulate a scoring method. The scoring method can be adopted to discover which protein pairs are the most likely to interact among multiple protein pairs. The predicted human protein-protein interactions associated with confidence scores are derived from six eukaryotic organisms – rat, mouse, fly, worm, thale cress and baker's yeast. Conclusion Evaluation results of the proposed method using functional keyword and Gene Ontology (GO annotations indicate that some confidence is justified in the accuracy of the predicted interactions. Comparisons among existing methods also reveal that the proposed method predicts human protein-protein interactions more accurately than other interolog-based methods.

  9. 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...

  10. Network motifs in integrated cellular networks of transcription-regulation and protein-protein interaction

    Science.gov (United States)

    Yeger-Lotem, Esti; Sattath, Shmuel; Kashtan, Nadav; Itzkovitz, Shalev; Milo, Ron; Pinter, Ron Y.; Alon, Uri; Margalit, Hanah

    2004-04-01

    Genes and proteins generate molecular circuitry that enables the cell to process information and respond to stimuli. A major challenge is to identify characteristic patterns in this network of interactions that may shed light on basic cellular mechanisms. Previous studies have analyzed aspects of this network, concentrating on either transcription-regulation or protein-protein interactions. Here we search for composite network motifs: characteristic network patterns consisting of both transcription-regulation and protein-protein interactions that recur significantly more often than in random networks. To this end we developed algorithms for detecting motifs in networks with two or more types of interactions and applied them to an integrated data set of protein-protein interactions and transcription regulation in Saccharomyces cerevisiae. We found a two-protein mixed-feedback loop motif, five types of three-protein motifs exhibiting coregulation and complex formation, and many motifs involving four proteins. Virtually all four-protein motifs consisted of combinations of smaller motifs. This study presents a basic framework for detecting the building blocks of networks with multiple types of interactions.

  11. Multiplexed imaging of intracellular protein networks.

    Science.gov (United States)

    Grecco, Hernán E; Imtiaz, Sarah; Zamir, Eli

    2016-08-01

    Cellular functions emerge from the collective action of a large number of different proteins. Understanding how these protein networks operate requires monitoring their components in intact cells. Due to intercellular and intracellular molecular variability, it is important to monitor simultaneously multiple components at high spatiotemporal resolution. However, inherent trade-offs narrow the boundaries of achievable multiplexed imaging. Pushing these boundaries is essential for a better understanding of cellular processes. Here the motivations, challenges and approaches for multiplexed imaging of intracellular protein networks are discussed. © 2016 International Society for Advancement of Cytometry. PMID:27183498

  12. Multifunctional proteins revealed by overlapping clustering in protein interaction network

    OpenAIRE

    Becker, Emmanuelle; Robisson, Benoît; Chapple, Charles E.; Guénoche, Alain; Brun, Christine

    2011-01-01

    Motivation: Multifunctional proteins perform several functions. They are expected to interact specifically with distinct sets of partners, simultaneously or not, depending on the function performed. Current graph clustering methods usually allow a protein to belong to only one cluster, therefore impeding a realistic assignment of multifunctional proteins to clusters. Results: Here, we present Overlapping Cluster Generator (OCG), a novel clustering method which decomposes a network into overla...

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

    Directory of Open Access Journals (Sweden)

    Oleksii Kuchaiev

    2009-08-01

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

  14. 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.

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

    OpenAIRE

    Sun Zhirong; Liu Ke; Chen Hu; Zhang Song

    2009-01-01

    Abstract Background Genome sequencing projects generate massive amounts of sequence data but there are still many proteins whose functions remain unknown. The availability of large scale protein-protein interaction data sets makes it possible to develop new function prediction methods based on protein-protein interaction (PPI) networks. Although several existing methods combine multiple information resources, there is no study that integrates protein domain information and PPI networks to pre...

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

    Science.gov (United States)

    Zhong, Ming-Chao; Veillette, André

    2013-11-01

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

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

    Directory of Open Access Journals (Sweden)

    Loic Royer

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

  18. Defective jejunal and colonic salt absorption and alteredNa +/H+ exchanger 3 (NHE3) activity in NHE regulatory factor 1 (NHERF1) adaptor protein-deficient mice

    NARCIS (Netherlands)

    N. Broere (Nellie); M. Chen (Min); A. Cinar (Ayhan); A.K. Singh (Arbind); J. Hillesheim (Jutta); B. Riederer (Beat Michel); M. Lunnemann; I. Rottinghaus (Ingrid); A. Krabbenhöft (Anja); R. Engelhardt (Regina); B. Rausch; E.J. Weinman (Edward); M. Donowitz (Mark); A. Hubbard; O. Kocher (Olivier); H.R. de Jonge (Hugo); B.M. Hogema (Boris); U. Seidler (Ursula)

    2009-01-01

    textabstractWe investigated the role of the Na+/H+ exchanger regulatory factor 1 (NHERF1) on intestinal salt and water absorption, brush border membrane (BBM) morphology, and on the NHE3 mRNA expression, protein abundance, and transport activity in the murine intestine. NHERF1-deficient mice display

  19. 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

  20. Differential Association of the Na+/H+ Exchanger Regulatory Factor (NHERF Family of Adaptor Proteins with the Raft- and the Non-Raft Brush Border Membrane Fractions of NHE3

    Directory of Open Access Journals (Sweden)

    Ayesha Sultan

    2013-11-01

    Full Text Available Background/Aims: Trafficking, brush border membrane (BBM retention, and signal-specific regulation of the Na+/H+ exchanger NHE3 is regulated by the Na+/H+ Exchanger Regulatory Factor (NHERF family of PDZ-adaptor proteins, which enable the formation of multiprotein complexes. It is unclear, however, what determines signal specificity of these NHERFs. Thus, we studied the association of NHE3, NHERF1 (EBP50, NHERF2 (E3KARP, and NHERF3 (PDZK1 with lipid rafts in murine small intestinal BBM. Methods: Detergent resistant membranes (“lipid rafts” were isolated by floatation of Triton X-incubated small intestinal BBM from a variety of knockout mouse strains in an Optiprep step gradient. Acid-activated NHE3 activity was measured fluorometrically in BCECF-loaded microdissected villi, or by assessment of CO2/HCO3- mediated increase in fluid absorption in perfused jejunal loops of anethetized mice. Results: NHE3 was found to partially associate with lipid rafts in the native BBM, and NHE3 raft association had an impact on NHE3 transport activity and regulation in vivo. NHERF1, 2 and 3 were differentially distributed to rafts and non-rafts, with NHERF2 being most raft-associated and NHERF3 entirely non-raft associated. NHERF2 expression enhanced the localization of NHE3 to membrane rafts. The use of acid sphingomyelinase-deficient mice, which have altered membrane lipid as well as lipid raft composition, allowed us to test the validity of the lipid raft concept in vivo. Conclusions: The differential association of the NHERFs with the raft-associated and the non-raft fraction of NHE3 in the brush border membrane is one component of the differential and signal-specific NHE3 regulation by the different NHERFs.

  1. 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

  2. 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

  3. Detecting overlapping protein complexes in protein-protein interaction networks

    OpenAIRE

    Nepusz, Tamás; Yu, Haiyuan; Paccanaro, Alberto

    2012-01-01

    We introduce clustering with overlapping neighborhood expansion (ClusterONE), a method for detecting potentially overlapping protein complexes from protein-protein interaction data. ClusterONE-derived complexes for several yeast data sets showed better correspondence with reference complexes in the Munich Information Center for Protein Sequence (MIPS) catalog and complexes derived from the Saccharomyces Genome Database (SGD) than the results of seven popular methods. The results also showed a...

  4. A conserved protein interaction network involving the yeast MAP kinases Fus3 and Kss1.

    Science.gov (United States)

    Kusari, Anasua B; Molina, Douglas M; Sabbagh, Walid; Lau, Chang S; Bardwell, Lee

    2004-01-19

    The Saccharomyces cerevisiae mitogen-activated protein kinases (MAPKs) Fus3 and Kss1 bind to multiple regulators and substrates. We show that mutations in a conserved docking site in these MAPKs (the CD/7m region) disrupt binding to an important subset of their binding partners, including the Ste7 MAPK kinase, the Ste5 adaptor/scaffold protein, and the Dig1 and Dig2 transcriptional repressors. Supporting the possibility that Ste5 and Ste7 bind to the same region of the MAPKs, they partially competed for Fus3 binding. In vivo, some of the MAPK mutants displayed reduced Ste7-dependent phosphorylation, and all of them exhibited multiple defects in mating and pheromone response. The Kss1 mutants were also defective in Kss1-imposed repression of Ste12. We conclude that MAPKs contain a structurally and functionally conserved docking site that mediates an overall positively acting network of interactions with cognate docking sites on their regulators and substrates. Key features of this interaction network appear to have been conserved from yeast to humans. PMID:14734536

  5. An Algorithm for Finding Functional Modules and Protein Complexes in Protein-Protein Interaction Networks

    OpenAIRE

    Guangyu Cui; Yu Chen; De-Shuang Huang; Kyungsook Han

    2008-01-01

    Biological processes are often performed by a group of proteins rather than by individual proteins, and proteins in a same biological group form a densely connected subgraph in a protein-protein interaction network. Therefore, finding a densely connected subgraph provides useful information to predict the function or protein complex of uncharacterized proteins in the highly connected subgraph. We have developed an efficient algorithm and program for finding cliques and near-cliques in a prote...

  6. The E3 Ubiquitin Ligase Adaptor Protein Skp1 Is Glycosylated by an Evolutionarily Conserved Pathway That Regulates Protist Growth and Development.

    Science.gov (United States)

    Rahman, Kazi; Zhao, Peng; Mandalasi, Msano; van der Wel, Hanke; Wells, Lance; Blader, Ira J; West, Christopher M

    2016-02-26

    Toxoplasma gondii is a protist parasite of warm-blooded animals that causes disease by proliferating intracellularly in muscle and the central nervous system. Previous studies showed that a prolyl 4-hydroxylase related to animal HIFα prolyl hydroxylases is required for optimal parasite proliferation, especially at low O2. We also observed that Pro-154 of Skp1, a subunit of the Skp1/Cullin-1/F-box protein (SCF)-class of E3-ubiquitin ligases, is a natural substrate of this enzyme. In an unrelated protist, Dictyostelium discoideum, Skp1 hydroxyproline is modified by five sugars via the action of three glycosyltransferases, Gnt1, PgtA, and AgtA, which are required for optimal O2-dependent development. We show here that TgSkp1 hydroxyproline is modified by a similar pentasaccharide, based on mass spectrometry, and that assembly of the first three sugars is dependent on Toxoplasma homologs of Gnt1 and PgtA. Reconstitution of the glycosyltransferase reactions in extracts with radioactive sugar nucleotide substrates and appropriate Skp1 glycoforms, followed by chromatographic analysis of acid hydrolysates of the reaction products, confirmed the predicted sugar identities as GlcNAc, Gal, and Fuc. Disruptions of gnt1 or pgtA resulted in decreased parasite growth. Off target effects were excluded based on restoration of the normal glycan chain and growth upon genetic complementation. By analogy to Dictyostelium Skp1, the mechanism may involve regulation of assembly of the SCF complex. Understanding the mechanism of Toxoplasma Skp1 glycosylation is expected to help develop it as a drug target for control of the pathogen, as the glycosyltransferases are absent from mammalian hosts. PMID:26719340

  7. The E3 Ubiquitin Ligase Adaptor Protein Skp1 Is Glycosylated by an Evolutionarily Conserved Pathway That Regulates Protist Growth and Development.

    Science.gov (United States)

    Rahman, Kazi; Zhao, Peng; Mandalasi, Msano; van der Wel, Hanke; Wells, Lance; Blader, Ira J; West, Christopher M

    2016-02-26

    Toxoplasma gondii is a protist parasite of warm-blooded animals that causes disease by proliferating intracellularly in muscle and the central nervous system. Previous studies showed that a prolyl 4-hydroxylase related to animal HIFα prolyl hydroxylases is required for optimal parasite proliferation, especially at low O2. We also observed that Pro-154 of Skp1, a subunit of the Skp1/Cullin-1/F-box protein (SCF)-class of E3-ubiquitin ligases, is a natural substrate of this enzyme. In an unrelated protist, Dictyostelium discoideum, Skp1 hydroxyproline is modified by five sugars via the action of three glycosyltransferases, Gnt1, PgtA, and AgtA, which are required for optimal O2-dependent development. We show here that TgSkp1 hydroxyproline is modified by a similar pentasaccharide, based on mass spectrometry, and that assembly of the first three sugars is dependent on Toxoplasma homologs of Gnt1 and PgtA. Reconstitution of the glycosyltransferase reactions in extracts with radioactive sugar nucleotide substrates and appropriate Skp1 glycoforms, followed by chromatographic analysis of acid hydrolysates of the reaction products, confirmed the predicted sugar identities as GlcNAc, Gal, and Fuc. Disruptions of gnt1 or pgtA resulted in decreased parasite growth. Off target effects were excluded based on restoration of the normal glycan chain and growth upon genetic complementation. By analogy to Dictyostelium Skp1, the mechanism may involve regulation of assembly of the SCF complex. Understanding the mechanism of Toxoplasma Skp1 glycosylation is expected to help develop it as a drug target for control of the pathogen, as the glycosyltransferases are absent from mammalian hosts.

  8. Analysis of protein folds using protein contact networks

    Indian Academy of Sciences (India)

    Pankaj Barah; Somdatta Sinha

    2008-08-01

    Proteins are important biomolecules, which perform diverse structural and functional roles in living systems. Starting from a linear chain of amino acids, proteins fold to different secondary structures, which then fold through short- and long-range interactions to give rise to the final three-dimensional shapes useful to carry out the biophysical and biochemical functions. Proteins are defined as having a common `fold' if they have major secondary structural elements with same topological connections. It is known that folding mechanisms are largely determined by a protein's topology rather than its interatomic interactions. The native state protein structures can, thus, be modelled, using a graph-theoretical approach, as coarse-grained networks of amino acid residues as `nodes' and the inter-residue interactions/contacts as `links'. Using the network representation of protein structures and their 2D contact maps, we have identified the conserved contact patterns (groups of contacts) representing two typical folds – the EF-hand and the ubiquitin-like folds. Our results suggest that this direct and computationally simple methodology can be used to infer about the presence of specific folds from the protein's contact map alone.

  9. Extracting protein regulatory networks with graphical models.

    Science.gov (United States)

    Grzegorczyk, Marco

    2007-09-01

    During the last decade the development of high-throughput biotechnologies has resulted in the production of exponentially expanding quantities of biological data, such as genomic and proteomic expression data. One fundamental problem in systems biology is to learn the architecture of biochemical pathways and regulatory networks in an inferential way from such postgenomic data. Along with the increasing amount of available data, a lot of novel statistical methods have been developed and proposed in the literature. This article gives a non-mathematical overview of three widely used reverse engineering methods, namely relevance networks, graphical Gaussian models, and Bayesian networks, whereby the focus is on their relative merits and shortcomings. In addition the reverse engineering results of these graphical methods on cytometric protein data from the RAF-signalling network are cross-compared via AUROC scatter plots. PMID:17893851

  10. Probabilistic methods for predicting protein functions in protein-protein interaction networks

    OpenAIRE

    Best, Christoph; Zimmer, Ralf; Apostolakis, Joannis

    2005-01-01

    We discuss probabilistic methods for predicting protein functions from protein-protein interaction networks. Previous work based on Markov Randon Fields is extended and compared to a general machine-learning theoretic approach. Using actual protein interaction networks for yeast from the MIPS database and GO-SLIM function assignments, we compare the predictions of the different probabilistic methods and of a standard support vector machine. It turns out that, with the currently available netw...

  11. Modularity detection in protein-protein interaction networks

    Directory of Open Access Journals (Sweden)

    Narayanan Tejaswini

    2011-12-01

    Full Text Available Abstract Background Many recent studies have investigated modularity in biological networks, and its role in functional and structural characterization of constituent biomolecules. A technique that has shown considerable promise in the domain of modularity detection is the Newman and Girvan (NG algorithm, which relies on the number of shortest-paths across pairs of vertices in the network traversing a given edge, referred to as the betweenness of that edge. The edge with the highest betweenness is iteratively eliminated from the network, with the betweenness of the remaining edges recalculated in every iteration. This generates a complete dendrogram, from which modules are extracted by applying a quality metric called modularity denoted by Q. This exhaustive computation can be prohibitively expensive for large networks such as Protein-Protein Interaction Networks. In this paper, we present a novel optimization to the modularity detection algorithm, in terms of an efficient termination criterion based on a target edge betweenness value, using which the process of iterative edge removal may be terminated. Results We validate the robustness of our approach by applying our algorithm on real-world protein-protein interaction networks of Yeast, C.Elegans and Drosophila, and demonstrate that our algorithm consistently has significant computational gains in terms of reduced runtime, when compared to the NG algorithm. Furthermore, our algorithm produces modules comparable to those from the NG algorithm, qualitatively and quantitatively. We illustrate this using comparison metrics such as module distribution, module membership cardinality, modularity Q, and Jaccard Similarity Coefficient. Conclusions We have presented an optimized approach for efficient modularity detection in networks. The intuition driving our approach is the extraction of holistic measures of centrality from graphs, which are representative of inherent modular structure of the

  12. The Effects of Network Neighbours on Protein Evolution

    OpenAIRE

    Guang-Zhong Wang; Martin J Lercher

    2011-01-01

    Interacting proteins may often experience similar selection pressures. Thus, we may expect that neighbouring proteins in biological interaction networks evolve at similar rates. This has been previously shown for protein-protein interaction networks. Similarly, we find correlated rates of evolution of neighbours in networks based on co-expression, metabolism, and synthetic lethal genetic interactions. While the correlations are statistically significant, their magnitude is small, with network...

  13. Role of polymorphisms of toll-like receptor (TLR 4, TLR9, toll-interleukin 1 receptor domain containing adaptor protein (TIRAP and FCGR2A genes in malaria susceptibility and severity in Burundian children

    Directory of Open Access Journals (Sweden)

    Esposito Susanna

    2012-06-01

    Full Text Available Abstract Background Malaria caused by Plasmodium falciparum is one of the leading causes of human morbidity and mortality from infectious diseases, predominantly in tropical and sub-tropical countries. As genetic variations in the toll-like receptors (TLRs-signalling pathway have been associated with either susceptibility or resistance to several infectious and inflammatory diseases, the supposition is that single nucleotide polymorphisms (SNPs of TLR2, TLR4, TLR9, Toll-interleukin 1 receptor domain containing adaptor protein (TIRAP and FCGR2A could modulate malaria susceptibility and severity. Methods This study was planned to make a further contribution to solving the problem of the real role of the most common polymorphisms of TLR4, TLR9, TIRAP and FCGR2A genes in modulating the risk of malaria and disease severity in children from Burundi, Central Africa. All the paediatric patients aged six months to 10 years admitted to the hospital of Kiremba, Burundi, between February 2011 and September 2011, for fever and suspicion of acute malaria were screened for malaria parasitaemia by light microscopy of thick and thin blood smears. In children with malaria and in uninfected controls enrolled during the study period in the same hospital, blood samples were obtained on filter paper and TLR4 Asp299Gly rs4986790, TLR9 G1174A rs352139, T-1486 C rs187084 TLR9 T-1237 C rs5743836, TIRAP Ser180Leu rs8177374 and the FCGR2A His131Arg rs1801274 polymorphisms were studied using an ABI PRISM 7900 HT Fast Real-time instrument. Results A total of 602 patients and 337 controls were enrolled. Among the malaria cases, 553 (91.9 % were considered as suffering from uncomplicated and 49 (8.1 % from severe malaria. TLR9 T1237C rs5743836CC was associated with an increased risk of developing malaria (p = 0.03, although it was found with the same frequency in uncomplicated and severe malaria cases. No other differences were found in all alleles studied and in

  14. CPL:Detecting Protein Complexes by Propagating Labels on Protein-Protein Interaction Network

    Institute of Scientific and Technical Information of China (English)

    代启国; 郭茂祖; 刘晓燕; 滕志霞; 王春宇

    2014-01-01

    Proteins usually bind together to form complexes, which play an important role in cellular activities. Many graph clustering methods have been proposed to identify protein complexes by finding dense regions in protein-protein interaction networks. We present a novel framework (CPL) that detects protein complexes by propagating labels through interactions in a network, in which labels denote complex identifiers. With proper propagation in CPL, proteins in the same complex will be assigned with the same labels. CPL does not make any strong assumptions about the topological structures of the complexes, as in previous methods. The CPL algorithm is tested on several publicly available yeast protein-protein interaction networks and compared with several state-of-the-art methods. The results suggest that CPL performs better than the existing methods. An analysis of the functional homogeneity based on a gene ontology analysis shows that the detected complexes of CPL are highly biologically relevant.

  15. WD40 proteins propel cellular networks.

    Science.gov (United States)

    Stirnimann, Christian U; Petsalaki, Evangelia; Russell, Robert B; Müller, Christoph W

    2010-10-01

    Recent findings indicate that WD40 domains play central roles in biological processes by acting as hubs in cellular networks; however, they have been studied less intensely than other common domains, such as the kinase, PDZ or SH3 domains. As suggested by various interactome studies, they are among the most promiscuous interactors. Structural studies suggest that this property stems from their ability, as scaffolds, to interact with diverse proteins, peptides or nucleic acids using multiple surfaces or modes of interaction. A general scaffolding role is supported by the fact that no WD40 domain has been found with intrinsic enzymatic activity despite often being part of large molecular machines. We discuss the WD40 domain distributions in protein networks and structures of WD40-containing assemblies to demonstrate their versatility in mediating critical cellular functions.

  16. Predicting multiplex subcellular localization of proteins using protein-protein interaction network: a comparative study

    OpenAIRE

    Jiang Jonathan Q; Wu Maoying

    2012-01-01

    Abstract Background Proteins that interact in vivo tend to reside within the same or "adjacent" subcellular compartments. This observation provides opportunities to reveal protein subcellular localization in the context of the protein-protein interaction (PPI) network. However, so far, only a few efforts based on heuristic rules have been made in this regard. Results We systematically and quantitatively validate the hypothesis that proteins physically interacting with each other probably shar...

  17. CCM2-CCM3 interaction stabilizes their protein expression and permits endothelial network formation

    Energy Technology Data Exchange (ETDEWEB)

    Draheim, Kyle M.; Li, Xiaofeng; Zhang, Rong; Fisher, Oriana S.; Villari, Giulia; Boggon, Titus J.; Calderwood, David A. [Yale

    2015-04-21

    Mutations in the essential adaptor proteins CCM2 or CCM3 lead to cerebral cavernous malformations (CCM), vascular lesions that most frequently occur in the brain and are strongly associated with hemorrhagic stroke, seizures, and other neurological disorders. CCM2 binds CCM3, but the molecular basis of this interaction, and its functional significance, have not been elucidated. Here, we used x-ray crystallography and structure-guided mutagenesis to show that an α-helical LD-like motif within CCM2 binds the highly conserved “HP1” pocket of the CCM3 focal adhesion targeting (FAT) homology domain. By knocking down CCM2 or CCM3 and rescuing with binding-deficient mutants, we establish that CCM2–CCM3 interactions protect CCM2 and CCM3 proteins from proteasomal degradation and show that both CCM2 and CCM3 are required for normal endothelial cell network formation. However, CCM3 expression in the absence of CCM2 is sufficient to support normal cell growth, revealing complex-independent roles for CCM3.

  18. Evolutionarily conserved herpesviral protein interaction networks.

    Directory of Open Access Journals (Sweden)

    Even Fossum

    2009-09-01

    Full Text Available Herpesviruses constitute a family of large DNA viruses widely spread in vertebrates and causing a variety of different diseases. They possess dsDNA genomes ranging from 120 to 240 kbp encoding between 70 to 170 open reading frames. We previously reported the protein interaction networks of two herpesviruses, varicella-zoster virus (VZV and Kaposi's sarcoma-associated herpesvirus (KSHV. In this study, we systematically tested three additional herpesvirus species, herpes simplex virus 1 (HSV-1, murine cytomegalovirus and Epstein-Barr virus, for protein interactions in order to be able to perform a comparative analysis of all three herpesvirus subfamilies. We identified 735 interactions by genome-wide yeast-two-hybrid screens (Y2H, and, together with the interactomes of VZV and KSHV, included a total of 1,007 intraviral protein interactions in the analysis. Whereas a large number of interactions have not been reported previously, we were able to identify a core set of highly conserved protein interactions, like the interaction between HSV-1 UL33 with the nuclear egress proteins UL31/UL34. Interactions were conserved between orthologous proteins despite generally low sequence similarity, suggesting that function may be more conserved than sequence. By combining interactomes of different species we were able to systematically address the low coverage of the Y2H system and to extract biologically relevant interactions which were not evident from single species.

  19. Competitive and cooperative interactions mediate RNA transfer from herpesvirus saimiri ORF57 to the mammalian export adaptor ALYREF.

    Directory of Open Access Journals (Sweden)

    Richard B Tunnicliffe

    2014-02-01

    Full Text Available The essential herpesvirus adaptor protein HVS ORF57, which has homologs in all other herpesviruses, promotes viral mRNA export by utilizing the cellular mRNA export machinery. ORF57 protein specifically recognizes viral mRNA transcripts, and binds to proteins of the cellular transcription-export (TREX complex, in particular ALYREF. This interaction introduces viral mRNA to the NXF1 pathway, subsequently directing it to the nuclear pore for export to the cytoplasm. Here we have used a range of techniques to reveal the sites for direct contact between RNA and ORF57 in the absence and presence of ALYREF. A binding site within ORF57 was characterized which recognizes specific viral mRNA motifs. When ALYREF is present, part of this ORF57 RNA binding site, composed of an α-helix, binds preferentially to ALYREF. This competitively displaces viral RNA from the α-helix, but contact with RNA is still maintained by a flanking region. At the same time, the flexible N-terminal domain of ALYREF comes into contact with the viral RNA, which becomes engaged in an extensive network of synergistic interactions with both ALYREF and ORF57. Transfer of RNA to ALYREF in the ternary complex, and involvement of individual ORF57 residues in RNA recognition, were confirmed by UV cross-linking and mutagenesis. The atomic-resolution structure of the ORF57-ALYREF interface was determined, which noticeably differed from the homologous ICP27-ALYREF structure. Together, the data provides the first site-specific description of how viral mRNA is locked by a herpes viral adaptor protein in complex with cellular ALYREF, giving herpesvirus access to the cellular mRNA export machinery. The NMR strategy used may be more generally applicable to the study of fuzzy protein-protein-RNA complexes which involve flexible polypeptide regions.

  20. Connecting the dots in Huntington's disease with protein interaction networks

    OpenAIRE

    Giorgini, Flaviano; Muchowski, Paul J.

    2005-01-01

    Analysis of protein-protein interaction networks is becoming important for inferring the function of uncharacterized proteins. A recent study using this approach has identified new proteins and interactions that might be involved in the pathogenesis of the neurodegenerative disorder Huntington's disease, including a GTPase-activating protein that co-localizes with protein aggregates in Huntington's disease patients.

  1. The Intrinsic Geometric Structure of Protein-Protein Interaction Networks for Protein Interaction Prediction.

    Science.gov (United States)

    Fang, Yi; Sun, Mengtian; Dai, Guoxian; Ramain, Karthik

    2016-01-01

    Recent developments in high-throughput technologies for measuring protein-protein interaction (PPI) have profoundly advanced our ability to systematically infer protein function and regulation. However, inherently high false positive and false negative rates in measurement have posed great challenges in computational approaches for the prediction of PPI. A good PPI predictor should be 1) resistant to high rate of missing and spurious PPIs, and 2) robust against incompleteness of observed PPI networks. To predict PPI in a network, we developed an intrinsic geometry structure (IGS) for network, which exploits the intrinsic and hidden relationship among proteins in network through a heat diffusion process. In this process, all explicit PPIs participate simultaneously to glue local infinitesimal and noisy experimental interaction data to generate a global macroscopic descriptions about relationships among proteins. The revealed implicit relationship can be interpreted as the probability of two proteins interacting with each other. The revealed relationship is intrinsic and robust against individual, local and explicit protein interactions in the original network. We apply our approach to publicly available PPI network data for the evaluation of the performance of PPI prediction. Experimental results indicate that, under different levels of the missing and spurious PPIs, IGS is able to robustly exploit the intrinsic and hidden relationship for PPI prediction with a higher sensitivity and specificity compared to that of recently proposed methods. PMID:26886733

  2. Modularity in the evolution of yeast protein interaction network

    OpenAIRE

    Ogishima, Soichi; Tanaka, Hiroshi; Nakaya, Jun

    2015-01-01

    Protein interaction networks are known to exhibit remarkable structures: scale-free and small-world and modular structures. To explain the evolutionary processes of protein interaction networks possessing scale-free and small-world structures, preferential attachment and duplication-divergence models have been proposed as mathematical models. Protein interaction networks are also known to exhibit another remarkable structural characteristic, modular structure. How the protein interaction netw...

  3. Discover Protein Complexes in Protein-Protein Interaction Networks Using Parametric Local Modularity

    OpenAIRE

    Tan Kai; Kim Jongkwang

    2010-01-01

    Abstract Background Recent advances in proteomic technologies have enabled us to create detailed protein-protein interaction maps in multiple species and in both normal and diseased cells. As the size of the interaction dataset increases, powerful computational methods are required in order to effectively distil network models from large-scale interactome data. Results We present an algorithm, miPALM (Module Inference by Parametric Local Modularity), to infer protein complexes in a protein-pr...

  4. 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.

  5. Protein interaction network related to Helicobacter pylori infection response

    Institute of Scientific and Technical Information of China (English)

    Kyu Kwang Kim; Han Bok Kim

    2009-01-01

    AIM: To understand the complex reaction of gastric inflammation induced by Helicobacter pylori (H pylori ) in a systematic manner using a protein interaction network. METHODS: The expression of genes significantly changed on microarray during H pylori infection was scanned from the web literary database and translated into proteins. A network of protein interactions was constructed by searching the primary interactions of selected proteins. The constructed network was mathematically analyzed and its biological function was examined. In addition, the nodes on the network were checked to determine if they had any further functional importance or relation to other proteins by extending them.RESULTS: The scale-free network showing the relationship between inflammation and carcinogenesis was constructed. Mathematical analysis showed hub and bottleneck proteins, and these proteins were mostly related to immune response. The network contained pathways and proteins related to H pylori infection, such as the JAK-STAT pathway triggered by interleukins. Activation of nuclear factor (NF)-kB, TLR4, and other proteins known to function as core proteins of immune response were also found.These immune-related proteins interacted on the network with pathways and proteins related to the cell cycle, cell maintenance and proliferation, and transcription regulators such as BRCA1, FOS, REL, and zinc finger proteins. The extension of nodes showed interactions of the immune proteins with cancerrelated proteins. One extended network, the core network, a summarized form of the extended network, and cell pathway model were constructed. CONCLUSION: Immune-related proteins activated by H pylori infection interact with proto-oncogene proteins. The hub and bottleneck proteins are potential drug targets for gastric inflammation and cancer.

  6. The AP-3 adaptor complex is required for vacuolar function in Arabidopsis

    NARCIS (Netherlands)

    Zwiewka, M.; Feraru, E.; Moller, B.K.; Hwang, I.; Feraru, M.I.; Kleine-Vehn, J.; Weijers, D.; Friml, J.

    2011-01-01

    Subcellular trafficking is required for a multitude of functions in eukaryotic cells. It involves regulation of cargo sorting, vesicle formation, trafficking and fusion processes at multiple levels. Adaptor protein (AP) complexes are key regulators of cargo sorting into vesicles in yeast and mammals

  7. Probing heterobivalent binding to the endocytic AP-2 adaptor complex by DNA-based spatial screening.

    Science.gov (United States)

    Diezmann, F; von Kleist, L; Haucke, V; Seitz, O

    2015-08-01

    The double helical DNA scaffold offers a unique set of properties, which are particularly useful for studies of multivalency in biomolecular interactions: (i) multivalent ligand displays can be formed upon nucleic acid hybridization in a self-assembly process, which facilitates spatial screening (ii) valency and spatial arrangement of the ligand display can be precisely controlled and (iii) the flexibility of the ligand display can be adjusted by integrating nick sites and unpaired template regions. Herein we describe the use of DNA-based spatial screening for the characterization of the adaptor complex 2 (AP-2), a central interaction hub within the endocytic protein network in clathrin-mediated endocytosis. AP-2 is comprised of a core domain and two, so-called appendage domains, the α- and the β2-ear, which associate with cytoplasmatic proteins required for the formation or maturation of clathrin/AP-2 coated pits. Each appendage domain has two binding grooves which recognize distinct peptide motives with micromolar affinity. This provides opportunities for enhanced interactions with protein molecules that contain two (or more) different peptide motives. To determine whether a particular, spatial arrangement of binding motifs is required for high affinity binding we probed the distance-affinity relationships by means of DNA-programmed spatial screening with self-assembled peptide-DNA complexes. By using trimolecular and tetramolecular assemblies two different peptides were positioned in 2-22 nucleotide distance. The binding data obtained with both recombinant protein in well-defined buffer systems and native AP-2 in brain extract suggests that the two binding sites of the AP-2 α-appendage can cooperate to provide up to 40-fold enhancement of affinity compared to the monovalent interaction. The distance between the two recognized peptide motives was less important provided that the DNA duplex segments were connected by flexible, single strand segments. By

  8. Pin-Align: A New Dynamic Programming Approach to Align Protein-Protein Interaction Networks

    OpenAIRE

    Farid Amir-Ghiasvand; Abbas Nowzari-Dalini; Vida Momenzadeh

    2014-01-01

    To date, few tools for aligning protein-protein interaction networks have been suggested. These tools typically find conserved interaction patterns using various local or global alignment algorithms. However, the improvement of the speed, scalability, simplification, and accuracy of network alignment tools is still the target of new researches. In this paper, we introduce Pin-Align, a new tool for local alignment of protein-protein interaction networks. Pin-Align accuracy is tested on protein...

  9. Identifying drug-target proteins based on network features

    Institute of Scientific and Technical Information of China (English)

    ZHU MingZhu; GAO Lei; LI Xia; LIU ZhiCheng

    2009-01-01

    Proteins rarely function in isolation Inside and outside cells, but operate as part of a highly Intercon-nected cellular network called the interaction network. Therefore, the analysis of the properties of drug-target proteins in the biological network is especially helpful for understanding the mechanism of drug action In terms of informatice. At present, no detailed characterization and description of the topological features of drug-target proteins have been available in the human protein-protein interac-tion network. In this work, by mapping the drug-targets in DrugBank onto the interaction network of human proteins, five topological indices of drug-targets were analyzed and compared with those of the whole protein interactome set and the non-drug-target set. The experimental results showed that drug-target proteins have higher connectivity and quicker communication with each other in the PPI network. Based on these features, all proteins In the interaction network were ranked. The results showed that, of the top 100 proteins, 48 are covered by DrugBank; of the remaining 52 proteins, 9 are drug-target proteins covered by the TTD, Matador and other databases, while others have been dem-onstrated to be drug-target proteins in the literature.

  10. Identifying drug-target proteins based on network features

    Institute of Scientific and Technical Information of China (English)

    2009-01-01

    Proteins rarely function in isolation inside and outside cells, but operate as part of a highly intercon- nected cellular network called the interaction network. Therefore, the analysis of the properties of drug-target proteins in the biological network is especially helpful for understanding the mechanism of drug action in terms of informatics. At present, no detailed characterization and description of the topological features of drug-target proteins have been available in the human protein-protein interac- tion network. In this work, by mapping the drug-targets in DrugBank onto the interaction network of human proteins, five topological indices of drug-targets were analyzed and compared with those of the whole protein interactome set and the non-drug-target set. The experimental results showed that drug-target proteins have higher connectivity and quicker communication with each other in the PPI network. Based on these features, all proteins in the interaction network were ranked. The results showed that, of the top 100 proteins, 48 are covered by DrugBank; of the remaining 52 proteins, 9 are drug-target proteins covered by the TTD, Matador and other databases, while others have been dem- onstrated to be drug-target proteins in the literature.

  11. Ribo-Proteomics Approach to Profile RNA-Protein and Protein-Protein Interaction Networks.

    Science.gov (United States)

    Yeh, Hsin-Sung; Chang, Jae-Woong; Yong, Jeongsik

    2016-01-01

    Characterizing protein-protein and protein-RNA interaction networks is a fundamental step to understanding the function of an RNA-binding protein. In many cases, these interactions are transient and highly dynamic. Therefore, capturing stable as well as transient interactions in living cells for the identification of protein-binding partners and the mapping of RNA-binding sequences is key to a successful establishment of the molecular interaction network. In this chapter, we will describe a method for capturing the molecular interactions in living cells using formaldehyde as a crosslinker and enriching a specific RNA-protein complex from cell extracts followed by mass spectrometry and Next-Gen sequencing analyses. PMID:26965265

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

    Directory of Open Access Journals (Sweden)

    Fubito Nakatsu

    2014-11-01

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

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

    Directory of Open Access Journals (Sweden)

    Hao Wu

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

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

    Science.gov (United States)

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

    2014-01-01

    In this paper, we present a novel rough-fuzzy clustering (RFC) method to detect overlapping protein complexes in protein-protein interaction (PPI) networks. RFC focuses on fuzzy relation model rather than graph model by integrating fuzzy sets and rough sets, employs the upper and lower approximations of rough sets to deal with overlapping complexes, and calculates the number of complexes automatically. Fuzzy relation between proteins is established and then transformed into fuzzy equivalence relation. Non-overlapping complexes correspond to equivalence classes satisfying certain equivalence relation. To obtain overlapping complexes, we calculate the similarity between one protein and each complex, and then determine whether the protein belongs to one or multiple complexes by computing the ratio of each similarity to maximum similarity. To validate RFC quantitatively, we test it in Gavin, Collins, Krogan and BioGRID datasets. Experiment results show that there is a good correspondence to reference complexes in MIPS and SGD databases. Then we compare RFC with several previous methods, including ClusterONE, CMC, MCL, GCE, OSLOM and CFinder. Results show the precision, sensitivity and separation are 32.4%, 42.9% and 81.9% higher than mean of the five methods in four weighted networks, and are 0.5%, 11.2% and 66.1% higher than mean of the six methods in five unweighted networks. Our method RFC works well for protein complexes detection and provides a new insight of network division, and it can also be applied to identify overlapping community structure in social networks and LFR benchmark networks. PMID:24642838

  15. Dynamical Analysis of Protein Regulatory Network in Budding Yeast Nucleus

    Institute of Scientific and Technical Information of China (English)

    LI Fang-Ting; JIA Xun

    2006-01-01

    @@ Recent progresses in the protein regulatory network of budding yeast Saccharomyces cerevisiae have provided a global picture of its protein network for further dynamical research. We simplify and modularize the protein regulatory networks in yeast nucleus, and study the dynamical properties of the core 37-node network by a Boolean network model, especially the evolution steps and final fixed points. Our simulation results show that the number of fixed points N(k) for a given size of the attraction basin k obeys a power-law distribution N(k)∝k-2.024. The yeast network is more similar to a scale-free network than a random network in the above dynamical properties.

  16. Scaffold functions of 14-3-3 adaptors in B cell immunoglobulin class switch DNA recombination.

    Directory of Open Access Journals (Sweden)

    Tonika Lam

    Full Text Available Class switch DNA recombination (CSR of the immunoglobulin heavy chain (IgH locus crucially diversifies antibody biological effector functions. CSR involves the induction of activation-induced cytidine deaminase (AID expression and AID targeting to switch (S regions by 14-3-3 adaptors. 14-3-3 adaptors specifically bind to 5'-AGCT-3' repeats, which make up for the core of all IgH locus S regions. They selectively target the upstream and downstream S regions that are set to undergo S-S DNA recombination. We hypothesized that 14-3-3 adaptors function as scaffolds to stabilize CSR enzymatic elements on S regions. Here we demonstrate that all seven 14-3-3β, 14-3-3ε, 14-3-3γ, 14-3-3η, 14-3-3σ, 14-3-3τ and 14-3-3ζ adaptors directly interacted with AID, PKA-Cα (catalytic subunit and PKA-RIα (regulatory inhibitory subunit and uracil DNA glycosylase (Ung. 14-3-3 adaptors, however, did not interact with AID C-terminal truncation mutant AIDΔ(180-198 or AIDF193A and AIDL196A point-mutants (which have been shown not to bind to S region DNA and fail to mediate CSR. 14-3-3 adaptors colocalized with AID and replication protein A (RPA in B cells undergoing CSR. 14-3-3 and AID binding to S region DNA was disrupted by viral protein R (Vpr, an accessory protein of human immunodeficiency virus type-1 (HIV-1, which inhibited CSR without altering AID expression or germline IH-CH transcription. Accordingly, we demonstrated that 14-3-3 directly interact with Vpr, which in turn, also interact with AID, PKA-Cα and Ung. Altogether, our findings suggest that 14-3-3 adaptors play important scaffold functions and nucleate the assembly of multiple CSR factors on S regions. They also show that such assembly can be disrupted by a viral protein, thereby allowing us to hypothesize that small molecule compounds that specifically block 14-3-3 interactions with AID, PKA and/or Ung can be used to inhibit unwanted CSR.

  17. Scaffold functions of 14-3-3 adaptors in B cell immunoglobulin class switch DNA recombination.

    Science.gov (United States)

    Lam, Tonika; Thomas, Lisa M; White, Clayton A; Li, Guideng; Pone, Egest J; Xu, Zhenming; Casali, Paolo

    2013-01-01

    Class switch DNA recombination (CSR) of the immunoglobulin heavy chain (IgH) locus crucially diversifies antibody biological effector functions. CSR involves the induction of activation-induced cytidine deaminase (AID) expression and AID targeting to switch (S) regions by 14-3-3 adaptors. 14-3-3 adaptors specifically bind to 5'-AGCT-3' repeats, which make up for the core of all IgH locus S regions. They selectively target the upstream and downstream S regions that are set to undergo S-S DNA recombination. We hypothesized that 14-3-3 adaptors function as scaffolds to stabilize CSR enzymatic elements on S regions. Here we demonstrate that all seven 14-3-3β, 14-3-3ε, 14-3-3γ, 14-3-3η, 14-3-3σ, 14-3-3τ and 14-3-3ζ adaptors directly interacted with AID, PKA-Cα (catalytic subunit) and PKA-RIα (regulatory inhibitory subunit) and uracil DNA glycosylase (Ung). 14-3-3 adaptors, however, did not interact with AID C-terminal truncation mutant AIDΔ(180-198) or AIDF193A and AIDL196A point-mutants (which have been shown not to bind to S region DNA and fail to mediate CSR). 14-3-3 adaptors colocalized with AID and replication protein A (RPA) in B cells undergoing CSR. 14-3-3 and AID binding to S region DNA was disrupted by viral protein R (Vpr), an accessory protein of human immunodeficiency virus type-1 (HIV-1), which inhibited CSR without altering AID expression or germline IH-CH transcription. Accordingly, we demonstrated that 14-3-3 directly interact with Vpr, which in turn, also interact with AID, PKA-Cα and Ung. Altogether, our findings suggest that 14-3-3 adaptors play important scaffold functions and nucleate the assembly of multiple CSR factors on S regions. They also show that such assembly can be disrupted by a viral protein, thereby allowing us to hypothesize that small molecule compounds that specifically block 14-3-3 interactions with AID, PKA and/or Ung can be used to inhibit unwanted CSR.

  18. Evaluation of clustering algorithms for protein-protein interaction networks

    Directory of Open Access Journals (Sweden)

    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

  19. Protein Co-Expression Network Analysis (ProCoNA)

    Energy Technology Data Exchange (ETDEWEB)

    Gibbs, David L.; Baratt, Arie; Baric, Ralph; Kawaoka, Yoshihiro; Smith, Richard D.; Orwoll, Eric S.; Katze, Michael G.; Mcweeney, Shannon K.

    2013-06-01

    Biological networks are important for elucidating disease etiology due to their ability to model complex high dimensional data and biological systems. Proteomics provides a critical data source for such models, but currently lacks robust de novo methods for network construction, which could bring important insights in systems biology. We have evaluated the construction of network models using methods derived from weighted gene co-expression network analysis (WGCNA). We show that approximately scale-free peptide networks, composed of statistically significant modules, are feasible and biologically meaningful using two mouse lung experiments and one human plasma experiment. Within each network, peptides derived from the same protein are shown to have a statistically higher topological overlap and concordance in abundance, which is potentially important for inferring protein abundance. The module representatives, called eigenpeptides, correlate significantly with biological phenotypes. Furthermore, within modules, we find significant enrichment for biological function and known interactions (gene ontology and protein-protein interactions). Biological networks are important tools in the analysis of complex systems. In this paper we evaluate the application of weighted co-expression network analysis to quantitative proteomics data. Protein co-expression networks allow novel approaches for biological interpretation, quality control, inference of protein abundance, a framework for potentially resolving degenerate peptide-protein mappings, and a biomarker signature discovery.

  20. Combining neural networks for protein secondary structure prediction

    DEFF Research Database (Denmark)

    Riis, Søren Kamaric

    1995-01-01

    In this paper structured neural networks are applied to the problem of predicting the secondary structure of proteins. A hierarchical approach is used where specialized neural networks are designed for each structural class and then combined using another neural network. The submodels are designed...

  1. Topological Analyses of Protein-Ligand Binding: a Network Approach.

    Science.gov (United States)

    Costanzi, Stefano

    2016-01-01

    Proteins can be conveniently represented as networks of interacting residues, thus allowing the study of several network parameters that can shed light onto several of their structural and functional aspects. With respect to the binding of ligands, which are central for the function of many proteins, network analysis may constitute a possible route to assist the identification of binding sites. As the bulk of this review illustrates, this has generally been easier for enzymes than for non-enzyme proteins, perhaps due to the different topological nature of the binding sites of the former over those of the latter. The article also illustrates how network representations of binding sites can be used to search PDB structures in order to identify proteins that bind similar molecules and, lastly, how codifying proteins as networks can assist the analysis of the conformational changes consequent to ligand binding.

  2. 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.

  3. Towards a matrix mechanics framework for dynamic protein network

    OpenAIRE

    Bhattacharya, Sanjoy K.

    2010-01-01

    Protein–protein interaction networks are currently visualized by software generated interaction webs based upon static experimental data. Current state is limited to static, mostly non-compartmental network and non time resolved protein interactions. A satisfactory mathematical foundation for particle interactions within a viscous liquid state (situation within the cytoplasm) does not exist nor do current computer programs enable building dynamic interaction networks for time resolved interac...

  4. Visualizing and Clustering Protein Similarity Networks: Sequences, Structures, and Functions.

    Science.gov (United States)

    Mai, Te-Lun; Hu, Geng-Ming; Chen, Chi-Ming

    2016-07-01

    Research in the recent decade has demonstrated the usefulness of protein network knowledge in furthering the study of molecular evolution of proteins, understanding the robustness of cells to perturbation, and annotating new protein functions. In this study, we aimed to provide a general clustering approach to visualize the sequence-structure-function relationship of protein networks, and investigate possible causes for inconsistency in the protein classifications based on sequences, structures, and functions. Such visualization of protein networks could facilitate our understanding of the overall relationship among proteins and help researchers comprehend various protein databases. As a demonstration, we clustered 1437 enzymes by their sequences and structures using the minimum span clustering (MSC) method. The general structure of this protein network was delineated at two clustering resolutions, and the second level MSC clustering was found to be highly similar to existing enzyme classifications. The clustering of these enzymes based on sequence, structure, and function information is consistent with each other. For proteases, the Jaccard's similarity coefficient is 0.86 between sequence and function classifications, 0.82 between sequence and structure classifications, and 0.78 between structure and function classifications. From our clustering results, we discussed possible examples of divergent evolution and convergent evolution of enzymes. Our clustering approach provides a panoramic view of the sequence-structure-function network of proteins, helps visualize the relation between related proteins intuitively, and is useful in predicting the structure and function of newly determined protein sequences. PMID:27267620

  5. Enhancing the functional content of eukaryotic protein interaction networks.

    Directory of Open Access Journals (Sweden)

    Gaurav Pandey

    Full Text Available 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 100 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 HC.cont 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.

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

    OpenAIRE

    Peng Liu; Lei Yang; Daming Shi; Xianglong Tang

    2015-01-01

    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 net...

  7. Connectivity of neutral networks and structural conservation in protein evolution

    OpenAIRE

    Bastolla, Ugo; Porto, Markus; Roman, H. Eduardo; Vendruscolo, Michele

    2001-01-01

    Protein structures are much more conserved than sequences during evolution. Based on this observation, we investigate the consequences of structural conservation on protein evolution. We study seven of the most studied protein folds, finding out that an extended neutral network in sequence space is associated to each of them. Within our model, neutral evolution leads to a non-Poissonian substitution process, due to the broad distribution of connectivities in neutral networks. The observation ...

  8. Functional organization and its implication in evolution of the human protein-protein interaction network

    OpenAIRE

    Zhao Yiqiang; Mooney Sean D

    2012-01-01

    Abstract Background Based on the distinguishing properties of protein-protein interaction networks such as power-law degree distribution and modularity structure, several stochastic models for the evolution of these networks have been purposed, motivated by the idea that a validated model should reproduce similar topological properties of the empirical network. However, being able to capture topological properties does not necessarily mean it correctly reproduces how networks emerge and evolv...

  9. Crystal structure of Toll-like receptor adaptor MAL/TIRAP reveals the molecular basis for signal transduction and disease protection

    OpenAIRE

    Valkov, Eugene; Stamp, Anna; DiMaio, Frank; Baker, David; Verstak, Brett; Roversi, Pietro; Kellie, Stuart; Sweet, Matthew J.; Mansell, Ashley; Gay, Nicholas J.; Jennifer L Martin; Kobe, Bostjan

    2011-01-01

    Initiation of the innate immune response requires agonist recognition by pathogen-recognition receptors such as the Toll-like receptors (TLRs). Toll/interleukin-1 receptor (TIR) domain-containing adaptors are critical in orchestrating the signal transduction pathways after TLR and interleukin-1 receptor activation. Myeloid differentiation primary response gene 88 (MyD88) adaptor-like (MAL)/TIR domain-containing adaptor protein (TIRAP) is involved in bridging MyD88 to TLR2 and TLR4 in response...

  10. Profiling of Protein Interaction Networks of Protein Complexes Using Affinity Purification and Quantitative Mass Spectrometry*

    OpenAIRE

    Kaake, Robyn M; Wang, Xiaorong; Huang, Lan

    2010-01-01

    Protein-protein interactions are important for nearly all biological processes, and it is known that aberrant protein-protein interactions can lead to human disease and cancer. Recent evidence has suggested that protein interaction interfaces describe a new class of attractive targets for drug development. Full characterization of protein interaction networks of protein complexes and their dynamics in response to various cellular cues will provide essential information for us to understand ho...

  11. Adding protein context to the human protein-protein interaction network to reveal meaningful interactions.

    Directory of Open Access Journals (Sweden)

    Martin H Schaefer

    Full Text Available Interactions of proteins regulate signaling, catalysis, gene expression and many other cellular functions. Therefore, characterizing the entire human interactome is a key effort in current proteomics research. This challenge is complicated by the dynamic nature of protein-protein interactions (PPIs, which are conditional on the cellular context: both interacting proteins must be expressed in the same cell and localized in the same organelle to meet. Additionally, interactions underlie a delicate control of signaling pathways, e.g. by post-translational modifications of the protein partners - hence, many diseases are caused by the perturbation of these mechanisms. Despite the high degree of cell-state specificity of PPIs, many interactions are measured under artificial conditions (e.g. yeast cells are transfected with human genes in yeast two-hybrid assays or even if detected in a physiological context, this information is missing from the common PPI databases. To overcome these problems, we developed a method that assigns context information to PPIs inferred from various attributes of the interacting proteins: gene expression, functional and disease annotations, and inferred pathways. We demonstrate that context consistency correlates with the experimental reliability of PPIs, which allows us to generate high-confidence tissue- and function-specific subnetworks. We illustrate how these context-filtered networks are enriched in bona fide pathways and disease proteins to prove the ability of context-filters to highlight meaningful interactions with respect to various biological questions. We use this approach to study the lung-specific pathways used by the influenza virus, pointing to IRAK1, BHLHE40 and TOLLIP as potential regulators of influenza virus pathogenicity, and to study the signalling pathways that play a role in Alzheimer's disease, identifying a pathway involving the altered phosphorylation of the Tau protein. Finally, we provide the

  12. Evidence of probabilistic behaviour in protein interaction networks

    Directory of Open Access Journals (Sweden)

    Reifman Jaques

    2008-01-01

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

  13. Simulated evolution of protein-protein interaction networks with realistic topology.

    Science.gov (United States)

    Peterson, G Jack; Pressé, Steve; Peterson, Kristin S; Dill, Ken A

    2012-01-01

    We model the evolution of eukaryotic protein-protein interaction (PPI) networks. In our model, PPI networks evolve by two known biological mechanisms: (1) Gene duplication, which is followed by rapid diversification of duplicate interactions. (2) Neofunctionalization, in which a mutation leads to a new interaction with some other protein. Since many interactions are due to simple surface compatibility, we hypothesize there is an increased likelihood of interacting with other proteins in the target protein's neighborhood. We find good agreement of the model on 10 different network properties compared to high-confidence experimental PPI networks in yeast, fruit flies, and humans. Key findings are: (1) PPI networks evolve modular structures, with no need to invoke particular selection pressures. (2) Proteins in cells have on average about 6 degrees of separation, similar to some social networks, such as human-communication and actor networks. (3) Unlike social networks, which have a shrinking diameter (degree of maximum separation) over time, PPI networks are predicted to grow in diameter. (4) The model indicates that evolutionarily old proteins should have higher connectivities and be more centrally embedded in their networks. This suggests a way in which present-day proteomics data could provide insights into biological evolution.

  14. Simulated evolution of protein-protein interaction networks with realistic topology.

    Directory of Open Access Journals (Sweden)

    G Jack Peterson

    Full Text Available We model the evolution of eukaryotic protein-protein interaction (PPI networks. In our model, PPI networks evolve by two known biological mechanisms: (1 Gene duplication, which is followed by rapid diversification of duplicate interactions. (2 Neofunctionalization, in which a mutation leads to a new interaction with some other protein. Since many interactions are due to simple surface compatibility, we hypothesize there is an increased likelihood of interacting with other proteins in the target protein's neighborhood. We find good agreement of the model on 10 different network properties compared to high-confidence experimental PPI networks in yeast, fruit flies, and humans. Key findings are: (1 PPI networks evolve modular structures, with no need to invoke particular selection pressures. (2 Proteins in cells have on average about 6 degrees of separation, similar to some social networks, such as human-communication and actor networks. (3 Unlike social networks, which have a shrinking diameter (degree of maximum separation over time, PPI networks are predicted to grow in diameter. (4 The model indicates that evolutionarily old proteins should have higher connectivities and be more centrally embedded in their networks. This suggests a way in which present-day proteomics data could provide insights into biological evolution.

  15. Simulated Evolution of Protein-Protein Interaction Networks with Realistic Topology

    OpenAIRE

    G Jack Peterson; Steve Pressé; Peterson, Kristin S.; Dill, Ken A.

    2012-01-01

    We model the evolution of eukaryotic protein-protein interaction (PPI) networks. In our model, PPI networks evolve by two known biological mechanisms: (1) Gene duplication, which is followed by rapid diversification of duplicate interactions. (2) Neofunctionalization, in which a mutation leads to a new interaction with some other protein. Since many interactions are due to simple surface compatibility, we hypothesize there is an increased likelihood of interacting with other proteins in the t...

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

    Directory of Open Access Journals (Sweden)

    Hidenori Ohnishi

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

  17. A conserved protein interaction network involving the yeast MAP kinases Fus3 and Kss1

    OpenAIRE

    Kusari, A B; D. M. Molina; W Sabbagh; Lau, C S; Bardwell, Lee

    2004-01-01

    The Saccharomyces cerevisiae mitogen-activated protein kinases (MAPKs) Fus3 and Kss1 bind to multiple regulators and substrates. We show that mutations in a conserved docking site in these MAPKs (the CD/7rn region) disrupt binding to an important subset of their binding partners, including the Ste7 MAPK kinase, the Ste5 adaptor/scaffold protein, and the Dig1 and Dig2 transcriptional repressors. Supporting the possibility that Ste5 and Ste7 bind to the same region of the MAPKs, they partially ...

  18. PANADA: protein association network annotation, determination and analysis.

    Directory of Open Access Journals (Sweden)

    Alberto J M Martin

    Full Text Available Increasingly large numbers of proteins require methods for functional annotation. This is typically based on pairwise inference from the homology of either protein sequence or structure. Recently, similarity networks have been presented to leverage both the ability to visualize relationships between proteins and assess the transferability of functional inference. Here we present PANADA, a novel toolkit for the visualization and analysis of protein similarity networks in Cytoscape. Networks can be constructed based on pairwise sequence or structural alignments either on a set of proteins or, alternatively, by database search from a single sequence. The Panada web server, executable for download and examples and extensive help files are available at URL: http://protein.bio.unipd.it/panada/.

  19. Protein interaction networks--more than mere modules.

    Directory of Open Access Journals (Sweden)

    Stefan Pinkert

    2010-01-01

    Full Text Available It is widely believed that the modular organization of cellular function is reflected in a modular structure of molecular networks. A common view is that a "module" in a network is a cohesively linked group of nodes, densely connected internally and sparsely interacting with the rest of the network. Many algorithms try to identify functional modules in protein-interaction networks (PIN by searching for such cohesive groups of proteins. Here, we present an alternative approach independent of any prior definition of what actually constitutes a "module". In a self-consistent manner, proteins are grouped into "functional roles" if they interact in similar ways with other proteins according to their functional roles. Such grouping may well result in cohesive modules again, but only if the network structure actually supports this. We applied our method to the PIN from the Human Protein Reference Database (HPRD and found that a representation of the network in terms of cohesive modules, at least on a global scale, does not optimally represent the network's structure because it focuses on finding independent groups of proteins. In contrast, a decomposition into functional roles is able to depict the structure much better as it also takes into account the interdependencies between roles and even allows groupings based on the absence of interactions between proteins in the same functional role. This, for example, is the case for transmembrane proteins, which could never be recognized as a cohesive group of nodes in a PIN. When mapping experimental methods onto the groups, we identified profound differences in the coverage suggesting that our method is able to capture experimental bias in the data, too. For example yeast-two-hybrid data were highly overrepresented in one particular group. Thus, there is more structure in protein-interaction networks than cohesive modules alone and we believe this finding can significantly improve automated function

  20. Dissipative electro-elastic network model of protein electrostatics

    CERN Document Server

    Martin, Daniel R; Matyushov, Dmitry V

    2011-01-01

    We propose a dissipative electro-elastic network model (DENM) to describe the dynamics and statistics of electrostatic fluctuations at active sites of proteins. The model combines the harmonic network of residue beads with overdamped dynamics of the normal modes of the network characterized by two friction coefficients. The electrostatic component is introduced to the model through atomic charges of the protein force field. The overall effect of the electrostatic fluctuations of the network is recorded through the frequency-dependent response functions of the electrostatic potential and electric field at the active site. We also consider the dynamics of displacements of individual residues in the network and the dynamics of distances between pairs of residues. The model is tested against loss spectra of residue displacements and the electrostatic potential and electric field at the heme's iron from all-atom molecular dynamics simulations of three hydrated globular proteins.

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

    Directory of Open Access Journals (Sweden)

    Wang Ding

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

  2. Nck adaptors are positive regulators of the size and sensitivity of the T-cell repertoire

    OpenAIRE

    Roy, Edwige; Togbe, Dieudonnée; Holdorf, Amy D.; Trubetskoy, Dmitry; Nabti, Sabrina; Küblbeck, Günter; Klevenz, Alexandra; Kopp-Schneider, Annette; Leithäuser, Frank; Möller, Peter; Bladt, Friedhelm; Hämmerling, Günter; Arnold, Bernd; Pawson, Tony; Tafuri, Anna

    2010-01-01

    The size and sensitivity of the T-cell repertoire governs the effectiveness of immune responses against invading pathogens. Both are modulated by T-cell receptor (TCR) activity through molecular mechanisms, which remain unclear. Here, we provide genetic evidence that the SH2/SH3 domain containing proteins Nck lower the threshold of T-cell responsiveness. The hallmarks of Nck deletion were T-cell lymphopenia and hyporeactivity to TCR-mediated stimulation. In the absence of the Nck adaptors, pe...

  3. 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.

  4. Finding finer functions for partially characterized proteins by protein-protein interaction networks

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    Based on high-throughput data, numerous algorithms have been designed to find functions of novel proteins. However, the effectiveness of such algorithms is currently limited by some fundamental factors, including (1) the low a-priori probability of novel proteins participating in a detailed function; (2) the huge false data present in high-throughput datasets; (3) the incomplete data coverage of functional classes; (4) the abundant but heterogeneous negative samples for training the algorithms; and (5) the lack of detailed functional knowledge for training algorithms. Here, for partially characterized proteins, we suggest an approach to finding their finer functions based on protein interaction sub-networks or gene expression patterns, defined in function-specific subspaces. The proposed approach can lessen the above-mentioned problems by properly defining the prediction range and functionally filtering the noisy data, and thus can efficiently find proteins' novel functions. For thousands of yeast and human proteins partially characterized, it is able to reliably find their finer functions (e.g., the translational functions) with more than 90% precision. The predicted finer functions are highly valuable both for guiding the follow-up wet-lab validation and for providing the necessary data for training algorithms to learn other proteins.

  5. Characterization of Protein-Protein Interfaces through a Protein Contact Network Approach.

    Science.gov (United States)

    Di Paola, Luisa; Platania, Chiara Bianca Maria; Oliva, Gabriele; Setola, Roberto; Pascucci, Federica; Giuliani, Alessandro

    2015-01-01

    Anthrax toxin comprises three different proteins, jointly acting to exert toxic activity: a non-toxic protective agent (PA), toxic edema factor (EF), and lethal factor (LF). Binding of PA to anthrax receptors promotes oligomerization of PA, binding of EF and LF, and then endocytosis of the complex. Homomeric forms of PA, complexes of PA bound to LF and to the endogenous receptor capillary morphogenesis gene 2 (CMG2) were analyzed. In this work, we characterized protein-protein interfaces (PPIs) and identified key residues at PPIs of complexes, by means of a protein contact network (PCN) approach. Flexibility and global and local topological properties of each PCN were computed. The vulnerability of each PCN was calculated using different node removal strategies, with reference to specific PCN topological descriptors, such as participation coefficient, contact order, and degree. The participation coefficient P, the topological descriptor of the node's ability to intervene in protein inter-module communication, was the key descriptor of PCN vulnerability of all structures. High P residues were localized both at PPIs and other regions of complexes, so that we argued an allosteric mechanism in protein-protein interactions. The identification of residues, with key role in the stability of PPIs, has a huge potential in the development of new drugs, which would be designed to target not only PPIs but also residues localized in allosteric regions of supramolecular complexes.

  6. A quantitative approach to study indirect effects among disease proteins in the human protein interaction network

    Directory of Open Access Journals (Sweden)

    Jordán Ferenc

    2010-07-01

    Full Text Available Abstract Background Systems biology makes it possible to study larger and more intricate systems than before, so it is now possible to look at the molecular basis of several diseases in parallel. Analyzing the interaction network of proteins in the cell can be the key to understand how complex processes lead to diseases. Novel tools in network analysis provide the possibility to quantify the key interacting proteins in large networks as well as proteins that connect them. Here we suggest a new method to study the relationships between topology and functionality of the protein-protein interaction network, by identifying key mediator proteins possibly maintaining indirect relationships among proteins causing various diseases. Results Based on the i2d and OMIM databases, we have constructed (i a network of proteins causing five selected diseases (DP, disease proteins plus their interacting partners (IP, non-disease proteins, the DPIP network and (ii a protein network showing only these IPs and their interactions, the IP network. The five investigated diseases were (1 various cancers, (2 heart diseases, (3 obesity, (4 diabetes and (5 autism. We have quantified the number and strength of IP-mediated indirect effects between the five groups of disease proteins and hypothetically identified the most important mediator proteins linking heart disease to obesity or diabetes in the IP network. The results present the relationship between mediator role and centrality, as well as between mediator role and functional properties of these proteins. Conclusions We show that a protein which plays an important indirect mediator role between two diseases is not necessarily a hub in the PPI network. This may suggest that, even if hub proteins and disease proteins are trivially of great interest, mediators may also deserve more attention, especially if disease-disease associations are to be understood. Identifying the hubs may not be sufficient to understand

  7. An analysis pipeline for the inferenceof protein-protein interaction networks

    Energy Technology Data Exchange (ETDEWEB)

    Taylor, Ronald C. [Pacific Northwest National Laboratory (PNNL); Singhal, Mudita [Pacific Northwest National Laboratory (PNNL); Daly, Don S. [Pacific Northwest National Laboratory (PNNL); Gilmore, Jason [Pacific Northwest National Laboratory (PNNL); Cannon, Bill [Pacific Northwest National Laboratory (PNNL); Domico, Kelly [Pacific Northwest National Laboratory (PNNL); White, Amanda M. [Pacific Northwest National Laboratory (PNNL); Auberry, Deanna L [ORNL; Auberry, Kenneth J [ORNL; Hooker, Brian [Pacific Northwest National Laboratory (PNNL); Hurst, Gregory {Greg} B [ORNL; McDermott, Jason [Pacific Northwest National Laboratory (PNNL); McDonald, W Hayes [ORNL; Pelletier, Dale A [ORNL; Schmoyer, Denise D [ORNL; Wiley, Steven [Pacific Northwest National Laboratory (PNNL)

    2009-09-01

    We present an integrated platform that is used for the reconstruction and analysis of protein-protein interaction networks inferred from Mass Spectrometry (MS) bait-prey experiment data. At the heart of this pipeline is 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. Among the many algorithms available in SEBINI is the Bayesian Estimator of Probabilities of Protein-Protein Associations (BEPro3) algorithm, which is used to infer interaction networks from such MS affinity isolation data. For integration, comparison and analysis of the inferred protein-protein interactions with interaction evidence obtained from multiple public sources, the pipeline connects to the Collective Analysis of Biological Interaction Networks (CABIN) software. Incorporating BEPro3 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 MS bait-prey experiments.

  8. Bias tradeoffs in the creation and analysis of protein-protein interaction networks

    OpenAIRE

    Gillis, Jesse; Ballouz, Sara; Pavlidis, Paul

    2014-01-01

    Networks constructed from aggregated protein-protein interaction data are commonplace in biology. But the studies these data are derived from were conducted with their own hypotheses and foci. Focusing on data from budding yeast present in BioGRID, we determine that many of the downstream signals present in network data are significantly impacted by biases in the original data. We determine the degree to which selection bias in favor of biologically interesting bait proteins goes down with st...

  9. Optimization of multiplexed RADseq libraries using low-cost adaptors.

    Science.gov (United States)

    Henri, Hélène; Cariou, Marie; Terraz, Gabriel; Martinez, Sonia; El Filali, Adil; Veyssiere, Marine; Duret, Laurent; Charlat, Sylvain

    2015-04-01

    Reduced representation genomics approaches, of which RADseq is currently the most popular form, offer the possibility to produce genome wide data from potentially any species, without previous genomic information. The application of RADseq to highly multiplexed libraries (including numerous specimens, and potentially numerous different species) is however limited by technical constraints. First, the cost of synthesis of Illumina adaptors including molecular identifiers (MIDs) becomes excessive when numerous specimens are to be multiplexed. Second, the necessity to empirically adjust the ratio of adaptors to genomic DNA concentration impedes the high throughput application of RADseq to heterogeneous samples, of variable DNA concentration and quality. In an attempt to solve these problems, we propose here some adjustments regarding the adaptor synthesis. First, we show that the common and unique (MID) parts of adaptors can be synthesized separately and subsequently ligated, which drastically reduces the synthesis cost, and thus allows multiplexing hundreds of specimens. Second, we show that self-ligation of adaptors, which makes the adaptor concentration so critical, can be simply prevented by using unphosphorylated adaptors, which significantly improves the ligation and sequencing yield.

  10. Accuracy improvement in protein complex prediction from protein interaction networks by refining cluster overlaps

    OpenAIRE

    Chiam Tak; Cho Young-Rae

    2012-01-01

    Abstract Background Recent computational techniques have facilitated analyzing genome-wide protein-protein interaction data for several model organisms. Various graph-clustering algorithms have been applied to protein interaction networks on the genomic scale for predicting the entire set of potential protein complexes. In particular, the density-based clustering algorithms which are able to generate overlapping clusters, i.e. the clusters sharing a set of nodes, are well-suited to protein co...

  11. Predicting and validating protein interactions using network structure.

    Directory of Open Access Journals (Sweden)

    Pao-Yang Chen

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

  12. Properties of Fibrillar Protein Assemblies and their Percolating Networks

    NARCIS (Netherlands)

    Veerman, C.

    2004-01-01

    Properties of Fibrillar Protein Assemblies and their Percolating Networks. PhD thesis, Wageningen University, The Netherlands Keywords: bovine serum albumin, complex fluids, excluded volume, fibrils, gels, innovation, b-lactoglobulin, ovalbumin, percolation, proteins, rheology, rheo-optics, self-ass

  13. Programming Molecular Association and Viscoelastic Behavior in Protein Networks.

    Science.gov (United States)

    Dooling, Lawrence J; Buck, Maren E; Zhang, Wen-Bin; Tirrell, David A

    2016-06-01

    A set of recombinant artificial proteins that can be cross-linked, by either covalent bonds or association of helical domains or both, is described. The designed proteins can be used to construct molecular networks in which the mechanism of crosslinking determines the time-dependent responses to mechanical deformation. PMID:27061171

  14. Topological features of proteins from amino acid residue networks

    CERN Document Server

    Alves, N A; Alves, Nelson Augusto; Martinez, Alexandre Souto

    2006-01-01

    Topological properties of native folds are obtained from statistical analysis of 160 low homology proteins covering the four structural classes. This is done analysing one, two and three-vertex joint distribution of quantities related to the corresponding network of amino acid residues. Emphasis on the amino acid residue hydrophobicity leads to the definition of their center of mass as vertices in this contact network model with interactions represented by edges. The network analysis helps us to interpret experimental results such as hydrophobic scales and fraction of buried accessible surface area in terms of the network connectivity. To explore the vertex type dependent correlations, we build a network of hydrophobic and polar vertices. This procedure presents the wiring diagram of the topological structure of globular proteins leading to the following attachment probabilities between hydrophobic-hydrophobic 0.424(5), hydrophobic-polar 0.419(2) and polar-polar 0.157(3) residues.

  15. SLIDER: Mining correlated motifs in protein-protein interaction networks

    NARCIS (Netherlands)

    Boyen, P.; Dijk, van A.D.J.; Ham, van R.C.H.J.; Neven, F.

    2009-01-01

    Abstract—Correlated motif mining (CMM) is the problem to find overrepresented pairs of patterns, called motif pairs, in interacting protein sequences. Algorithmic solutions for CMM thereby provide a computational method for predicting binding sites for protein interaction. In this paper, we adopt a

  16. Vps10p Transport from the trans-Golgi Network to the Endosome Is Mediated by Clathrin-coated Vesicles

    OpenAIRE

    Deloche, Olivier; Yeung, Bonny G.; Payne, Gregory S.; Schekman, Randy

    2001-01-01

    A native immunoisolation procedure has been used to investigate the role of clathrin-coated vesicles (CCVs) in the transport of vacuolar proteins between the trans-Golgi network (TGN) and the prevacuolar/endosome compartments in the yeast Saccharomyces cerevisiae. We find that Apl2p, one large subunit of the adaptor protein-1 complex, and Vps10p, the carboxypeptidase Y vacuolar protein receptor, are associated with clathrin molecules. Vps10p packaging in CCVs is re...

  17. Nck adaptors are positive regulators of the size and sensitivity of the T-cell repertoire.

    Science.gov (United States)

    Roy, Edwige; Togbe, Dieudonnée; Holdorf, Amy D; Trubetskoy, Dmitry; Nabti, Sabrina; Küblbeck, Günter; Klevenz, Alexandra; Kopp-Schneider, Annette; Leithäuser, Frank; Möller, Peter; Bladt, Friedhelm; Hämmerling, Günter; Arnold, Bernd; Pawson, Tony; Tafuri, Anna

    2010-08-31

    The size and sensitivity of the T-cell repertoire governs the effectiveness of immune responses against invading pathogens. Both are modulated by T-cell receptor (TCR) activity through molecular mechanisms, which remain unclear. Here, we provide genetic evidence that the SH2/SH3 domain containing proteins Nck lower the threshold of T-cell responsiveness. The hallmarks of Nck deletion were T-cell lymphopenia and hyporeactivity to TCR-mediated stimulation. In the absence of the Nck adaptors, peripheral T cells expressing a TCR with low avidity for self-antigens were strongly reduced, whereas an overall impairment of T-cell activation by weak antigenic stimulation was observed. Mechanistically, Nck deletion resulted in a significant decrease in calcium mobilization and ERK phosphorylation upon TCR engagement. Taken together, our findings unveil a crucial role for the Nck adaptors in shaping the T-cell repertoire to ensure maximal antigenic coverage and optimal T cell excitability. PMID:20709959

  18. Nck adaptors are positive regulators of the size and sensitivity of the T-cell repertoire.

    Science.gov (United States)

    Roy, Edwige; Togbe, Dieudonnée; Holdorf, Amy D; Trubetskoy, Dmitry; Nabti, Sabrina; Küblbeck, Günter; Klevenz, Alexandra; Kopp-Schneider, Annette; Leithäuser, Frank; Möller, Peter; Bladt, Friedhelm; Hämmerling, Günter; Arnold, Bernd; Pawson, Tony; Tafuri, Anna

    2010-08-31

    The size and sensitivity of the T-cell repertoire governs the effectiveness of immune responses against invading pathogens. Both are modulated by T-cell receptor (TCR) activity through molecular mechanisms, which remain unclear. Here, we provide genetic evidence that the SH2/SH3 domain containing proteins Nck lower the threshold of T-cell responsiveness. The hallmarks of Nck deletion were T-cell lymphopenia and hyporeactivity to TCR-mediated stimulation. In the absence of the Nck adaptors, peripheral T cells expressing a TCR with low avidity for self-antigens were strongly reduced, whereas an overall impairment of T-cell activation by weak antigenic stimulation was observed. Mechanistically, Nck deletion resulted in a significant decrease in calcium mobilization and ERK phosphorylation upon TCR engagement. Taken together, our findings unveil a crucial role for the Nck adaptors in shaping the T-cell repertoire to ensure maximal antigenic coverage and optimal T cell excitability.

  19. Construction of a chloroplast protein interaction network and functional mining of photosynthetic proteins in Arabidopsis thaliana

    Institute of Scientific and Technical Information of China (English)

    Qing-Bo Yu; Yong-Lan Cui; Kang Chong; Yi-Xue Li; Yu-Hua Li; Zhongming Zhao; Tie-Liu Shi; Zhong-Nan Yang; Guang Li; Guan Wang; Jing-Chun Sun; Peng-Cheng Wang; Chen Wang; Hua-Ling Mi; Wei-Min Ma; Jian Cui

    2008-01-01

    Chloroplast is a typical plant cell organeUe where photosynthesis takes place.In this study,a total of 1 808 chloroplast core proteins in Arabidopsis thaliana were reliably identified by combining the results of previously published studies and our own predictions.We then constructed a chloroplast protein interaction network primarily based on these core protein interactions.The network had 22 925 protein interaction pairs which involved 2 214 proteins.A total of 160 previously uncharacterized proteins were annotated in this network.The subunits of the photosynthetic complexes were modularized,and the functional relationships among photosystem Ⅰ (PSI),photosystem Ⅱ (PSII),light harvesting complex of photosystem Ⅰ (LHC Ⅰ) and light harvesting complex of photosystem Ⅰ (LHC Ⅱ) could be deduced from the predicted protein interactions in this network.We further confirmed an interaction between an unknown protein AT1G52220 and a photosynthetic subunit PSI-D2 by yeast two-hybrid analysis.Our chloroplast protein interaction network should be useful for functional mining of photosynthetic proteins and investigation of chloroplast-related functions at the systems biology level in Arabidopsis.

  20. 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.

  1. Reconstruction of Protein Networks Using Reverse-Phase Protein Array Data.

    Science.gov (United States)

    von der Heyde, Silvia; Sonntag, Johanna; Kramer, Frank; Bender, Christian; Korf, Ulrike; Beißbarth, Tim

    2016-01-01

    In this chapter, we describe an approach to reconstruct cellular signaling networks based on measurements of protein activation after different stimulation experiments. As experimental platform reverse-phase protein arrays (RPPA) are used. RPPA allow the measurement of proteins and phosphoproteins across many samples in parallel with minimal sample consumption using a panel of highly target protein-specific antibodies. Functional interactions of proteins are modeled using a Boolean network. We describe the Boolean network reconstruction approach ddepn (dynamic deterministic effects propagation networks), which uses time course data to derive protein interactions based on perturbation experiments. We explain how the method works, give a practical application example, and describe how the results can be interpreted. Furthermore prior knowledge on signaling pathways is essential for network reconstruction. Here we describe the use of our software rBiopaxParser to integrate prior knowledge on protein signaling available in public databases. All applied methods are freely available as open-source R software packages. We describe the preparation of RPPA data as well as all relevant programming steps to format the RPPA data, to infer the prior knowledge, and to reconstruct and analyze the protein signaling networks. PMID:26519181

  2. Creative elements: network-based predictions of active centres in proteins, cellular and social networks

    CERN Document Server

    Csermely, Peter

    2008-01-01

    Active centres and hot spots of proteins have a paramount importance in enzyme action, protein complex formation and drug design. Recently a number of publications successfully applied the analysis of residue networks to predict active centres in proteins. Most real-world networks show a number of properties, such as small-worldness or scale-free degree distribution, which are rather general features of networks from molecules to the society. Based on extensive analogies I propose that the existing findings and methodology enable us to detect active centres in cells, social networks and ecosystems. Members of these active centres are creative elements of the respective networks, which may help them to survive unprecedented, novel challenges, and play a key role in the development, survival and evolvability of complex systems.

  3. 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.

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

    Directory of Open Access Journals (Sweden)

    Pike Andrew D

    2010-06-01

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

  5. The adaptor molecule CARD9 is essential for tuberculosis control

    OpenAIRE

    Dorhoi, Anca; Desel, Christiane; Yeremeev, Vladimir; Pradl, Lydia; Brinkmann, Volker; Mollenkopf, Hans J; Hanke, Karin; Gross, Olaf; Ruland, Jürgen; Stefan H. E. Kaufmann

    2010-01-01

    The cross talk between host and pathogen starts with recognition of bacterial signatures through pattern recognition receptors (PRRs), which mobilize downstream signaling cascades. We investigated the role of the cytosolic adaptor caspase recruitment domain family, member 9 (CARD9) in tuberculosis. This adaptor was critical for full activation of innate immunity by converging signals downstream of multiple PRRs. Card9(-/-) mice succumbed early after aerosol infection, with higher mycobacteria...

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

    Directory of Open Access Journals (Sweden)

    Sandip Chakraborty

    2016-01-01

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

  7. Robustness of indispensable nodes in controlling protein-protein interaction network

    CERN Document Server

    Zhang, Xizhe; Yang, Yunyi

    2016-01-01

    Recently, the structural controllability theory has been introduced to analyze the Protein-Protein Interaction (PPI) network. The indispensable nodes, which their removal increase the number of driver nodes to control the network, are found essential in PPI network. However, the PPI network is far from complete and there may exist many false-positive or false-negative interactions, which promotes us to question: are these indispensable nodes robust to structural change? Here we systematically investigate the robustness of indispensable nodes of PPI network by removing and adding possible interactions. We found that the indispensable nodes are sensitive to the structural change and very few edges can change the type of many indispensable nodes. The finding may promote our understanding to the control principle of PPI network.

  8. Discovering Distinct Functional Modules of Specific Cancer Types Using Protein-Protein Interaction Networks

    OpenAIRE

    Ru Shen; Xiaosheng Wang; Chittibabu Guda

    2015-01-01

    Background. The molecular profiles exhibited in different cancer types are very different; hence, discovering distinct functional modules associated with specific cancer types is very important to understand the distinct functions associated with them. Protein-protein interaction networks carry vital information about molecular interactions in cellular systems, and identification of functional modules (subgraphs) in these networks is one of the most important applications of biological networ...

  9. Yeast Gga Coat Proteins Function with Clathrin in Golgi to Endosome Transport

    OpenAIRE

    Costaguta, G; Stefan, C. J.; Bensen, E. S.; Emr, S D; Payne, G S

    2001-01-01

    Gga proteins represent a newly recognized, evolutionarily conserved protein family with homology to the “ear” domain of the clathrin adaptor AP-1 γ subunit. Yeast cells contain two Gga proteins, Gga1p and Gga2p, that have been proposed to act in transport between the trans-Golgi network and endosomes. Here we provide genetic and physical evidence that yeast Gga proteins function in trans-Golgi network clathrin coats. Deletion of Gga2p (gga2Δ), the major Gga protein...

  10. The clathrin adaptor complexes as a paradigm for membrane-associated allostery

    OpenAIRE

    Canagarajah, Bertram J.; Ren, Xuefeng; Bonifacino, Juan S.; Hurley, James H.

    2013-01-01

    The clathrin-associated adaptor protein (AP) complexes AP-1 and AP-2 are two members of a family of heterotetrameric assemblies that connect transmembrane protein cargo to vesicular coats. Cargo binding by AP-1 is activated by the small GTPase Arf1, while AP-2 is activated by the phosphoinositide PI(4,5)P2. The structures of both AP-1 and AP-2 have been determined in their locked and unlocked conformations. The structures show how different activators use different mechanisms to trigger simil...

  11. Lists2Networks: Integrated analysis of gene/protein lists

    Directory of Open Access Journals (Sweden)

    Ma'ayan Avi

    2010-02-01

    Full Text Available Abstract Background Systems biologists are faced with the difficultly of analyzing results from large-scale studies that profile the activity of many genes, RNAs and proteins, applied in different experiments, under different conditions, and reported in different publications. To address this challenge it is desirable to compare the results from different related studies such as mRNA expression microarrays, genome-wide ChIP-X, RNAi screens, proteomics and phosphoproteomics experiments in a coherent global framework. In addition, linking high-content multilayered experimental results with prior biological knowledge can be useful for identifying functional themes and form novel hypotheses. Results We present Lists2Networks, a web-based system that allows users to upload lists of mammalian genes/proteins onto a server-based program for integrated analysis. The system includes web-based tools to manipulate lists with different set operations, to expand lists using existing mammalian networks of protein-protein interactions, co-expression correlation, or background knowledge co-annotation correlation, as well as to apply gene-list enrichment analyses against many gene-list libraries of prior biological knowledge such as pathways, gene ontology terms, kinase-substrate, microRNA-mRAN, and protein-protein interactions, metabolites, and protein domains. Such analyses can be applied to several lists at once against many prior knowledge libraries of gene-lists associated with specific annotations. The system also contains features that allow users to export networks and share lists with other users of the system. Conclusions Lists2Networks is a user friendly web-based software system expected to significantly ease the computational analysis process for experimental systems biologists employing high-throughput experiments at multiple layers of regulation. The system is freely available at http://www.lists2networks.org.

  12. Topological Properties of Protein-Protein and Metabolic Interaction Networks of Drosophila melanogaster

    Institute of Scientific and Technical Information of China (English)

    Thanigaimani Rajarathinam; Yen-Han Lin

    2006-01-01

    The underlying principle governing the natural phenomena of life is one of the critical issues receiving due importance in recent years. A key feature of the scale-free architecture is the vitality of the most connected nodes (hubs). The major objective of this article was to analyze the protein-protein and metabolic interaction networks of Drosophila melanogaster by considering the architectural patterns and the consequence of removal of hubs on the topological parameter of the two interaction systems. Analysis showed that both interaction networks follow a scale-free model, establishing the fact that most real world networks,from varied situations, conform to the small world pattern. The average path length showed a two-fold and a three-fold increase (changing from 9.42 to 20.93 and from 5.29 to 17.75, respectively) for the protein-protein and metabolic interaction networks, respectively, due to the deletion of hubs. On the contrary, the arbitrary elimination of nodes did not show any remarkable disparity in the topological parameter of the protein-protein and metabolic interaction networks (average path length: 9.42±0.02 and 5.27±0.01, respectively). This aberrant behavior for the two cases underscores the significance of the most linked nodes to the natural topology of the networks.

  13. 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.

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

    Science.gov (United States)

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

    2016-06-21

    Cytochrome P450 (CYP) enzymes that degrade xenobiotics play a critical role in the metabolism and biotransformation of drugs and xenobiotics in humans as well as experimental animal models such as mouse and rat. These proteins function as a network collectively as well as independently. Though there are several reports on the organization, regulation and functionality of various CYP enzymes at the molecular level, the understanding of organization and functionality of these proteins at the holistic level remain unclear. The objective of this study is to understand the organization and functionality of xenobiotic degrading CYP enzymes of human, mouse and rat using network theory approaches and to study species differences that exist among them at the holistic level. For our analysis, a protein-protein interaction (PPI) network for CYP enzymes of human, mouse and rat was constructed using the STRING database. Topology, centrality, modularity and robustness analyses were performed for our predicted CYP PPI networks that were then validated by comparison with randomly generated network models. Network centrality analyses of CYP PPI networks reveal the central/hub proteins in the network. Modular analysis of the CYP PPI networks of human, mouse and rat resulted in functional clusters. These clusters were subjected to ontology and pathway enrichment analysis. The analyses show that the cluster of the human CYP PPI network is enriched with pathways principally related to xenobiotic/drug metabolism. Endo-xenobiotic crosstalk dominated in mouse and rat CYP PPI networks, and they were highly enriched with endogenous metabolic and signaling pathways. Thus, cross-species comparisons and analyses of human, mouse and rat CYP PPI networks gave insights about species differences that existed at the holistic level. More investigations from both reductionist and holistic perspectives can help understand CYP metabolism and species extrapolation in a much better way. PMID:27194593

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

    Directory of Open Access Journals (Sweden)

    Leach Sonia M

    2008-06-01

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

  16. Detecting Protein Complexes in Protein Interaction Networks Modeled as Gene Expression Biclusters.

    Science.gov (United States)

    Hanna, Eileen Marie; Zaki, Nazar; Amin, Amr

    2015-01-01

    Developing suitable methods for the detection of protein complexes in protein interaction networks continues to be an intriguing area of research. The importance of this objective originates from the fact that protein complexes are key players in most cellular processes. The more complexes we identify, the better we can understand normal as well as abnormal molecular events. Up till now, various computational methods were designed for this purpose. However, despite their notable performance, questions arise regarding potential ways to improve them, in addition to ameliorative guidelines to introduce novel approaches. A close interpretation leads to the assent that the way in which protein interaction networks are initially viewed should be adjusted. These networks are dynamic in reality and it is necessary to consider this fact to enhance the detection of protein complexes. In this paper, we present "DyCluster", a framework to model the dynamic aspect of protein interaction networks by incorporating gene expression data, through biclustering techniques, prior to applying complex-detection algorithms. The experimental results show that DyCluster leads to higher numbers of correctly-detected complexes with better evaluation scores. The high accuracy achieved by DyCluster in detecting protein complexes is a valid argument in favor of the proposed method. DyCluster is also able to detect biologically meaningful protein groups. The code and datasets used in the study are downloadable from https://github.com/emhanna/DyCluster. PMID:26641660

  17. Detecting Protein Complexes in Protein Interaction Networks Modeled as Gene Expression Biclusters.

    Directory of Open Access Journals (Sweden)

    Eileen Marie Hanna

    Full Text Available Developing suitable methods for the detection of protein complexes in protein interaction networks continues to be an intriguing area of research. The importance of this objective originates from the fact that protein complexes are key players in most cellular processes. The more complexes we identify, the better we can understand normal as well as abnormal molecular events. Up till now, various computational methods were designed for this purpose. However, despite their notable performance, questions arise regarding potential ways to improve them, in addition to ameliorative guidelines to introduce novel approaches. A close interpretation leads to the assent that the way in which protein interaction networks are initially viewed should be adjusted. These networks are dynamic in reality and it is necessary to consider this fact to enhance the detection of protein complexes. In this paper, we present "DyCluster", a framework to model the dynamic aspect of protein interaction networks by incorporating gene expression data, through biclustering techniques, prior to applying complex-detection algorithms. The experimental results show that DyCluster leads to higher numbers of correctly-detected complexes with better evaluation scores. The high accuracy achieved by DyCluster in detecting protein complexes is a valid argument in favor of the proposed method. DyCluster is also able to detect biologically meaningful protein groups. The code and datasets used in the study are downloadable from https://github.com/emhanna/DyCluster.

  18. Identifying functional modules in protein-protein interaction networks: An integrated exact approach

    NARCIS (Netherlands)

    Dittrich, M.; Klau, G.W.; Rosenwald, A.; Dandekar, T.; et al, not CWI

    2008-01-01

    Motivation: With the exponential growth of expression and protein-protein interaction (PPI) data, the frontier of research in system biology shifts more and more to the integrated analysis of these large datasets. Of particular interest is the identification of functional modules in PPI networks, sh

  19. 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.

  20. Simple Protein Complex Purification and Identification Method Suitable for High- throughput Mapping of Protein Interaction Networks

    Energy Technology Data Exchange (ETDEWEB)

    Markillie, Lye Meng; Lin, Chiann Tso; Adkins, Joshua N.; Auberry, Deanna L.; Hill, Eric A.; Hooker, Brian S.; Moore, Priscilla A.; Moore, Ronald J.; Shi, Liang; Wiley, H. S.; Kery, Vladimir

    2005-04-11

    Most of the current methods for purification and identification of protein complexes use endogenous expression of affinity tagged bait, tandem affinity tag purification of protein complexes followed by specific elution of complexes from beads, gel separation, in-gel digestion and mass spectrometric analysis of protein interactors. We propose a single affinity tag in vitro pulldown assay with denaturing elution, trypsin digestion in organic solvent and LC ESI MS/MS protein identification using SEQUEST analysis. Our method is simple, easy to scale up and automate thus suitable for high throughput mapping of protein interaction networks and functional proteomics.

  1. Detecting Protein Complexes in Protein Interaction Networks Modeled as Gene Expression Biclusters

    OpenAIRE

    Eileen Marie Hanna; Nazar Zaki; Amr Amin

    2015-01-01

    Developing suitable methods for the detection of protein complexes in protein interaction networks continues to be an intriguing area of research. The importance of this objective originates from the fact that protein complexes are key players in most cellular processes. The more complexes we identify, the better we can understand normal as well as abnormal molecular events. Up till now, various computational methods were designed for this purpose. However, despite their notable performance, ...

  2. Constructing a robust protein-protein interaction network by integrating multiple public databases

    OpenAIRE

    Ding Don; Tong Weida; Fang Hong; Ye Yanbin; Su Zhenqiang; Guo Li; Liu Zhichao; Martha Venkata-Swamy; Xu Xiaowei

    2011-01-01

    Abstract Background Protein-protein interactions (PPIs) are a critical component for many underlying biological processes. A PPI network can provide insight into the mechanisms of these processes, as well as the relationships among different proteins and toxicants that are potentially involved in the processes. There are many PPI databases publicly available, each with a specific focus. The challenge is how to effectively combine their contents to generate a robust and biologically relevant P...

  3. Domain-Domain Interactions Underlying Herpesvirus-Human Protein-Protein Interaction Networks

    OpenAIRE

    Zohar Itzhaki

    2011-01-01

    Protein-domains play an important role in mediating protein-protein interactions. Furthermore, the same domain-pairs mediate different interactions in different contexts and in various organisms, and therefore domain-pairs are considered as the building blocks of interactome networks. Here we extend these principles to the host-virus interface and find the domain-pairs that potentially mediate human-herpesvirus interactions. Notably, we find that the same domain-pairs used by other organisms ...

  4. Ubc2, an Ortholog of the Yeast Ste50p Adaptor, Possesses a Basidiomycete-Specific Carboxy terminal Extension Essential for Pathogenicity Independent of Pheromone Response.

    Science.gov (United States)

    Proteins involved in the MAP kinase pathway controlling mating, morphogenesis and pathogenicity have been identified previously in the fungus Ustilago maydis. One of these, the Ubc2 adaptor protein, possesses a basidiomycete-specific structure. In addition to containing SAM and RA domains typical of...

  5. Systematic discovery of new recognition peptides mediating protein interaction networks

    DEFF Research Database (Denmark)

    Neduva, Victor; Linding, Rune; Su-Angrand, Isabelle;

    2005-01-01

    Many aspects of cell signalling, trafficking, and targeting are governed by interactions between globular protein domains and short peptide segments. These domains often bind multiple peptides that share a common sequence pattern, or "linear motif" (e.g., SH3 binding to PxxP). Many domains...... molecular details of how interaction networks are constructed, and can explain how one protein is able to bind to very different partners. Here we show that binding motifs can be detected using data from genome-scale interaction studies, and thus avoid the normally slow discovery process. Our approach based...... that binds Translin with a KD of 43 microM. We estimate that there are dozens or even hundreds of linear motifs yet to be discovered that will give molecular insight into protein networks and greatly illuminate cellular processes.Many aspects of cell signalling, trafficking, and targeting are governed...

  6. Predicting the Secondary Structure of Proteins by Cascading Neural Networks

    Directory of Open Access Journals (Sweden)

    Maryam Alirezaee

    2012-11-01

    Full Text Available Protein Secondary Structure Prediction (PSSP is considered as a challenging task in bioinformatics and so many approaches have been proposed in the literature to solve this problem via achieving more accurate prediction results. Accurate prediction of secondary structure is a critical role in deducing tertiary structure of proteins and their functions. Among the proposed approaches to tackle this problem, Artificial Neural Networks (ANNs are considered as one of the successful tools that are widely used in this field. Recently, many efforts have been devoted to modify, improve and combine this methodology with other machine learning methods in order to get better results. In this work, we have proposed a two-stage feed forward neural network for prediction of protein secondary structures. To evaluate our approach, it is applied on RS126 dataset and its results are compared with some other NN-based methods.

  7. AtPIN: Arabidopsis thaliana Protein Interaction Network

    Directory of Open Access Journals (Sweden)

    Silva-Filho Marcio C

    2009-12-01

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

  8. Conventional and novel Gγ protein families constitute the heterotrimeric G-protein signaling network in soybean.

    Directory of Open Access Journals (Sweden)

    Swarup Roy Choudhury

    Full Text Available Heterotrimeric G-proteins comprised of Gα, Gβ and Gγ proteins are important signal transducers in all eukaryotes. The Gγ protein of the G-protein heterotrimer is crucial for its proper targeting at the plasma membrane and correct functioning. Gγ proteins are significantly smaller and more diverse than the Gα and Gβ proteins. In model plants Arabidopsis and rice that have a single Gα and Gβ protein, the presence of two canonical Gγ proteins provide some diversity to the possible heterotrimeric combinations. Our recent analysis of the latest version of the soybean genome has identified ten Gγ proteins which belong to three distinct families based on their C-termini. We amplified the full length cDNAs, analyzed their detailed expression profile by quantitative PCR, assessed their localization and performed yeast-based interaction analysis to evaluate interaction specificity with different Gβ proteins. Our results show that ten Gγ genes are retained in the soybean genome and have interesting expression profiles across different developmental stages. Six of the newly identified proteins belong to two plant-specific Gγ protein families. Yeast-based interaction analyses predict some degree of interaction specificity between different Gβ and Gγ proteins. This research thus identifies a highly diverse G-protein network from a plant species. Homologs of these novel proteins have been previously identified as QTLs for grain size and yield in rice.

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

    Directory of Open Access Journals (Sweden)

    Wei Sheng Chia

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

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

    Science.gov (United States)

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

    2016-01-01

    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. PMID:27257060

  11. Graphical Features of Functional Genes in Human Protein Interaction Network.

    Science.gov (United States)

    Wang, Pei; Chen, Yao; Lu, Jinhu; Wang, Qingyun; Yu, Xinghuo

    2016-06-01

    With the completion of the human genome project, it is feasible to investigate large-scale human protein interaction network (HPIN) with complex networks theory. Proteins are encoded by genes. Essential, viable, disease, conserved, housekeeping (HK) and tissue-enriched (TE) genes are functional genes, which are organized and functioned via interaction networks. Based on up-to-date data from various databases or literature, two large-scale HPINs and six subnetworks are constructed. We illustrate that the HPINs and most of the subnetworks are sparse, small-world, scale-free, disassortative and with hierarchical modularity. Among the six subnetworks, essential, disease and HK subnetworks are more densely connected than the others. Statistical analysis on the topological structures of the HPIN reveals that the lethal, the conserved, the HK and the TE genes are with hallmark graphical features. Receiver operating characteristic (ROC) curves indicate that the essential genes can be distinguished from the viable ones with accuracy as high as almost 70%. Closeness, semi-local and eigenvector centralities can distinguish the HK genes from the TE ones with accuracy around 82%. Furthermore, the Venn diagram, cluster dendgrams and classifications of disease genes reveal that some classes of disease genes are with hallmark graphical features, especially for cancer genes, HK disease genes and TE disease genes. The findings facilitate the identification of some functional genes via topological structures. The investigations shed some light on the characteristics of the compete interactome, which have potential implications in networked medicine and biological network control. PMID:26841412

  12. Locus heterogeneity disease genes encode proteins with high interconnectivity in the human protein interaction network.

    Science.gov (United States)

    Keith, Benjamin P; Robertson, David L; Hentges, Kathryn E

    2014-01-01

    Mutations in genes potentially lead to a number of genetic diseases with differing severity. These disease genes have been the focus of research in recent years showing that the disease gene population as a whole is not homogeneous, and can be categorized according to their interactions. Locus heterogeneity describes a single disorder caused by mutations in different genes each acting individually to cause the same disease. Using datasets of experimentally derived human disease genes and protein interactions, we created a protein interaction network to investigate the relationships between the products of genes associated with a disease displaying locus heterogeneity, and use network parameters to suggest properties that distinguish these disease genes from the overall disease gene population. Through the manual curation of known causative genes of 100 diseases displaying locus heterogeneity and 397 single-gene Mendelian disorders, we use network parameters to show that our locus heterogeneity network displays distinct properties from the global disease network and a Mendelian network. Using the global human proteome, through random simulation of the network we show that heterogeneous genes display significant interconnectivity. Further topological analysis of this network revealed clustering of locus heterogeneity genes that cause identical disorders, indicating that these disease genes are involved in similar biological processes. We then use this information to suggest additional genes that may contribute to diseases with locus heterogeneity.

  13. Differential Protein Network Analysis of the Immune Cell Lineage

    Directory of Open Access Journals (Sweden)

    Trevor Clancy

    2014-01-01

    Full Text Available Recently, the Immunological Genome Project (ImmGen completed the first phase of the goal to understand the molecular circuitry underlying the immune cell lineage in mice. That milestone resulted in the creation of the most comprehensive collection of gene expression profiles in the immune cell lineage in any model organism of human disease. There is now a requisite to examine this resource using bioinformatics integration with other molecular information, with the aim of gaining deeper insights into the underlying processes that characterize this immune cell lineage. We present here a bioinformatics approach to study differential protein interaction mechanisms across the entire immune cell lineage, achieved using affinity propagation applied to a protein interaction network similarity matrix. We demonstrate that the integration of protein interaction networks with the most comprehensive database of gene expression profiles of the immune cells can be used to generate hypotheses into the underlying mechanisms governing the differentiation and the differential functional activity across the immune cell lineage. This approach may not only serve as a hypothesis engine to derive understanding of differentiation and mechanisms across the immune cell lineage, but also help identify possible immune lineage specific and common lineage mechanism in the cells protein networks.

  14. Negative Group Velocity and Spin-Flip in Microwave Adaptors

    CERN Document Server

    Carot, Alexander; Nimtz, Guenter

    2012-01-01

    A Fabry-Perot like interferometer with two microwaveguide adaptors as reflectors creates a passive dielectric medium with a negative group delay time due to polarization shift. A rotational strain of the polarization vector by one of the adaptors is coupled with a drastic negative group velocity. The adapted rectangular and circular waveguides have the same dispersion. The input rectangular waveguide mode is linearly polarized, whereas the basic mode of the adapted circular waveguide is circularly polarized. A 667 wavelengths long circular waveguide connects the input with the output adaptor. Experiments are performed in the frequency and in the time domain. We describe, how the helical polarization change and the spin-flip of the two different circular wave modes produce the observed negative group velocity.

  15. Optimized Adaptor Polymerase Chain Reaction Method for Efficient Genomic Walking

    Institute of Scientific and Technical Information of China (English)

    Peng XU; Rui-Ying HU; Xiao-Yan DING

    2006-01-01

    Genomic walking is one of the most useful approaches in genome-related research. Three kinds of PCR-based methods are available for this purpose. However, none of them has been generally applied because they are either insensitive or inefficient. Here we present an efficient PCR protocol, an optimized adaptor PCR method for genomic walking. Using a combination of a touchdown PCR program and a special adaptor, the optimized adaptor PCR protocol achieves high sensitivity with low background noise. By applying this protocol, the insertion sites of a gene trap mouse line and two gene promoters from the incompletely sequenced Xenopus laevis genome were successfully identified with high efficiency. The general application of this protocol in genomic walking was promising.

  16. Integrated cellular network of transcription regulations and protein-protein interactions

    Directory of Open Access Journals (Sweden)

    Chen Bor-Sen

    2010-03-01

    Full Text Available Abstract Background With the accumulation of increasing omics data, a key goal of systems biology is to construct networks at different cellular levels to investigate cellular machinery of the cell. However, there is currently no satisfactory method to construct an integrated cellular network that combines the gene regulatory network and the signaling regulatory pathway. Results In this study, we integrated different kinds of omics data and developed a systematic method to construct the integrated cellular network based on coupling dynamic models and statistical assessments. The proposed method was applied to S. cerevisiae stress responses, elucidating the stress response mechanism of the yeast. From the resulting integrated cellular network under hyperosmotic stress, the highly connected hubs which are functionally relevant to the stress response were identified. Beyond hyperosmotic stress, the integrated network under heat shock and oxidative stress were also constructed and the crosstalks of these networks were analyzed, specifying the significance of some transcription factors to serve as the decision-making devices at the center of the bow-tie structure and the crucial role for rapid adaptation scheme to respond to stress. In addition, the predictive power of the proposed method was also demonstrated. Conclusions We successfully construct the integrated cellular network which is validated by literature evidences. The integration of transcription regulations and protein-protein interactions gives more insight into the actual biological network and is more predictive than those without integration. The method is shown to be powerful and flexible and can be used under different conditions and for different species. The coupling dynamic models of the whole integrated cellular network are very useful for theoretical analyses and for further experiments in the fields of network biology and synthetic biology.

  17. 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.

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

    International Nuclear Information System (INIS)

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

  19. DMPD: Adaptor usage and Toll-like receptor signaling specificity. [Dynamic Macrophage Pathway CSML Database

    Lifescience Database Archive (English)

    Full Text Available 15876435 Adaptor usage and Toll-like receptor signaling specificity. Dunne A, O'Nei...sage and Toll-like receptor signaling specificity. PubmedID 15876435 Title Adaptor usage and Toll-like receptor signaling specific

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

    Science.gov (United States)

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

    2006-01-01

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

  1. Exploring virus relationships based on virus-host protein-protein interaction network

    OpenAIRE

    Xu Feng; Zhao Chen; Li Yuhua; Li Jiang; Deng Youping; Shi Tieliu

    2011-01-01

    Abstract Background Currently, several systems have been proposed to classify viruses and indicate the relationships between different ones, though each system has its limitations because of the complexity of viral origins and their rapid evolution rate. We hereby propose a new method to explore the relationships between different viruses. Method A new method, which is based on the virus-host protein-protein interaction network, is proposed in this paper to categorize viruses. The distances b...

  2. Identification of Candidate Genes related to Bovine Marbling using Protein-Protein Interaction Networks

    OpenAIRE

    Lim, Dajeong; Kim, Nam-Kuk; Park, Hye-Sun; Lee, Seung-Hwan; Cho, Yong-Min; Oh, Sung Jong; Kim, Tae-Hun; Kim, Heebal

    2011-01-01

    Complex traits are determined by the combined effects of many loci and are affected by gene networks or biological pathways. Systems biology approaches have an important role in the identification of candidate genes related to complex diseases or traits at the system level. The present study systemically analyzed genes associated with bovine marbling score and identified their relationships. The candidate nodes were obtained using MedScan text-mining tools and linked by protein-protein intera...

  3. Cytosol- and clathrin-dependent stimulation of endocytosis in vitro by purified adaptors

    OpenAIRE

    1992-01-01

    Using stage-specific assays for receptor-mediated endocytosis of transferrin (Tfn) into perforated A431 cells we show that purified adaptors stimulate coated pit assembly and ligand sequestration into deeply invaginated coated pits. Late events in endocytosis involving membrane fission and coated vesicle budding which lead to the internalization of Tfn are unaffected. AP2, plasma membrane adaptors, are active at physiological concentrations, whereas AP1, Golgi adaptors, are inactive. Adaptor-...

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2011-12-31

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

  5. Improving Protein Fold Recognition by Deep Learning Networks

    Science.gov (United States)

    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.

  6. Prediction and systematic study of protein-protein interaction networks of Leptospira interrogans

    Institute of Scientific and Technical Information of China (English)

    SUN Jingchun; XU Jinlin; CAO Jianping; LIU Qi; GUO Xiaokui; SHI Tieliu; LI Yixue

    2006-01-01

    Leptospira interrogans serovar Lai is a pathogenic bacterium that causes a spirochetal zoonosis in humans and some animals. With its complete genome sequence available, it is possible to analyze protein-protein interactions from a whole- genome standpoint. Here we combine four recently developed computational approaches (gene fusion method, gene neighbor method, phylogenetic profiles method, and operon method) to predict protein-pro- tein interaction networks of Leptospira interrogans strain Lai. Through comprehensive analysis on in- teractions among proteins of motility and chemotaxis system, signal transduction, lipopolysaccaride bio- synthesis and a series of proteins related to adhesion and invasion, we provided information for further studying on its pathogenic mechanism. In addition, we also assigned 203 previously uncharacterized proteins with possible functions based on the known functions of its interacting partners. This work is helpful for further investigating L. interrogans strain Lai.

  7. A second-generation protein-protein interaction network of Helicobacter pylori.

    Science.gov (United States)

    Häuser, Roman; Ceol, Arnaud; Rajagopala, Seesandra V; Mosca, Roberto; Siszler, Gabriella; Wermke, Nadja; Sikorski, Patricia; Schwarz, Frank; Schick, Matthias; Wuchty, Stefan; Aloy, Patrick; Uetz, Peter

    2014-05-01

    Helicobacter pylori infections cause gastric ulcers and play a major role in the development of gastric cancer. In 2001, the first protein interactome was published for this species, revealing over 1500 binary protein interactions resulting from 261 yeast two-hybrid screens. Here we roughly double the number of previously published interactions using an ORFeome-based, proteome-wide yeast two-hybrid screening strategy. We identified a total of 1515 protein-protein interactions, of which 1461 are new. The integration of all the interactions reported in H. pylori results in 3004 unique interactions that connect about 70% of its proteome. Excluding interactions of promiscuous proteins we derived from our new data a core network consisting of 908 interactions. We compared our data set to several other bacterial interactomes and experimentally benchmarked the conservation of interactions using 365 protein pairs (interologs) of E. coli of which one third turned out to be conserved in both species.

  8. 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

  9. A liquid crystal of ascorbyl palmitate, used as vaccine platform, provides sustained release of antigen and has intrinsic pro-inflammatory and adjuvant activities which are dependent on MyD88 adaptor protein.

    Science.gov (United States)

    Sánchez Vallecillo, María F; Minguito de la Escalera, María M; Aguirre, María V; Ullio Gamboa, Gabriela V; Palma, Santiago D; González-Cintado, Leticia; Chiodetti, Ana L; Soldano, Germán; Morón, Gabriel; Allemandi, Daniel A; Ardavín, Carlos; Pistoresi-Palencia, María C; Maletto, Belkys A

    2015-09-28

    Modern subunit vaccines require the development of new adjuvant strategies. Recently, we showed that CpG-ODN formulated with a liquid crystal nanostructure formed by self-assembly of 6-O-ascorbyl palmitate (Coa-ASC16) is an attractive system for promoting an antigen-specific immune response to weak antigens. Here, we showed that after subcutaneous injection of mice with near-infrared fluorescent dye-labeled OVA antigen formulated with Coa-ASC16, the dye-OVA was retained at the injection site for a longer period than when soluble dye-OVA was administered. Coa-ASC16 alone elicited a local inflammation, but how this material triggers this response has not been described yet. Although it is known that some materials used as a platform are not immunologically inert, very few studies have directly focused on this topic. In this study, we explored the underlying mechanisms concerning the interaction between Coa-ASC16 and the immune system and we found that the whole inflammatory response elicited by Coa-ASC16 (leukocyte recruitment and IL-1β, IL-6 and IL-12 production) was dependent on the MyD88 protein. TLR2, TLR4, TLR7 and NLRP3-inflammasome signaling were not required for induction of this inflammatory response. Coa-ASC16 induced local release of self-DNA, and in TLR9-deficient mice IL-6 production was absent. In addition, Coa-ASC16 revealed an intrinsic adjuvant activity which was affected by MyD88 and IL-6 absence. Taken together these results indicate that Coa-ASC16 used as a vaccine platform is effective due to the combination of the controlled release of antigen and its intrinsic pro-inflammatory activity. Understanding how Coa-ASC16 works might have significant implications for rational vaccine design. PMID:26188153

  10. Amyloid Beta-Protein and Neural Network Dysfunction

    Directory of Open Access Journals (Sweden)

    Fernando Peña-Ortega

    2013-01-01

    Full Text Available Understanding the neural mechanisms underlying brain dysfunction induced by amyloid beta-protein (Aβ represents one of the major challenges for Alzheimer’s disease (AD research. The most evident symptom of AD is a severe decline in cognition. Cognitive processes, as any other brain function, arise from the activity of specific cell assemblies of interconnected neurons that generate neural network dynamics based on their intrinsic and synaptic properties. Thus, the origin of Aβ-induced cognitive dysfunction, and possibly AD-related cognitive decline, must be found in specific alterations in properties of these cells and their consequences in neural network dynamics. The well-known relationship between AD and alterations in the activity of several neural networks is reflected in the slowing of the electroencephalographic (EEG activity. Some features of the EEG slowing observed in AD, such as the diminished generation of different network oscillations, can be induced in vivo and in vitro upon Aβ application or by Aβ overproduction in transgenic models. This experimental approach offers the possibility to study the mechanisms involved in cognitive dysfunction produced by Aβ. This type of research may yield not only basic knowledge of neural network dysfunction associated with AD, but also novel options to treat this modern epidemic.

  11. 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

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

    Science.gov (United States)

    Yen, Eric A; Tsay, Aaron; Waldispuhl, Jerome; Vogel, Jackie

    2014-05-01

    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 visualization of the hidden

  13. Anti-adaptors use distinct modes of binding to inhibit the RssB-dependent turnover of RpoS (σS by ClpXP.

    Directory of Open Access Journals (Sweden)

    Dimce eMicevski

    2015-04-01

    Full Text Available In Escherichia coli, σS is the master regulator of the general stress response. The level of σS changes in response to multiple stress conditions and it is regulated at many levels including protein turnover. In the absence of stress, σS is rapidly degraded by the AAA+ protease, ClpXP in a regulated manner that depends on the adaptor protein RssB. This two-component response regulator mediates the recognition of σS and its delivery to ClpXP. The turnover of σS however, can be inhibited in a stress specific manner, by one of three anti-adaptor proteins. Each anti-adaptor binds to RssB and inhibits its activity, but how this is achieved is not fully understood at a molecular level. Here we describe details of the interaction between each anti-adaptor and RssB that leads to the stabilization of σS. By defining the domains of RssB using partial proteolysis we demonstrate that each anti-adaptor uses a distinct mode of binding to inhibit RssB activity. IraD docks specifically to the N-terminal domain of RssB, IraP interacts primarily with the C-terminal domain, while IraM interacts with both domains. Despite these differences in binding, we propose that docking of each anti-adaptor induces a conformational change in RssB, which resembles the inactive dimer of RssB. This dimer-like state of RssB not only prevents substrate binding but also triggers substrate release from a pre-bound complex.

  14. UIF, a New mRNA export adaptor that works together with REF/ALY, requires FACT for recruitment to mRNA.

    Science.gov (United States)

    Hautbergue, Guillaume M; Hung, Ming-Lung; Walsh, Matthew J; Snijders, Ambrosius P L; Chang, Chung-Te; Jones, Rachel; Ponting, Chris P; Dickman, Mark J; Wilson, Stuart A

    2009-12-01

    Messenger RNA (mRNA) export adaptors play an important role in the transport of mRNA from the nucleus to the cytoplasm. They couple early mRNA processing events such as 5' capping and 3' end formation with loading of the TAP/NXF1 export receptor onto mRNA. The canonical adaptor REF/ALY/Yra1 is recruited to mRNA via UAP56 and subsequently delivers the mRNA to NXF1 [1]. Knockdown of UAP56 [2, 3] and NXF1 [4-7] in higher eukaryotes efficiently blocks mRNA export, whereas knockdown of REF only causes a modest reduction, suggesting the existence of additional adaptors [8-10]. Here we identify a new UAP56-interacting factor, UIF, which functions as an export adaptor, binding NXF1 and delivering mRNA to the nuclear pore. REF and UIF are simultaneously found on the same mRNA molecules, and both proteins are required for efficient export of mRNA. We show that the histone chaperone FACT specifically binds UIF, but not REF, via the SSRP1 subunit, and this interaction is required for recruitment of UIF to mRNA. Together the results indicate that REF and UIF represent key human adaptors for the export of cellular mRNAs via the UAP56-NXF1 pathway.

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

    Science.gov (United States)

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

    2016-03-01

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

  16. Phospho-tyrosine dependent protein–protein interaction network

    Science.gov (United States)

    Grossmann, Arndt; Benlasfer, Nouhad; Birth, Petra; Hegele, Anna; Wachsmuth, Franziska; Apelt, Luise; Stelzl, Ulrich

    2015-01-01

    Post-translational protein modifications, such as tyrosine phosphorylation, regulate protein–protein interactions (PPIs) critical for signal processing and cellular phenotypes. We extended an established yeast two-hybrid system employing human protein kinases for the analyses of phospho-tyrosine (pY)-dependent PPIs in a direct experimental, large-scale approach. We identified 292 mostly novel pY-dependent PPIs which showed high specificity with respect to kinases and interacting proteins and validated a large fraction in co-immunoprecipitation experiments from mammalian cells. About one-sixth of the interactions are mediated by known linear sequence binding motifs while the majority of pY-PPIs are mediated by other linear epitopes or governed by alternative recognition modes. Network analysis revealed that pY-mediated recognition events are tied to a highly connected protein module dedicated to signaling and cell growth pathways related to cancer. Using binding assays, protein complementation and phenotypic readouts to characterize the pY-dependent interactions of TSPAN2 (tetraspanin 2) and GRB2 or PIK3R3 (p55γ), we exemplarily provide evidence that the two pY-dependent PPIs dictate cellular cancer phenotypes. PMID:25814554

  17. The endocytic adaptor Eps15 controls marginal zone B cell numbers.

    Directory of Open Access Journals (Sweden)

    Benedetta Pozzi

    Full Text Available Eps15 is an endocytic adaptor protein involved in clathrin and non-clathrin mediated endocytosis. In Caenorhabditis elegans and Drosophila melanogaster lack of Eps15 leads to defects in synaptic vesicle recycling and synapse formation. We generated Eps15-KO mice to investigate its function in mammals. Eps15-KO mice are born at the expected Mendelian ratio and are fertile. Using a large-scale phenotype screen covering more than 300 parameters correlated to human disease, we found that Eps15-KO mice did not show any sign of disease or neural deficits. Instead, altered blood parameters pointed to an immunological defect. By competitive bone marrow transplantation we demonstrated that Eps15-KO hematopoietic precursor cells were more efficient than the WT counterparts in repopulating B220⁺ bone marrow cells, CD19⁻ thymocytes and splenic marginal zone (MZ B cells. Eps15-KO mice showed a 2-fold increase in MZ B cell numbers when compared with controls. Using reverse bone marrow transplantation, we found that Eps15 regulates MZ B cell numbers in a cell autonomous manner. FACS analysis showed that although MZ B cells were increased in Eps15-KO mice, transitional and pre-MZ B cell numbers were unaffected. The increase in MZ B cell numbers in Eps15 KO mice was not dependent on altered BCR signaling or Notch activity. In conclusion, in mammals, the endocytic adaptor protein Eps15 is a regulator of B-cell lymphopoiesis.

  18. Cell cycle-dependent adaptor complex for ClpXP-mediated proteolysis directly integrates phosphorylation and second messenger signals.

    Science.gov (United States)

    Smith, Stephen C; Joshi, Kamal K; Zik, Justin J; Trinh, Katherine; Kamajaya, Aron; Chien, Peter; Ryan, Kathleen R

    2014-09-30

    The cell-division cycle of Caulobacter crescentus depends on periodic activation and deactivation of the essential response regulator CtrA. Although CtrA is critical for transcription during some parts of the cell cycle, its activity must be eliminated before chromosome replication because CtrA also blocks the initiation of DNA replication. CtrA activity is down-regulated both by dephosphorylation and by proteolysis, mediated by the ubiquitous ATP-dependent protease ClpXP. Here we demonstrate that proteins needed for rapid CtrA proteolysis in vivo form a phosphorylation-dependent and cyclic diguanylate (cdG)-dependent adaptor complex that accelerates CtrA degradation in vitro by ClpXP. The adaptor complex includes CpdR, a single-domain response regulator; PopA, a cdG-binding protein; and RcdA, a protein whose activity cannot be predicted. When CpdR is unphosphorylated and when PopA is bound to cdG, they work together with RcdA in an all-or-none manner to reduce the Km of CtrA proteolysis 10-fold. We further identified a set of amino acids in the receiver domain of CtrA that modulate its adaptor-mediated degradation in vitro and in vivo. Complex formation between PopA and CtrA depends on these amino acids, which reside on alpha-helix 1 of the CtrA receiver domain, and on cdG binding by PopA. These results reveal that each accessory factor plays an essential biochemical role in the regulated proteolysis of CtrA and demonstrate, to our knowledge, the first example of a multiprotein, cdG-dependent proteolytic adaptor.

  19. 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 779 protein-protein interactions. A number of proteins were identified having interactions with more than one of the protein kinases. The fully reconstructed interaction network includes all the information available in separate databases for all the proteins included in the network (nodes......) 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...

  20. Predicting protein functions from redundancies in large-scale protein interaction networks

    Science.gov (United States)

    Samanta, Manoj Pratim; Liang, Shoudan

    2003-01-01

    Interpreting data from large-scale protein interaction experiments has been a challenging task because of the widespread presence of random false positives. Here, we present a network-based statistical algorithm that overcomes this difficulty and allows us to derive functions of unannotated proteins from large-scale interaction data. Our algorithm uses the insight that if two proteins share significantly larger number of common interaction partners than random, they have close functional associations. Analysis of publicly available data from Saccharomyces cerevisiae reveals >2,800 reliable functional associations, 29% of which involve at least one unannotated protein. By further analyzing these associations, we derive tentative functions for 81 unannotated proteins with high certainty. Our method is not overly sensitive to the false positives present in the data. Even after adding 50% randomly generated interactions to the measured data set, we are able to recover almost all (approximately 89%) of the original associations.

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

    Energy Technology Data Exchange (ETDEWEB)

    Li, Zheng; Chen, Wei

    2016-07-05

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

  2. Convolutional neural network architectures for predicting DNA–protein binding

    Science.gov (United States)

    Zeng, Haoyang; Edwards, Matthew D.; Liu, Ge; Gifford, David K.

    2016-01-01

    Motivation: Convolutional neural networks (CNN) have outperformed conventional methods in modeling the sequence specificity of DNA–protein binding. Yet inappropriate CNN architectures can yield poorer performance than simpler models. Thus an in-depth understanding of how to match CNN architecture to a given task is needed to fully harness the power of CNNs for computational biology applications. Results: We present a systematic exploration of CNN architectures for predicting DNA sequence binding using a large compendium of transcription factor datasets. We identify the best-performing architectures by varying CNN width, depth and pooling designs. We find that adding convolutional kernels to a network is important for motif-based tasks. We show the benefits of CNNs in learning rich higher-order sequence features, such as secondary motifs and local sequence context, by comparing network performance on multiple modeling tasks ranging in difficulty. We also demonstrate how careful construction of sequence benchmark datasets, using approaches that control potentially confounding effects like positional or motif strength bias, is critical in making fair comparisons between competing methods. We explore how to establish the sufficiency of training data for these learning tasks, and we have created a flexible cloud-based framework that permits the rapid exploration of alternative neural network architectures for problems in computational biology. Availability and Implementation: All the models analyzed are available at http://cnn.csail.mit.edu. Contact: gifford@mit.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27307608

  3. Molecular Architecture of Spinal Cord Injury Protein Interaction Network.

    Directory of Open Access Journals (Sweden)

    Ali Alawieh

    Full Text Available Spinal cord injury (SCI is associated with complex pathophysiological processes that follow the primary traumatic event and determine the extent of secondary damage and functional recovery. Numerous reports have used global and hypothesis-driven approaches to identify protein changes that contribute to the overall pathology of SCI in an effort to identify potential therapeutic interventions. In this study, we use a semi-automatic annotation approach to detect terms referring to genes or proteins dysregulated in the SCI literature and develop a curated SCI interactome. Network analysis of the SCI interactome revealed the presence of a rich-club organization corresponding to a "powerhouse" of highly interacting hub-proteins. Studying the modular organization of the network have shown that rich-club proteins cluster into modules that are specifically enriched for biological processes that fall under the categories of cell death, inflammation, injury recognition and systems development. Pathway analysis of the interactome and the rich-club revealed high similarity indicating the role of the rich-club proteins as hubs of the most prominent pathways in disease pathophysiology and illustrating the centrality of pro-and anti-survival signal competition in the pathology of SCI. In addition, evaluation of centrality measures of single nodes within the rich-club have revealed that neuronal growth factor (NGF, caspase 3, and H-Ras are the most central nodes and potentially an interesting targets for therapy. Our integrative approach uncovers the molecular architecture of SCI interactome, and provide an essential resource for evaluating significant therapeutic candidates.

  4. Category theoretic analysis of hierarchical protein materials and social networks

    CERN Document Server

    Spivak, David I; Buehler, Markus J

    2011-01-01

    Materials in biology span all the scales from Angstroms to meters and typically consist of complex hierarchical assemblies of simple building blocks. Here we review an application of category theory to describe structural and resulting functional properties of biological protein materials by developing so-called ologs. An olog is like a "concept web" or "semantic network" except that it follows a rigorous mathematical formulation based on category theory. This key difference ensures that an olog is unambiguous, highly adaptable to evolution and change, and suitable for sharing concepts with other ologs. We consider a simple example of an alpha-helical and an amyloid-like protein filament subjected to axial extension and develop an olog representation of their structural and resulting mechanical properties. We also construct a representation of a social network in which people send text-messages to their nearest neighbors and act as a team to perform a task. We show that the olog for the protein and the olog f...

  5. Quantitation, network and function of protein phosphorylation in plant cell

    Directory of Open Access Journals (Sweden)

    Lin eZHU

    2013-01-01

    Full Text Available Protein phosphorylation is one of the most important post-translational modifications (PTMs as it participates in regulating various cellular processes and biological functions. It is therefore crucial to identify phosphorylated proteins to construct a phosphor-relay network, and eventually to understand the underlying molecular regulatory mechanism in response to both internal and external stimuli. The changes in phosphorylation status at these novel phosphosites can be accurately measured using a 15N-stable isotopic labeling in Arabidopsis (SILIA quantitative proteomic approach in a high-throughput manner. One of the unique characteristics of the SILIA quantitative phosphoproteomic approach is the preservation of native PTM status on protein during the entire peptide preparation procedure. Evolved from SILIA is another quantitative PTM proteomic approach, AQUIP (absolute quantitation of isoforms of post-translationally modified proteins, which was developed by combining the advantages of targeted proteomics with SILIA. Bioinformatics-based phosphorylation site prediction coupled with an MS-based in vitro kinase assay is an additional way to extend the capability of phosphosite identification from the total cellular protein. The combined use of SILIA and AQUIP provides a novel strategy for molecular systems biological study and for investigation of in vivo biological functions of these phosphoprotein isoforms and combinatorial codes of PTMs.

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

    Science.gov (United States)

    Wang, Kun; Peng, Xiaojue; Ji, Yanxiao; Yang, Pingfang; Zhu, Yingguo; Li, Shaoqing

    2013-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Wang eKun

    2013-04-01

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

  8. Identification of Candidate Genes related to Bovine Marbling using Protein-Protein Interaction Networks

    Directory of Open Access Journals (Sweden)

    Dajeong Lim, Nam-Kuk Kim, Hye-Sun Park, Seung-Hwan Lee, Yong-Min Cho, Sung Jong Oh, Tae-Hun Kim, Heebal Kim

    2011-01-01

    Full Text Available Complex traits are determined by the combined effects of many loci and are affected by gene networks or biological pathways. Systems biology approaches have an important role in the identification of candidate genes related to complex diseases or traits at the system level. The present study systemically analyzed genes associated with bovine marbling score and identified their relationships. The candidate nodes were obtained using MedScan text-mining tools and linked by protein-protein interaction (PPI from the Human Protein Reference Database (HPRD. To determine key node of marbling, the degree and betweenness centrality (BC were used. The hub nodes and biological pathways of our network are consistent with the previous reports about marbling traits, and also suggest unknown candidate genes associated with intramuscular fat. Five nodes were identified as hub genes, which was consistent with the network analysis using quantitative reverse-transcription PCR (qRT-PCR. Key nodes of the PPI network have positive roles (PPARγ, C/EBPα, and RUNX1T1 and negative roles (RXRA, CAMK2A in the development of intramuscular fat by several adipogenesis-related pathways. This study provides genetic information for identifying candidate genes for the marbling trait in bovine.

  9. Empirically controlled mapping of the Caenorhabditis elegans protein-protein interactome network.

    Science.gov (United States)

    Simonis, Nicolas; Rual, Jean-François; Carvunis, Anne-Ruxandra; Tasan, Murat; Lemmens, Irma; Hirozane-Kishikawa, Tomoko; Hao, Tong; Sahalie, Julie M; Venkatesan, Kavitha; Gebreab, Fana; Cevik, Sebiha; Klitgord, Niels; Fan, Changyu; Braun, Pascal; Li, Ning; Ayivi-Guedehoussou, Nono; Dann, Elizabeth; Bertin, Nicolas; Szeto, David; Dricot, Amélie; Yildirim, Muhammed A; Lin, Chenwei; de Smet, Anne-Sophie; Kao, Huey-Ling; Simon, Christophe; Smolyar, Alex; Ahn, Jin Sook; Tewari, Muneesh; Boxem, Mike; Milstein, Stuart; Yu, Haiyuan; Dreze, Matija; Vandenhaute, Jean; Gunsalus, Kristin C; Cusick, Michael E; Hill, David E; Tavernier, Jan; Roth, Frederick P; Vidal, Marc

    2009-01-01

    To provide accurate biological hypotheses and elucidate global properties of cellular networks, systematic identification of protein-protein interactions must meet high quality standards.We present an expanded C. elegans protein-protein interaction network, or 'interactome' map, derived from testing a matrix of approximately 10,000 x approximately 10,000 proteins using a highly specific, high-throughput yeast two-hybrid system. Through a new empirical quality control framework, we show that the resulting data set (Worm Interactome 2007, or WI-2007) was similar in quality to low-throughput data curated from the literature. We filtered previous interaction data sets and integrated them with WI-2007 to generate a high-confidence consolidated map (Worm Interactome version 8, or WI8). This work allowed us to estimate the size of the worm interactome at approximately 116,000 interactions. Comparison with other types of functional genomic data shows the complementarity of distinct experimental approaches in predicting different functional relationships between genes or proteins PMID:19123269

  10. Competitive and Cooperative Interactions Mediate RNA Transfer from Herpesvirus Saimiri ORF57 to the Mammalian Export Adaptor ALYREF

    OpenAIRE

    Tunnicliffe, Richard B.; Hautbergue, Guillaume M.; Wilson, Stuart A.; Priti Kalra; Golovanov, Alexander P.

    2014-01-01

    The essential herpesvirus adaptor protein HVS ORF57, which has homologs in all other herpesviruses, promotes viral mRNA export by utilizing the cellular mRNA export machinery. ORF57 protein specifically recognizes viral mRNA transcripts, and binds to proteins of the cellular transcription-export (TREX) complex, in particular ALYREF. This interaction introduces viral mRNA to the NXF1 pathway, subsequently directing it to the nuclear pore for export to the cytoplasm. Here we have used a range o...

  11. Category theoretic analysis of hierarchical protein materials and social networks.

    Directory of Open Access Journals (Sweden)

    David I Spivak

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

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

    Directory of Open Access Journals (Sweden)

    Nielsen Jens

    2010-05-01

    Full Text Available Abstract Background Several protein-protein interaction studies have been performed for the yeast Saccharomyces cerevisiae using different high-throughput experimental techniques. All these results are collected in the BioGRID database and the SGD database provide detailed annotation of the different 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-sensing and metabolic regulatory signal transduction pathways (STP operating in Saccharomyces cerevisiae. The reconstructed STP network includes a full protein-protein interaction network including the key nodes Snf1, Tor1, Hog1 and Pka1. The network includes a total of 623 structural open reading frames (ORFs and 779 protein-protein interactions. A number of proteins were identified having interactions with more than one of the protein kinases. The fully reconstructed interaction network includes all the information available in separate databases for all the proteins included in the network (nodes 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 of nutrient sensing and regulation in S. cerevisiae. Furthermore, we propose this annotated reconstruction as a first step towards generation of an extensive annotated protein-protein interaction network of signal transduction and metabolic regulation in this yeast.

  13. 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.

  14. Protein networks in induced sputum from smokers and COPD patients

    Directory of Open Access Journals (Sweden)

    Baraniuk JN

    2015-09-01

    Full Text Available James N Baraniuk,1 Begona Casado,1 Lewis K Pannell,2 Peter B McGarvey,3 Piera Boschetto,4 Maurizio Luisetti,5,† Paolo Iadarola6 1Division of Rheumatology, Immunology and Allergy, Georgetown University, Washington, DC, 2Proteomics and Mass Spectrometry Laboratory, Mitchell Cancer Center, University of South Alabama, Mobile, AL, 3Innovation Center for Biomedical Informatics, Georgetown University, Washington, DC, USA; 4Department of Medical Sciences, University of Ferrara, Ferrara, 5SC Pneumologia, Dipartimento Medicina Molecolare, Fondazione IRCCS Policlinico San Matteo, 6Lazzaro Spallanzani Department of Biology and Biotechnology, University of Pavia, Pavia, Italy †Maurizio Luisetti passed away on October 20, 2014 Rationale: Subtypes of cigarette smoke-induced disease affect different lung structures and may have distinct pathophysiological mechanisms. Objective: To determine if proteomic classification of the cellular and vascular origins of sputum proteins can characterize these mechanisms and phenotypes. Subjects and methods: Individual sputum specimens from lifelong nonsmokers (n=7 and smokers with normal lung function (n=13, mucous hypersecretion with normal lung function (n=11, obstructed airflow without emphysema (n=15, and obstruction plus emphysema (n=10 were assessed with mass spectrometry. Data reduction, logarithmic transformation of spectral counts, and Cytoscape network-interaction analysis were performed. The original 203 proteins were reduced to the most informative 50. Sources were secretory dimeric IgA, submucosal gland serous and mucous cells, goblet and other epithelial cells, and vascular permeability. Results: Epithelial proteins discriminated nonsmokers from smokers. Mucin 5AC was elevated in healthy smokers and chronic bronchitis, suggesting a continuum with the severity of hypersecretion determined by mechanisms of goblet-cell hyperplasia. Obstructed airflow was correlated with glandular proteins and lower levels of

  15. Protein-spanning water networks and implications for prediction of protein-protein interactions mediated through hydrophobic effects.

    Science.gov (United States)

    Cui, Di; Ou, Shuching; Patel, Sandeep

    2014-12-01

    Hydrophobic effects, often conflated with hydrophobic forces, are implicated as major determinants in biological association and self-assembly processes. Protein-protein interactions involved in signaling pathways in living systems are a prime example where hydrophobic effects have profound implications. In the context of protein-protein interactions, a priori knowledge of relevant binding interfaces (i.e., clusters of residues involved directly with binding interactions) is difficult. In the case of hydrophobically mediated interactions, use of hydropathy-based methods relying on single residue hydrophobicity properties are routinely and widely used to predict propensities for such residues to be present in hydrophobic interfaces. However, recent studies suggest that consideration of hydrophobicity for single residues on a protein surface require accounting of the local environment dictated by neighboring residues and local water. In this study, we use a method derived from percolation theory to evaluate spanning water networks in the first hydration shells of a series of small proteins. We use residue-based water density and single-linkage clustering methods to predict hydrophobic regions of proteins; these regions are putatively involved in binding interactions. We find that this simple method is able to predict with sufficient accuracy and coverage the binding interface residues of a series of proteins. The approach is competitive with automated servers. The results of this study highlight the importance of accounting of local environment in determining the hydrophobic nature of individual residues on protein surfaces.

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Directory of Open Access Journals (Sweden)

    Thomas Wallach

    2013-03-01

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

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

    Science.gov (United States)

    Wallach, Thomas; Schellenberg, Katja; Maier, Bert; Kalathur, Ravi Kiran Reddy; Porras, Pablo; Wanker, Erich E; Futschik, Matthias E; Kramer, Achim

    2013-03-01

    Essentially all biological processes depend on protein-protein interactions (PPIs). Timing of such interactions is crucial for regulatory function. Although circadian (~24-hour) clocks constitute fundamental cellular timing mechanisms regulating important physiological processes, PPI dynamics on this timescale are largely unknown. Here, we identified 109 novel PPIs among circadian clock proteins via a yeast-two-hybrid approach. Among them, the interaction of protein phosphatase 1 and CLOCK/BMAL1 was found to result in BMAL1 destabilization. We constructed a dynamic circadian PPI network predicting the PPI timing using circadian expression data. Systematic circadian phenotyping (RNAi and overexpression) suggests a crucial role for components involved in dynamic interactions. Systems analysis of a global dynamic network in liver revealed that interacting proteins are expressed at similar times likely to restrict regulatory interactions to specific phases. Moreover, we predict that circadian PPIs dynamically connect many important cellular processes (signal transduction, cell cycle, etc.) contributing to temporal organization of cellular physiology in an unprecedented manner. PMID:23555304

  19. 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.

  20. Visualization of protein interaction networks: problems and solutions

    Directory of Open Access Journals (Sweden)

    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

  1. 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.

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

    Science.gov (United States)

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

    2015-01-01

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

  3. Analysis of membrane proteins in metagenomics: networks of correlated environmental features and protein families.

    Science.gov (United States)

    Patel, Prianka V; Gianoulis, Tara A; Bjornson, Robert D; Yip, Kevin Y; Engelman, Donald M; Gerstein, Mark B

    2010-07-01

    Recent metagenomics studies have begun to sample the genomic diversity among disparate habitats and relate this variation to features of the environment. Membrane proteins are an intuitive, but thus far overlooked, choice in this type of analysis as they directly interact with the environment, receiving signals from the outside and transporting nutrients. Using global ocean sampling (GOS) data, we found nearly approximately 900,000 membrane proteins in large-scale metagenomic sequence, approximately a fifth of which are completely novel, suggesting a large space of hitherto unexplored protein diversity. Using GPS coordinates for the GOS sites, we extracted additional environmental features via interpolation from the World Ocean Database, the National Center for Ecological Analysis and Synthesis, and empirical models of dust occurrence. This allowed us to study membrane protein variation in terms of natural features, such as phosphate and nitrate concentrations, and also in terms of human impacts, such as pollution and climate change. We show that there is widespread variation in membrane protein content across marine sites, which is correlated with changes in both oceanographic variables and human factors. Furthermore, using these data, we developed an approach, protein families and environment features network (PEN), to quantify and visualize the correlations. PEN identifies small groups of covarying environmental features and membrane protein families, which we call "bimodules." Using this approach, we find that the affinity of phosphate transporters is related to the concentration of phosphate and that the occurrence of iron transporters is connected to the amount of shipping, pollution, and iron-containing dust.

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

    Directory of Open Access Journals (Sweden)

    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.

  5. Limitations of Gene Duplication Models: Evolution of Modules in Protein Interaction Networks

    OpenAIRE

    Frank Emmert-Streib

    2012-01-01

    It has been generally acknowledged that the module structure of protein interaction networks plays a crucial role with respect to the functional understanding of these networks. In this paper, we study evolutionary aspects of the module structure of protein interaction networks, which forms a mesoscopic level of description with respect to the architectural principles of networks. The purpose of this paper is to investigate limitations of well known gene duplication models by showing that the...

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

    Energy Technology Data Exchange (ETDEWEB)

    Beers, Eric; Brunner, Amy; Helm, Richard; Dickerman, Allan

    2016-08-31

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2015-07-31

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

  8. Network analysis identifies protein clusters of functional importance in juvenile idiopathic arthritis

    OpenAIRE

    Stevens, Adam; Meyer, Stefan; Hanson, Daniel; Clayton, Peter; Donn, Rachelle

    2014-01-01

    Introduction Our objective was to utilise network analysis to identify protein clusters of greatest potential functional relevance in the pathogenesis of oligoarticular and rheumatoid factor negative (RF-ve) polyarticular juvenile idiopathic arthritis (JIA). Methods JIA genetic association data were used to build an interactome network model in BioGRID 3.2.99. The top 10% of this protein:protein JIA Interactome was used to generate a minimal essential network (MEN). Reactome FI Cytoscape 2.83...

  9. Illuminating spatial and temporal organization of protein interaction networks by mass spectrometry-based proteomics

    OpenAIRE

    Jiwen eYang; Sebastian Alexander Wagner; Petra eBeli

    2015-01-01

    Protein-protein interactions are at the core of all cellular functions and dynamic alterations in protein interactions regulate cellular signaling. In the last decade, mass spectrometry-based proteomics has delivered unprecedented insights into human protein interaction networks. Affinity purification-mass spectrometry has been extensively employed for focused and high-throughput studies of steady state protein-protein interactions. Future challenges remain in mapping transient protein intera...

  10. A novel functional module detection algorithm for protein-protein interaction networks

    Directory of Open Access Journals (Sweden)

    Zhang Aidong

    2006-12-01

    Full Text Available Abstract Background The sparse connectivity of protein-protein interaction data sets makes identification of functional modules challenging. The purpose of this study is to critically evaluate a novel clustering technique for clustering and detecting functional modules in protein-protein interaction networks, termed STM. Results STM selects representative proteins for each cluster and iteratively refines clusters based on a combination of the signal transduced and graph topology. STM is found to be effective at detecting clusters with a diverse range of interaction structures that are significant on measures of biological relevance. The STM approach is compared to six competing approaches including the maximum clique, quasi-clique, minimum cut, betweeness cut and Markov Clustering (MCL algorithms. The clusters obtained by each technique are compared for enrichment of biological function. STM generates larger clusters and the clusters identified have p-values that are approximately 125-fold better than the other methods on biological function. An important strength of STM is that the percentage of proteins that are discarded to create clusters is much lower than the other approaches. Conclusion STM outperforms competing approaches and is capable of effectively detecting both densely and sparsely connected, biologically relevant functional modules with fewer discards.

  11. MyProteinNet: build up-to-date protein interaction networks for organisms, tissues and user-defined contexts.

    Science.gov (United States)

    Basha, Omer; Flom, Dvir; Barshir, Ruth; Smoly, Ilan; Tirman, Shoval; Yeger-Lotem, Esti

    2015-07-01

    The identification of the molecular pathways active in specific contexts, such as disease states or drug responses, often requires an extensive view of the potential interactions between a subset of proteins. This view is not easily obtained: it requires the integration of context-specific protein list or expression data with up-to-date data of protein interactions that are typically spread across multiple databases. The MyProteinNet web server allows users to easily create such context-sensitive protein interaction networks. Users can automatically gather and consolidate data from up to 11 different databases to create a generic protein interaction network (interactome). They can score the interactions based on reliability and filter them by user-defined contexts including molecular expression and protein annotation. The output of MyProteinNet includes the generic and filtered interactome files, together with a summary of their network attributes. MyProteinNet is particularly geared toward building human tissue interactomes, by maintaining tissue expression profiles from multiple resources. The ability of MyProteinNet to facilitate the construction of up-to-date, context-specific interactomes and its applicability to 11 different organisms and to tens of human tissues, make it a powerful tool in meaningful analysis of protein networks. MyProteinNet is available at http://netbio.bgu.ac.il/myproteinnet.

  12. The protein interaction network of a taxis signal transduction system in a Halophilic Archaeon

    Directory of Open Access Journals (Sweden)

    Schlesner Matthias

    2012-11-01

    Full Text Available Abstract Background The taxis signaling system of the extreme halophilic archaeon Halobacterium (Hbt. salinarum differs in several aspects from its model bacterial counterparts Escherichia coli and Bacillus subtilis. We studied the protein interactions in the Hbt. salinarum taxis signaling system to gain an understanding of its structure, to gain knowledge about its known components and to search for new members. Results The interaction analysis revealed that the core signaling proteins are involved in different protein complexes and our data provide evidence for dynamic interchanges between them. Fifteen of the eighteen taxis receptors (halobacterial transducers, Htrs can be assigned to four different groups depending on their interactions with the core signaling proteins. Only one of these groups, which contains six of the eight Htrs with known signals, shows the composition expected for signaling complexes (receptor, kinase CheA, adaptor CheW, response regulator CheY. From the two Hbt. salinarum CheW proteins, only CheW1 is engaged in signaling complexes with Htrs and CheA, whereas CheW2 interacts with Htrs but not with CheA. CheY connects the core signaling structure to a subnetwork consisting of the two CheF proteins (which build a link to the flagellar apparatus, CheD (the hub of the subnetwork, two CheC complexes and the receptor methylesterase CheB. Conclusions Based on our findings, we propose two hypotheses. First, Hbt. salinarum might have the capability to dynamically adjust the impact of certain Htrs or Htr clusters depending on its current needs or environmental conditions. Secondly, we propose a hypothetical feedback loop from the response regulator to Htr methylation made from the CheC proteins, CheD and CheB, which might contribute to adaptation analogous to the CheC/CheD system of B. subtilis.

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

    OpenAIRE

    H Billur Engin; Emre Guney; Ozlem Keskin; Baldo Oliva; Attila Gursoy

    2013-01-01

    Integrating Structure to Protein-Protein Interaction Networks That Drive Metastasis to Brain and Lung in Breast Cancer H. Billur Engin1, Emre Guney2, Ozlem Keskin1, Baldo Oliva2, Attila Gursoy1* 1 Center for Computational Biology and Bioinformatics and College of Engineering, Koc University, Istanbul, Turkey, 2 Structural Bioinformatics Group (GRIB), Universitat Pompeu Fabra Abstract Blocking specific protein interactions can lead to human diseases. Accordingly, protein i...

  14. Association analysis of Nitric oxide synthase 1 adaptor protein(NOS1AP)gene rs348624 polymorphisms ;with early-onset schizophrenia in the Han Chinese population%NOS1 AP基因rs348624多态性与中国汉族早发性精神分裂症的关联分析

    Institute of Scientific and Technical Information of China (English)

    胡国芹; 汪作为; 张晨; 禹顺英; 易正辉; 杨程青; 吕钦谕; 赵静; 朱明环; 郭向晴; 徐阿红; 介勇; 姜雅琴

    2015-01-01

    Objective:To investigate the association between the Nitric oxide synthase 1 adaptor protein (NOS1AP)gene polymorphisms with early-onset schizophrenia in the Han Chinese population. Method:NOS1AP tag single nucleotide polymorphisms(tag SNPs)rs348624 were genotyped using TaqMan SNP genoty-ping assay in 285 early-onset schizophrenia patients and 826 healthy controls. The allele and genotype frequen-cies were performed and the association with age at onset was evaluated. Results:There were significant difference in allele and genotype frequencies between patients and control subjects for rs348624(χ2 =149. 17, df=1,p=0. 00;χ2 =137. 25,df=2,p=0. 00). The T allele was significantly associated with an earlier age of onset in early-onset schizophrenia patients(Kaplan-Meier log rank test p=0. 00). Conclusion:The NOS1AP gene rs348624 polymorphisms may play important roles in the susceptibility and onset age to early-onset schizo-phrenia in the Han Chinese population.%目的:探讨中国汉族人群一氧化氮合酶1接头蛋白( NOS1AP)基因rs348624多态性与早发性精神分裂症的易感性及其首发年龄的关联性。方法:选取285例早发性精神分裂症患者为研究组和826名正常对照组,采用TaqMan法,检测NOS1AP基因rs348624位点多态性,并分析研究组危险等位基因的频率与首发年龄的关联性。结果:研究组与对照组rs348624等位基因和基因型频率分布比较差异有统计学意义[χ2=149.17,自由度(df)=1,p=0.00;χ2=137.25,自由度(df)=2,p=0.00];Kap-lan-Meier分析显示,rs348624等位基因T的频率与早发性精神分裂症首发年龄显著相关( Kaplan-Meier log rank 检验p=0.00)。结论:在中国汉族人群中NOS1AP基因与早发性精神分裂症存在关联,其rs348624多态性可能是导致早发性精神分裂症患者发病年龄提前的重要因素。

  15. JiffyNet: a web-based instant protein network modeler for newly sequenced species.

    Science.gov (United States)

    Kim, Eiru; Kim, Hanhae; Lee, Insuk

    2013-07-01

    Revolutionary DNA sequencing technology has enabled affordable genome sequencing for numerous species. Thousands of species already have completely decoded genomes, and tens of thousands more are in progress. Naturally, parallel expansion of the functional parts list library is anticipated, yet genome-level understanding of function also requires maps of functional relationships, such as functional protein networks. Such networks have been constructed for many sequenced species including common model organisms. Nevertheless, the majority of species with sequenced genomes still have no protein network models available. Moreover, biologists might want to obtain protein networks for their species of interest on completion of the genome projects. Therefore, there is high demand for accessible means to automatically construct genome-scale protein networks based on sequence information from genome projects only. Here, we present a public web server, JiffyNet, specifically designed to instantly construct genome-scale protein networks based on associalogs (functional associations transferred from a template network by orthology) for a query species with only protein sequences provided. Assessment of the networks by JiffyNet demonstrated generally high predictive ability for pathway annotations. Furthermore, JiffyNet provides network visualization and analysis pages for wide variety of molecular concepts to facilitate network-guided hypothesis generation. JiffyNet is freely accessible at http://www.jiffynet.org.

  16. A Shortest Dependency Path Based Convolutional Neural Network for Protein-Protein Relation Extraction

    Directory of Open Access Journals (Sweden)

    Lei Hua

    2016-01-01

    Full Text Available The state-of-the-art methods for protein-protein interaction (PPI extraction are primarily based on kernel methods, and their performances strongly depend on the handcraft features. In this paper, we tackle PPI extraction by using convolutional neural networks (CNN and propose a shortest dependency path based CNN (sdpCNN model. The proposed method (1 only takes the sdp and word embedding as input and (2 could avoid bias from feature selection by using CNN. We performed experiments on standard Aimed and BioInfer datasets, and the experimental results demonstrated that our approach outperformed state-of-the-art kernel based methods. In particular, by tracking the sdpCNN model, we find that sdpCNN could extract key features automatically and it is verified that pretrained word embedding is crucial in PPI task.

  17. A Shortest Dependency Path Based Convolutional Neural Network for Protein-Protein Relation Extraction.

    Science.gov (United States)

    Hua, Lei; Quan, Chanqin

    2016-01-01

    The state-of-the-art methods for protein-protein interaction (PPI) extraction are primarily based on kernel methods, and their performances strongly depend on the handcraft features. In this paper, we tackle PPI extraction by using convolutional neural networks (CNN) and propose a shortest dependency path based CNN (sdpCNN) model. The proposed method (1) only takes the sdp and word embedding as input and (2) could avoid bias from feature selection by using CNN. We performed experiments on standard Aimed and BioInfer datasets, and the experimental results demonstrated that our approach outperformed state-of-the-art kernel based methods. In particular, by tracking the sdpCNN model, we find that sdpCNN could extract key features automatically and it is verified that pretrained word embedding is crucial in PPI task.

  18. A Shortest Dependency Path Based Convolutional Neural Network for Protein-Protein Relation Extraction

    Science.gov (United States)

    Quan, Chanqin

    2016-01-01

    The state-of-the-art methods for protein-protein interaction (PPI) extraction are primarily based on kernel methods, and their performances strongly depend on the handcraft features. In this paper, we tackle PPI extraction by using convolutional neural networks (CNN) and propose a shortest dependency path based CNN (sdpCNN) model. The proposed method (1) only takes the sdp and word embedding as input and (2) could avoid bias from feature selection by using CNN. We performed experiments on standard Aimed and BioInfer datasets, and the experimental results demonstrated that our approach outperformed state-of-the-art kernel based methods. In particular, by tracking the sdpCNN model, we find that sdpCNN could extract key features automatically and it is verified that pretrained word embedding is crucial in PPI task. PMID:27493967

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

    CERN Document Server

    Antal, Miklos A; Csermely, Peter

    2008-01-01

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

  20. Proteomic shifts in embryonic stem cells with gene dose modifications suggest the presence of balancer proteins in protein regulatory networks.

    Directory of Open Access Journals (Sweden)

    Lei Mao

    Full Text Available Large numbers of protein expression changes are usually observed in mouse models for neurodegenerative diseases, even when only a single gene was mutated in each case. To study the effect of gene dose alterations on the cellular proteome, we carried out a proteomic investigation on murine embryonic stem cells that either overexpressed individual genes or displayed aneuploidy over a genomic region encompassing 14 genes. The number of variant proteins detected per cell line ranged between 70 and 110, and did not correlate with the number of modified genes. In cell lines with single gene mutations, up and down-regulated proteins were always in balance in comparison to parental cell lines regarding number as well as concentration of differentially expressed proteins. In contrast, dose alteration of 14 genes resulted in an unequal number of up and down-regulated proteins, though the balance was kept at the level of protein concentration. We propose that the observed protein changes might partially be explained by a proteomic network response. Hence, we hypothesize the existence of a class of "balancer" proteins within the proteomic network, defined as proteins that buffer or cushion a system, and thus oppose multiple system disturbances. Through database queries and resilience analysis of the protein interaction network, we found that potential balancer proteins are of high cellular abundance, possess a low number of direct interaction partners, and show great allelic variation. Moreover, balancer proteins contribute more heavily to the network entropy, and thus are of high importance in terms of system resilience. We propose that the "elasticity" of the proteomic regulatory network mediated by balancer proteins may compensate for changes that occur under diseased conditions.

  1. ModuleRole: A Tool for Modulization, Role Determination and Visualization in Protein-Protein Interaction Networks

    OpenAIRE

    Guipeng Li; Ming Li; Yiwei Zhang; Dong Wang; Rong Li; Roger Guimerà; Juntao Tony Gao; Zhang, Michael Q

    2014-01-01

    Rapidly increasing amounts of (physical and genetic) protein-protein interaction (PPI) data are produced by various high-throughput techniques, and interpretation of these data remains a major challenge. In order to gain insight into the organization and structure of the resultant large complex networks formed by interacting molecules, using simulated annealing, a method based on the node connectivity, we developed ModuleRole, a user-friendly web server tool which finds modules in PPI network...

  2. Topology association analysis in weighted protein interaction network for gene prioritization

    Science.gov (United States)

    Wu, Shunyao; Shao, Fengjing; Zhang, Qi; Ji, Jun; Xu, Shaojie; Sun, Rencheng; Sun, Gengxin; Du, Xiangjun; Sui, Yi

    2016-11-01

    Although lots of algorithms for disease gene prediction have been proposed, the weights of edges are rarely taken into account. In this paper, the strengths of topology associations between disease and essential genes are analyzed in weighted protein interaction network. Empirical analysis demonstrates that compared to other genes, disease genes are weakly connected with essential genes in protein interaction network. Based on this finding, a novel global distance measurement for gene prioritization with weighted protein interaction network is proposed in this paper. Positive and negative flow is allocated to disease and essential genes, respectively. Additionally network propagation model is extended for weighted network. Experimental results on 110 diseases verify the effectiveness and potential of the proposed measurement. Moreover, weak links play more important role than strong links for gene prioritization, which is meaningful to deeply understand protein interaction network.

  3. Evolutionary Genomics Suggests That CheV Is an Additional Adaptor for Accommodating Specific Chemoreceptors within the Chemotaxis Signaling Complex.

    Directory of Open Access Journals (Sweden)

    Davi R Ortega

    2016-02-01

    Full Text Available Escherichia coli and Salmonella enterica are models for many experiments in molecular biology including chemotaxis, and most of the results obtained with one organism have been generalized to another. While most components of the chemotaxis pathway are strongly conserved between the two species, Salmonella genomes contain some chemoreceptors and an additional protein, CheV, that are not found in E. coli. The role of CheV was examined in distantly related species Bacillus subtilis and Helicobacter pylori, but its role in bacterial chemotaxis is still not well understood. We tested a hypothesis that in enterobacteria CheV functions as an additional adaptor linking the CheA kinase to certain types of chemoreceptors that cannot be effectively accommodated by the universal adaptor CheW. Phylogenetic profiling, genomic context and comparative protein sequence analyses suggested that CheV interacts with specific domains of CheA and chemoreceptors from an orthologous group exemplified by the Salmonella McpC protein. Structural consideration of the conservation patterns suggests that CheV and CheW share the same binding spot on the chemoreceptor structure, but have some affinity bias towards chemoreceptors from different orthologous groups. Finally, published experimental results and data newly obtained via comparative genomics support the idea that CheV functions as a "phosphate sink" possibly to off-set the over-stimulation of the kinase by certain types of chemoreceptors. Overall, our results strongly suggest that CheV is an additional adaptor for accommodating specific chemoreceptors within the chemotaxis signaling complex.

  4. Evolutionary Genomics Suggests That CheV Is an Additional Adaptor for Accommodating Specific Chemoreceptors within the Chemotaxis Signaling Complex.

    Science.gov (United States)

    Ortega, Davi R; Zhulin, Igor B

    2016-02-01

    Escherichia coli and Salmonella enterica are models for many experiments in molecular biology including chemotaxis, and most of the results obtained with one organism have been generalized to another. While most components of the chemotaxis pathway are strongly conserved between the two species, Salmonella genomes contain some chemoreceptors and an additional protein, CheV, that are not found in E. coli. The role of CheV was examined in distantly related species Bacillus subtilis and Helicobacter pylori, but its role in bacterial chemotaxis is still not well understood. We tested a hypothesis that in enterobacteria CheV functions as an additional adaptor linking the CheA kinase to certain types of chemoreceptors that cannot be effectively accommodated by the universal adaptor CheW. Phylogenetic profiling, genomic context and comparative protein sequence analyses suggested that CheV interacts with specific domains of CheA and chemoreceptors from an orthologous group exemplified by the Salmonella McpC protein. Structural consideration of the conservation patterns suggests that CheV and CheW share the same binding spot on the chemoreceptor structure, but have some affinity bias towards chemoreceptors from different orthologous groups. Finally, published experimental results and data newly obtained via comparative genomics support the idea that CheV functions as a "phosphate sink" possibly to off-set the over-stimulation of the kinase by certain types of chemoreceptors. Overall, our results strongly suggest that CheV is an additional adaptor for accommodating specific chemoreceptors within the chemotaxis signaling complex.

  5. Radioresistance related genes screened by protein-protein interaction network analysis in nasopharyngeal carcinoma

    International Nuclear Information System (INIS)

    Objective: To discover radioresistance associated molecular biomarkers and its mechanism in nasopharyngeal carcinoma by protein-protein interaction network analysis. Methods: Whole genome expression microarray was applied to screen out differentially expressed genes in two cell lines CNE-2R and CNE-2 with different radiosensitivity. Four differentially expressed genes were randomly selected for further verification by the semi-quantitative RT-PCR analysis with self-designed primers. The common differentially expressed genes from two experiments were analyzed with the SNOW online database in order to find out the central node related to the biomarkers of nasopharyngeal carcinoma radioresistance. The expression of STAT1 in CNE-2R and CNE-2 cells was measured by Western blot. Results: Compared with CNE-2 cells, 374 genes in CNE-2R cells were differentially expressed while 197 genes showed significant differences. Four randomly selected differentially expressed genes were verified by RT-PCR and had same change trend in consistent with the results of chip assay. Analysis with the SNOW database demonstrated that those 197 genes could form a complicated interaction network where STAT1 and JUN might be two key nodes. Indeed, the STAT1-α expression in CNE-2R was higher than that in CNE-2 (t=4.96, P<0.05). Conclusions: The key nodes of STAT1 and JUN may be the molecular biomarkers leading to radioresistance in nasopharyngeal carcinoma, and STAT1-α might have close relationship with radioresistance. (authors)

  6. Molecular Principles of Gene Fusion Mediated Rewiring of Protein Interaction Networks in Cancer.

    Science.gov (United States)

    Latysheva, Natasha S; Oates, Matt E; Maddox, Louis; Flock, Tilman; Gough, Julian; Buljan, Marija; Weatheritt, Robert J; Babu, M Madan

    2016-08-18

    Gene fusions are common cancer-causing mutations, but the molecular principles by which fusion protein products affect interaction networks and cause disease are not well understood. Here, we perform an integrative analysis of the structural, interactomic, and regulatory properties of thousands of putative fusion proteins. We demonstrate that genes that form fusions (i.e., parent genes) tend to be highly connected hub genes, whose protein products are enriched in structured and disordered interaction-mediating features. Fusion often results in the loss of these parental features and the depletion of regulatory sites such as post-translational modifications. Fusion products disproportionately connect proteins that did not previously interact in the protein interaction network. In this manner, fusion products can escape cellular regulation and constitutively rewire protein interaction networks. We suggest that the deregulation of central, interaction-prone proteins may represent a widespread mechanism by which fusion proteins alter the topology of cellular signaling pathways and promote cancer. PMID:27540857

  7. Analysis of Arf1 GTPase-dependent membrane binding and remodeling using the exomer secretory vesicle cargo adaptor

    Science.gov (United States)

    Paczkowski, Jon E.; Fromme, J. Christopher

    2016-01-01

    Summary Protein-protein and protein-membrane interactions play a critical role in shaping biological membranes through direct physical contact with the membrane surface. This is particularly evident in many steps of membrane trafficking, in which proteins deform the membrane and induce fission to form transport carriers. The small GTPase Arf1 and related proteins have the ability to remodel membranes by insertion of an amphipathic helix into the membrane. Arf1 and the exomer cargo adaptor coordinate cargo sorting into subset of secretory vesicle carriers in the model organism Saccharomyces cerevisiae. Here, we detail the assays we used to explore the cooperative action of Arf1 and exomer to bind and remodel membranes. We expect these methods are broadly applicable to other small GTPase/effector systems where investigation of membrane binding and remodeling is of interest. PMID:27632000

  8. Pathway Analysis Incorporating Protein-Protein Interaction Networks Identified Candidate Pathways for the Seven Common Diseases.

    Science.gov (United States)

    Lin, Peng-Lin; Yu, Ya-Wen; Chung, Ren-Hua

    2016-01-01

    Pathway analysis has become popular as a secondary analysis strategy for genome-wide association studies (GWAS). Most of the current pathway analysis methods aggregate signals from the main effects of single nucleotide polymorphisms (SNPs) in genes within a pathway without considering the effects of gene-gene interactions. However, gene-gene interactions can also have critical effects on complex diseases. Protein-protein interaction (PPI) networks have been used to define gene pairs for the gene-gene interaction tests. Incorporating the PPI information to define gene pairs for interaction tests within pathways can increase the power for pathway-based association tests. We propose a pathway association test, which aggregates the interaction signals in PPI networks within a pathway, for GWAS with case-control samples. Gene size is properly considered in the test so that genes do not contribute more to the test statistic simply due to their size. Simulation studies were performed to verify that the method is a valid test and can have more power than other pathway association tests in the presence of gene-gene interactions within a pathway under different scenarios. We applied the test to the Wellcome Trust Case Control Consortium GWAS datasets for seven common diseases. The most significant pathway is the chaperones modulate interferon signaling pathway for Crohn's disease (p-value = 0.0003). The pathway modulates interferon gamma, which induces the JAK/STAT pathway that is involved in Crohn's disease. Several other pathways that have functional implications for the seven diseases were also identified. The proposed test based on gene-gene interaction signals in PPI networks can be used as a complementary tool to the current existing pathway analysis methods focusing on main effects of genes. An efficient software implementing the method is freely available at http://puppi.sourceforge.net. PMID:27622767

  9. The AP-1A and AP-1B clathrin adaptor complexes define biochemically and functionally distinct membrane domains

    OpenAIRE

    Fölsch, Heike; Pypaert, Marc; Maday, Sandra; Pelletier, Laurence; Mellman, Ira

    2003-01-01

    Most epithelial cells contain two AP-1 clathrin adaptor complexes. AP-1A is ubiquitously expressed and involved in transport between the TGN and endosomes. AP-1B is expressed only in epithelia and mediates the polarized targeting of membrane proteins to the basolateral surface. Both AP-1 complexes are heterotetramers and differ only in their 50-kD μ1A or μ1B subunits. Here, we show that AP-1A and AP-1B, together with their respective cargoes, define physically and functionally distinct membra...

  10. Targeting the Human Cancer Pathway Protein Interaction Network by Structural Genomics*

    OpenAIRE

    Huang, Yuanpeng Janet; Hang, Dehua; Lu, Long Jason; Tong, Liang; Gerstein, Mark B; Montelione, Gaetano T.

    2008-01-01

    Structural genomics provides an important approach for characterizing and understanding systems biology. As a step toward better integrating protein three-dimensional (3D) structural information in cancer systems biology, we have constructed a Human Cancer Pathway Protein Interaction Network (HCPIN) by analysis of several classical cancer-associated signaling pathways and their physical protein-protein interactions. Many well known cancer-associated proteins play central roles as “hubs” or “b...

  11. DMPD: Signalling adaptors used by Toll-like receptors: an update. [Dynamic Macrophage Pathway CSML Database

    Lifescience Database Archive (English)

    Full Text Available 18706831 Signalling adaptors used by Toll-like receptors: an update. Kenny EF, O'Ne...tors used by Toll-like receptors: an update. PubmedID 18706831 Title Signalling adaptors used by Toll-like receptors: an update

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

    Science.gov (United States)

    Kwang, Ng Aik; Rodrigues, Daphne

    2002-01-01

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

  13. The integrated analysis of metabolic and protein interaction networks reveals novel molecular organizing principles

    Directory of Open Access Journals (Sweden)

    Walther Dirk

    2008-11-01

    Full Text Available Abstract Background The study of biological interaction networks is a central theme of systems biology. Here, we investigate the relationships between two distinct types of interaction networks: the metabolic pathway map and the protein-protein interaction network (PIN. It has long been established that successive enzymatic steps are often catalyzed by physically interacting proteins forming permanent or transient multi-enzymes complexes. Inspecting high-throughput PIN data, it was shown recently that, indeed, enzymes involved in successive reactions are generally more likely to interact than other protein pairs. In our study, we expanded this line of research to include comparisons of the underlying respective network topologies as well as to investigate whether the spatial organization of enzyme interactions correlates with metabolic efficiency. Results Analyzing yeast data, we detected long-range correlations between shortest paths between proteins in both network types suggesting a mutual correspondence of both network architectures. We discovered that the organizing principles of physical interactions between metabolic enzymes differ from the general PIN of all proteins. While physical interactions between proteins are generally dissortative, enzyme interactions were observed to be assortative. Thus, enzymes frequently interact with other enzymes of similar rather than different degree. Enzymes carrying high flux loads are more likely to physically interact than enzymes with lower metabolic throughput. In particular, enzymes associated with catabolic pathways as well as enzymes involved in the biosynthesis of complex molecules were found to exhibit high degrees of physical clustering. Single proteins were identified that connect major components of the cellular metabolism and may thus be essential for the structural integrity of several biosynthetic systems. Conclusion Our results reveal topological equivalences between the protein

  14. Protein co-expression network analysis (ProCoNA)

    OpenAIRE

    Gibbs, David L.; Baratt, Arie; Baric, Ralph S.; Kawaoka, Yoshihiro; Smith, Richard D.; Orwoll, Eric S.; Michael G Katze; McWeeney, Shannon K.

    2013-01-01

    Background Biological networks are important for elucidating disease etiology due to their ability to model complex high dimensional data and biological systems. Proteomics provides a critical data source for such models, but currently lacks robust de novo methods for network construction, which could bring important insights in systems biology. Results We have evaluated the construction of network models using methods derived from weighted gene co-expression network analysis (WGCNA). We show...

  15. Modeling the two-hybrid detector: experimental bias on protein interaction networks.

    Science.gov (United States)

    Stibius, Karin B; Sneppen, Kim

    2007-10-01

    This work was done to investigate the two-hybrid experiment for finding protein-protein interactions to explain the asymmetry found in the experimental data, and to help screen the data for high confidence interactions. By looking at the bait-prey experimental setup the resulting protein interaction network can be examined as a directed network (bait --> prey). We have investigated two possible scenarios for the asymmetry in the directed network by developing a biochemical model for the protein-DNA and protein-protein bindings inside the living yeast. One scenario assumes a background activity of bait proteins acting even without the prey, the other scenario explores the asymmetry in the chemistry associated with the bait being automatically located in the right position on the DNA. We conclude that the latter model gives the best description of the observed asymmetry. PMID:17557786

  16. Selection on Network Dynamics Drives Differential Rates of Protein Domain Evolution.

    Science.gov (United States)

    Mannakee, Brian K; Gutenkunst, Ryan N

    2016-07-01

    The long-held principle that functionally important proteins evolve slowly has recently been challenged by studies in mice and yeast showing that the severity of a protein knockout only weakly predicts that protein's rate of evolution. However, the relevance of these studies to evolutionary changes within proteins is unknown, because amino acid substitutions, unlike knockouts, often only slightly perturb protein activity. To quantify the phenotypic effect of small biochemical perturbations, we developed an approach to use computational systems biology models to measure the influence of individual reaction rate constants on network dynamics. We show that this dynamical influence is predictive of protein domain evolutionary rate within networks in vertebrates and yeast, even after controlling for expression level and breadth, network topology, and knockout effect. Thus, our results not only demonstrate the importance of protein domain function in determining evolutionary rate, but also the power of systems biology modeling to uncover unanticipated evolutionary forces.

  17. Selection on Network Dynamics Drives Differential Rates of Protein Domain Evolution.

    Directory of Open Access Journals (Sweden)

    Brian K Mannakee

    2016-07-01

    Full Text Available The long-held principle that functionally important proteins evolve slowly has recently been challenged by studies in mice and yeast showing that the severity of a protein knockout only weakly predicts that protein's rate of evolution. However, the relevance of these studies to evolutionary changes within proteins is unknown, because amino acid substitutions, unlike knockouts, often only slightly perturb protein activity. To quantify the phenotypic effect of small biochemical perturbations, we developed an approach to use computational systems biology models to measure the influence of individual reaction rate constants on network dynamics. We show that this dynamical influence is predictive of protein domain evolutionary rate within networks in vertebrates and yeast, even after controlling for expression level and breadth, network topology, and knockout effect. Thus, our results not only demonstrate the importance of protein domain function in determining evolutionary rate, but also the power of systems biology modeling to uncover unanticipated evolutionary forces.

  18. FunMod: A Cytoscape Plugin for Identifying Functional Modules in Undirected Protein–Protein Networks

    Directory of Open Access Journals (Sweden)

    Massimo Natale

    2014-08-01

    Full Text Available The characterization of the interacting behaviors of complex biological systems is a primary objective in protein–protein network analysis and computational biology. In this paper we present FunMod, an innovative Cytoscape version 2.8 plugin that is able to mine undirected protein–protein networks and to infer sub-networks of interacting proteins intimately correlated with relevant biological pathways. This plugin may enable the discovery of new pathways involved in diseases. In order to describe the role of each protein within the relevant biological pathways, FunMod computes and scores three topological features of the identified sub-networks. By integrating the results from biological pathway clustering and topological network analysis, FunMod proved to be useful for the data interpretation and the generation of new hypotheses in two case studies.

  19. 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.

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

    Directory of Open Access Journals (Sweden)

    Boucher Charles AB

    2010-07-01

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

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

    Science.gov (United States)

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

    2014-03-01

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

  2. p42.3 gene expression in gastric cancer cell and its protein regulatory network analysis

    Directory of Open Access Journals (Sweden)

    Zhang Jianhua

    2012-12-01

    Full Text Available Abstract Background To analyze the p42.3 gene expression in gastric cancer (GC cell, find the relationship between protein structure and function, establish the regulatory network of p42.3 protein molecule and then to obtain the optimal regulatory pathway. Methods The expression of p42.3 gene was analyzed by RT-PCR, Western Blot and other biotechnologies. The relationship between the spatial conformation of p42.3 protein molecule and its function was analyzed using bioinformatics, MATLAB and related knowledge about protein structure and function. Furthermore, based on similarity algorithm of spatial layered spherical coordinate, we compared p42.3 molecule with several similar structured proteins which are known for the function, screened the characteristic nodes related to tumorigenesis and development, and established the multi variable relational model between p42.3 protein expression, cell cycle regulation and biological characteristics in the level of molecular regulatory networks. Finally, the optimal regulatory network was found by using Bayesian network. Results (1 The expression amount of p42.3 in G1 and M phase was higher than that in S and G2 phase; (2 The space coordinate systems of different structural domains of p42.3 protein were established in Matlab7.0 software; (3 The optimal pathway of p42.3 gene in protein regulatory network in gastric cancer is Ras protein, Raf-1 protein, MEK, MAPK kinase, MAPK, tubulin, spindle protein, centromere protein and tumor. Conclusion It is of vital significance for mechanism research to find out the action pathway of p42.3 in protein regulatory network, since p42.3 protein plays an important role in the generation and development of GC.

  3. 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.

  4. The use of Gene Ontology terms for predicting highly-connected 'hub' nodes in protein-protein interaction networks

    Directory of Open Access Journals (Sweden)

    Cherkasov Artem

    2008-09-01

    Full Text Available Abstract Background Protein-protein interactions mediate a wide range of cellular functions and responses and have been studied rigorously through recent large-scale proteomics experiments and bioinformatics analyses. One of the most important findings of those endeavours was the observation that 'hub' proteins participate in significant numbers of protein interactions and play critical roles in the organization and function of cellular protein interaction networks (PINs 12. It has also been demonstrated that such hub proteins may constitute an important pool of attractive drug targets. Thus, it is crucial to be able to identify hub proteins based not only on experimental data but also by means of bioinformatics predictions. Results A hub protein classifier has been developed based on the available interaction data and Gene Ontology (GO annotations for proteins in the Escherichia coli, Saccharomyces cerevisiae, Drosophila melanogaster and Homo sapiens genomes. In particular, by utilizing the machine learning method of boosting trees we were able to create a predictive bioinformatics tool for the identification of proteins that are likely to play the role of a hub in protein interaction networks. Testing the developed hub classifier on external sets of experimental protein interaction data in Methicillin-resistant Staphylococcus aureus (MRSA 252 and Caenorhabditis elegans demonstrated that our approach can predict hub proteins with a high degree of accuracy. A practical application of the developed bioinformatics method has been illustrated by the effective protein bait selection for large-scale pull-down experiments that aim to map complete protein-protein interaction networks for several species. Conclusion The successful development of an accurate hub classifier demonstrated that highly-connected proteins tend to share certain relevant functional properties reflected in their Gene Ontology annotations. It is anticipated that the developed

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

    Directory of Open Access Journals (Sweden)

    Mazo Ilya

    2007-07-01

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

  6. A local average connectivity-based method for identifying essential proteins from the network level.

    Science.gov (United States)

    Li, Min; Wang, Jianxin; Chen, Xiang; Wang, Huan; Pan, Yi

    2011-06-01

    Identifying essential proteins is very important for understanding the minimal requirements of cellular survival and development. Fast growth in the amount of available protein-protein interactions has produced unprecedented opportunities for detecting protein essentiality from the network level. Essential proteins have been found to be more abundant among those highly connected proteins. However, there exist a number of highly connected proteins which are not essential. By analyzing these proteins, we find that few of their neighbors interact with each other. Thus, we propose a new local method, named LAC, to determine a protein's essentiality by evaluating the relationship between a protein and its neighbors. The performance of LAC is validated based on the yeast protein interaction networks obtained from two different databases: DIP and BioGRID. The experimental results of the two networks show that the number of essential proteins predicted by LAC clearly exceeds that explored by Degree Centrality (DC). More over, LAC is also compared with other seven measures of protein centrality (Neighborhood Component (DMNC), Betweenness Centrality (BC), Closeness Centrality (CC), Bottle Neck (BN), Information Centrality (IC), Eigenvector Centrality (EC), and Subgraph Centrality (SC)) in identifying essential proteins. The comparison results based on the validations of sensitivity, specificity, F-measure, positive predictive value, negative predictive value, and accuracy consistently show that LAC outweighs these seven previous methods. PMID:21704260

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

    Directory of Open Access Journals (Sweden)

    Rajesh Chowdhary

    Full Text Available 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/.

  8. SEBINI-CABIN: An Analysis Pipeline for Biological Network Inference, with a Case Study in Protein-Protein Interaction Network Reconstruction

    Energy Technology Data Exchange (ETDEWEB)

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

    2007-12-01

    One of the core tasks of the emerging discipline of systems biology is the reconstruction of the various biological networks in an organism. The importance of understanding such regulatory, interaction, and signaling networks has fueled the development by bioinformatics researchers of many inference algorithms for determining their structure. The Software Environment for BIological Network Inference (SEBINI) has been created to provide an interactive environment for the deployment, testing, and improvement of algorithms used to reconstruct the structures of regulatory and interaction networks from high-throughput expression data. Networks inferred from the SEBINI software platform can be further analyzed using the Collective Analysis of Biological Interaction Networks (CABIN) tool, a software package for exploratory data analysis that allows basic integration and analysis of protein-protein interaction and gene-to-gene regulatory evidence obtained from multiple sources. Thus, the combined SEBINI–CABIN platform aids in the more accurate determination of biological networks, in less time, with less effort. In this paper, we present a case study demonstrating the use of the SEBINI and CABIN tools for protein-protein interaction network reconstruction. Incorporating the Bayesian Estimator of Protein-Protein Association Probabilities (BEPro) algorithm into the SEBINI toolkit, we have created a pipeline for structural inference and supplemental analysis of protein-protein interaction networks from sets of mass spectrometry bait-prey experiment data. To the best of our knowledge the pipeline so designed is the first to be publicly available for such use. A demonstration web site for SEBINI can be accessed from https://www.emsl.pnl.gov/NIT/NIT.html. Source code and PostgreSQL database schema are available under open source license. Contact: ronald.taylor@pnl.gov. For commercial use, some algorithms included in SEBINI require licensing from the original developers. The

  9. DMPD: TIR domain-containing adaptors define the specificity of TLR signaling. [Dynamic Macrophage Pathway CSML Database

    Lifescience Database Archive (English)

    Full Text Available 14698224 TIR domain-containing adaptors define the specificity of TLR signaling. Ya...in-containing adaptors define the specificity of TLR signaling. PubmedID 14698224 Title TIR domain-containing adaptors define the spe...cificity of TLR signaling. Authors Yamamoto M, Takeda K,

  10. On the Variability of Neural Network Classification Measures in the Protein Secondary Structure Prediction Problem

    Directory of Open Access Journals (Sweden)

    Eric Sakk

    2013-01-01

    Full Text Available We revisit the protein secondary structure prediction problem using linear and backpropagation neural network architectures commonly applied in the literature. In this context, neural network mappings are constructed between protein training set sequences and their assigned structure classes in order to analyze the class membership of test data and associated measures of significance. We present numerical results demonstrating that classifier performance measures can vary significantly depending upon the classifier architecture and the structure class encoding technique. Furthermore, an analytic formulation is introduced in order to substantiate the observed numerical data. Finally, we analyze and discuss the ability of the neural network to accurately model fundamental attributes of protein secondary structure.

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Directory of Open Access Journals (Sweden)

    Ramanathan Murali

    2007-07-01

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

  13. Selection on Network Dynamics Drives Differential Rates of Protein Domain Evolution

    Science.gov (United States)

    Mannakee, Brian K.; Gutenkunst, Ryan N.

    2016-01-01

    The long-held principle that functionally important proteins evolve slowly has recently been challenged by studies in mice and yeast showing that the severity of a protein knockout only weakly predicts that protein’s rate of evolution. However, the relevance of these studies to evolutionary changes within proteins is unknown, because amino acid substitutions, unlike knockouts, often only slightly perturb protein activity. To quantify the phenotypic effect of small biochemical perturbations, we developed an approach to use computational systems biology models to measure the influence of individual reaction rate constants on network dynamics. We show that this dynamical influence is predictive of protein domain evolutionary rate within networks in vertebrates and yeast, even after controlling for expression level and breadth, network topology, and knockout effect. Thus, our results not only demonstrate the importance of protein domain function in determining evolutionary rate, but also the power of systems biology modeling to uncover unanticipated evolutionary forces. PMID:27380265

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

    Directory of Open Access Journals (Sweden)

    Chiranjib Chakraborty

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

  15. Predicting Pharmacodynamic Drug-Drug Interactions through Signaling Propagation Interference on Protein-Protein Interaction Networks.

    Directory of Open Access Journals (Sweden)

    Kyunghyun Park

    Full Text Available As pharmacodynamic drug-drug interactions (PD DDIs could lead to severe adverse effects in patients, it is important to identify potential PD DDIs in drug development. The signaling starting from drug targets is propagated through protein-protein interaction (PPI networks. PD DDIs could occur by close interference on the same targets or within the same pathways as well as distant interference through cross-talking pathways. However, most of the previous approaches have considered only close interference by measuring distances between drug targets or comparing target neighbors. We have applied a random walk with restart algorithm to simulate signaling propagation from drug targets in order to capture the possibility of their distant interference. Cross validation with DrugBank and Kyoto Encyclopedia of Genes and Genomes DRUG shows that the proposed method outperforms the previous methods significantly. We also provide a web service with which PD DDIs for drug pairs can be analyzed at http://biosoft.kaist.ac.kr/targetrw.

  16. 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.

  17. Convolutional LSTM Networks for Subcellular Localization of Proteins

    DEFF Research Database (Denmark)

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

    Machine learning is widely used to analyze biological sequence data. Non-sequential models such as SVMs or feed-forward neural networks are often used although they have no natural way of handling sequences of varying length. Recurrent neural networks such as the long short term memory (LSTM) model...

  18. Convolutional LSTM Networks for Subcellular Localization of Proteins

    DEFF Research Database (Denmark)

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

    2015-01-01

    Machine learning is widely used to analyze biological sequence data. Non-sequential models such as SVMs or feed-forward neural networks are often used although they have no natural way of handling sequences of varying length. Recurrent neural networks such as the long short term memory (LSTM) mod...

  19. 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.

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

    International Nuclear Information System (INIS)

    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

  1. [The study on the characters of membrane protein interaction and its network based on integrated intelligence method].

    Science.gov (United States)

    Shen, Yizhen; Ding, Yongsheng; Hao, Kuangrong

    2011-08-01

    Membrane protein and its interaction network have become a novel research direction in bioinformatics. In this paper, a novel membrane protein interaction network simulator is proposed for system biology studies by integrated intelligence method including spectrum analysis, fuzzy K-Nearest Neighbor(KNN) algorithm and so on. We consider biological system as a set of active computational components interacting with each other and with the external environment. Then we can use the network simulator to construct membrane protein interaction networks. Based on the proposed approach, we found that the membrane protein interaction network almost has some dynamic and collective characteristics, such as small-world network, scale free distributing, and hierarchical module structure. These properties are similar to those of other extensively studied protein interaction networks. The present studies on the characteristics of the membrane protein interaction network will be valuable for its relatively biological and medical studies. PMID:21936357

  2. Small-World Effect of Complex Network and Its Application toProtein Folding

    Institute of Scientific and Technical Information of China (English)

    卢全国; 陈宝方; 彭华魁; 祖巧红

    2004-01-01

    The famous "six letters" experiment carried out by Milgram demonstrated the existence of small-world effect in a complex network. One vertex tends to be connected to another by a shortest path through network because of the small-world effect. This paper uses the small-world effect to study protein folding pathway.

  3. Emergence of Complexity in Protein Functions and Metabolic Networks

    Science.gov (United States)

    Pohorille, Andzej

    2009-01-01

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

  4. Revisiting topological properties and models of protein-protein interaction networks from the perspective of dataset evolution.

    Science.gov (United States)

    Shao, Mingyu; Zhou, Shuigeng; Guan, Jihong

    2015-08-01

    Protein-protein interaction (PPI) networks are crucial for organisms. Many research efforts have thus been devoted to the study on the topological properties and models of PPI networks. However, existing studies did not always report consistent results on the topological properties of PPI networks. Although a number of PPI network models have been introduced, yet in the literature there is no convincing conclusion on which model is best for describing PPI networks. This situation is primarily caused by the incompleteness of current PPI datasets. To solve this problem, in this study, the authors propose to revisit the topological properties and models of PPI networks from the perspective of PPI dataset evolution. Concretely, they used 12 PPI datasets of Arabidopsis thaliana and 10 PPI datasets of Saccharomyces cerevisiae from different Biological General Repository for Interaction Datasets (BioGRID) database versions, and compared the topological properties of these datasets and the fitting capabilities of five typical PPI network models over these datasets. PMID:26243826

  5. The Effect of Edge Definition of Complex Networks on Protein Structure Identification

    Directory of Open Access Journals (Sweden)

    Jing Sun

    2013-01-01

    Full Text Available The main objective of this study is to explore the contribution of complex network together with its different definitions of vertexes and edges to describe the structure of proteins. Protein folds into a specific conformation for its function depending on interactions between residues. Consequently, in many studies, a protein structure was treated as a complex system comprised of individual components residues, and edges were interactions between residues. What is the proper time for representing a protein structure as a network? To confirm the effect of different definitions of vertexes and edges in constructing the amino acid interaction networks, protein domains and the structural unit of proteins were described using this method. The identification performance of 2847 proteins with domain/domains proved that the structure of proteins was described well when was around 5.0–7.5 Å, and the optimal cutoff value for constructing the protein structure networks was 5.0 Å ( distances while the ideal community division method was community structure detection based on edge betweenness in this study.

  6. The AP-3 adaptor complex is required for vacuolar function in Arabidopsis

    Institute of Scientific and Technical Information of China (English)

    Maria Zwiewka; Elena Feraru; Barbara M(o)ller; Inhwan Hwang; Mugurel I Feraru; Jürgen Kleine-Vehn; Dolf Weijers; Ji(n) Friml

    2011-01-01

    Subcellular trafficking is required for a multitude of functions in eukaryotic cells.It involves regulation of cargo sorting,vesicle formation,trafficking and fusion processes at multiple levels.Adaptor protein (AP) complexes are key regulators of cargo sorting into vesicles in yeast and mammals but their existence and function in plants have not been demonstrated.Here we report the identification of the protein-affected trafficking 4 (pat4) mutant defective in the putative δ subunit of the AP-3 complex.pat4 and pat2,a mutant isolated from the same GFP imaging-based forward genetic screen that lacks a functional putative AP-3 β,as well as dominant negative AP-3 μ transgenic lines display undistinguishable phenotypes characterized by largely normal morphology and development,but strong intracellular accumulation of membrane proteins in aberrant vacuolar structures.All mutants are defective in morphology and function of lytic and protein storage vacuoles (PSVs) but show normal sorting of reserve proteins to PSVs.Immunoprecipitation experiments and genetic studies revealed tight functional and physical associations of putative AP-3 β and AP-3 δ subunits.Furthermore,both proteins are closely linked with putative AP-3 μ and σ subunits and several components of the clathrin and dynamin machineries.Taken together,these results demonstrate that AP complexes,similar to those in other eukaryotes,exist in plants,and that AP-3 plays a specific role in the regulation of biogenesis and function of vacuoles in plant cells.

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

    Directory of Open Access Journals (Sweden)

    Xu Wenchen

    2015-01-01

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

  8. Protein network signatures associated with exogenous biofuels treatments in cyanobacterium Synechocystis sp. PCC 6803

    Directory of Open Access Journals (Sweden)

    Guangsheng ePei

    2014-11-01

    Full Text Available 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 needs 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 (PPI 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 WGCNA 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.

  9. 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

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

    Science.gov (United States)

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

    2013-04-25

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

  11. Allostery mediates ligand binding to Grb2 adaptor in a mutually exclusive manner.

    Science.gov (United States)

    McDonald, Caleb B; El Hokayem, Jimmy; Zafar, Nawal; Balke, Jordan E; Bhat, Vikas; Mikles, David C; Deegan, Brian J; Seldeen, Kenneth L; Farooq, Amjad

    2013-02-01

    Allostery plays a key role in dictating the stoichiometry and thermodynamics of multi-protein complexes driving a plethora of cellular processes central to health and disease. Herein, using various biophysical tools, we demonstrate that although Sos1 nucleotide exchange factor and Gab1 docking protein recognize two non-overlapping sites within the Grb2 adaptor, allostery promotes the formation of two distinct pools of Grb2-Sos1 and Grb2-Gab1 binary signaling complexes in concert in lieu of a composite Sos1-Grb2-Gab1 ternary complex. Of particular interest is the observation that the binding of Sos1 to the nSH3 domain within Grb2 sterically blocks the binding of Gab1 to the cSH3 domain and vice versa in a mutually exclusive manner. Importantly, the formation of both the Grb2-Sos1 and Grb2-Gab1 binary complexes is governed by a stoichiometry of 2:1, whereby the respective SH3 domains within Grb2 homodimer bind to Sos1 and Gab1 via multivalent interactions. Collectively, our study sheds new light on the role of allostery in mediating cellular signaling machinery. PMID:23334917

  12. A Method for Community Detection in Protein Networks Using Spectral Optimization

    Directory of Open Access Journals (Sweden)

    Sminu Izudheen

    2011-12-01

    Full Text Available Identification of community structures in complex networks has been a challenge in many domain and discipline. In protein networks these community interactions play a vital role in identifying the outcome of many cellular mechanisms. This paper reports the use of spectral optimization of triangular modularity as an effective method to identify these community structures. The algorithm has been carefully tested on real biological data and the results acknowledge that this is a powerful method for extracting community structures from protein networks.

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

    Directory of Open Access Journals (Sweden)

    Gaston K Mazandu

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

  14. Reuse of structural domain–domain interactions in protein networks

    OpenAIRE

    Bateman Alex; Schuster-Böckler Benjamin

    2007-01-01

    Abstract Background Protein interactions are thought to be largely mediated by interactions between structural domains. Databases such as iPfam relate interactions in protein structures to known domain families. Here, we investigate how the domain interactions from the iPfam database are distributed in protein interactions taken from the HPRD, MPact, BioGRID, DIP and IntAct databases. Results We find that known structural domain interactions can only explain a subset of 4–19% of the available...

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

    Directory of Open Access Journals (Sweden)

    Jones Nick S

    2010-07-01

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

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

    DEFF Research Database (Denmark)

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

    2007-01-01

    We performed a systematic, large-scale analysis of human protein complexes comprising gene products implicated in many different categories of human disease to create a phenome-interactome network. This was done by integrating quality-controlled interactions of human proteins with a validated, co...

  17. Dynamic modularity in protein interaction networks predicts breast cancer outcome

    DEFF Research Database (Denmark)

    Taylor, Ian W; Linding, Rune; Warde-Farley, David;

    2009-01-01

    in biochemical structure were observed between the two types of hubs. Signaling domains were found more often in intermodular hub proteins, which were also more frequently associated with oncogenesis. Analysis of two breast cancer patient cohorts revealed that altered modularity of the human interactome may...... to predict patient outcome. An analysis of hub proteins identified intermodular hub proteins that are co-expressed with their interacting partners in a tissue-restricted manner and intramodular hub proteins that are co-expressed with their interacting partners in all or most tissues. Substantial differences...... be useful as an indicator of breast cancer prognosis....

  18. Redundancies in Large-scale Protein Interaction Networks

    CERN Document Server

    Samanta, M P; Samanta, Manoj Pratim; Liang, Shoudan

    2003-01-01

    Understanding functional associations among genes discovered in sequencing projects is a key issue in post-genomic biology. However, reliable interpretation of the protein interaction data has been difficult. In this work, we show that if two proteins share significantly larger number of common interaction partners than random, they have close functional associations. Analysis of publicly available data from Saccharomyces cerevisiae reveals more than 2800 reliable functional associations, 29% of which involve at least one unannotated protein. By further analyzing these associations, we derive tentative functions for 81 unannotated proteins with high certainty.

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

    Directory of Open Access Journals (Sweden)

    Anna Delprato

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

  20. Controlling for gene expression changes in transcription factor protein networks.

    Science.gov (United States)

    Banks, Charles A S; Lee, Zachary T; Boanca, Gina; Lakshminarasimhan, Mahadevan; Groppe, Brad D; Wen, Zhihui; Hattem, Gaye L; Seidel, Chris W; Florens, Laurence; Washburn, Michael P

    2014-06-01

    The development of affinity purification technologies combined with mass spectrometric analysis of purified protein mixtures has been used both to identify new protein-protein interactions and to define the subunit composition of protein complexes. Transcription factor protein interactions, however, have not been systematically analyzed using these approaches. Here, we investigated whether ectopic expression of an affinity tagged transcription factor as bait in affinity purification mass spectrometry experiments perturbs gene expression in cells, resulting in the false positive identification of bait-associated proteins when typical experimental controls are used. Using quantitative proteomics and RNA sequencing, we determined that the increase in the abundance of a set of proteins caused by overexpression of the transcription factor RelA is not sufficient for these proteins to then co-purify non-specifically and be misidentified as bait-associated proteins. Therefore, typical controls should be sufficient, and a number of different baits can be compared with a common set of controls. This is of practical interest when identifying bait interactors from a large number of different baits. As expected, we found several known RelA interactors enriched in our RelA purifications (NFκB1, NFκB2, Rel, RelB, IκBα, IκBβ, and IκBε). We also found several proteins not previously described in association with RelA, including the small mitochondrial chaperone Tim13. Using a variety of biochemical approaches, we further investigated the nature of the association between Tim13 and NFκB family transcription factors. This work therefore provides a conceptual and experimental framework for analyzing transcription factor protein interactions.

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

    DEFF Research Database (Denmark)

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

    2004-01-01

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

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

    DEFF Research Database (Denmark)

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

    2011-01-01

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

  3. Virus host protein interaction network analysis reveals that the HEV ORF3 protein may interrupt the blood coagulation process.

    Directory of Open Access Journals (Sweden)

    Yansheng Geng

    Full Text Available Hepatitis E virus (HEV is endemic worldwide and a major cause of acute liver disease in developing countries. However, the molecular mechanisms of liver pathology and clinical disease are not well understood for HEV infection. Open reading frame 3 (ORF3 of HEV encodes a small phosphoprotein, which is assumed to be involved in liver pathology and clinical disease. In this study, the interactions between the HEV ORF3 protein and human proteins were investigated using a stringent, high-throughput yeast two-hybrid (Y2H analysis. Thirty two proteins were shown to interact with genotype 1 ORF3, 28 of which have not been reported previously. These novel interactions were evaluated by coimmunoprecipitation of protein complexes from transfected cells. We found also that the ORF3 proteins of genotype 4 and rabbit HEV interacted with all of the human proteins identified by the genotype 1 ORF3 protein. However, the putative ORF3 protein derived from avian HEV did not interact with the majority of these human proteins. The identified proteins were used to infer an overall interaction map linking the ORF3 protein with components of the host cellular networks. Analysis of this interaction map, based on functional annotation with the Gene Ontology features and KEGG pathways, revealed an enrichment of host proteins involved in complement coagulation, cellular iron ion homeostasis and oxidative stress. Additional canonical pathway analysis highlighted the enriched biological pathways relevant to blood coagulation and hemostasis. Consideration of the clinical manifestations of hepatitis E reported previously and the results of biological analysis from this study suggests that the ORF3 protein is likely to lead to an imbalance of coagulation and fibrinolysis by interacting with host proteins and triggering the corresponding pathological processes. These results suggest critical approaches to further study of the pathogenesis of the HEV ORF3 protein.

  4. Why do hubs in the yeast protein interaction network tend to be essential: reexamining the connection between the network topology and essentiality.

    Directory of Open Access Journals (Sweden)

    Elena Zotenko

    Full Text Available The centrality-lethality rule, which notes that high-degree nodes in a protein interaction network tend to correspond to proteins that are essential, suggests that the topological prominence of a protein in a protein interaction network may be a good predictor of its biological importance. Even though the correlation between degree and essentiality was confirmed by many independent studies, the reason for this correlation remains illusive. Several hypotheses about putative connections between essentiality of hubs and the topology of protein-protein interaction networks have been proposed, but as we demonstrate, these explanations are not supported by the properties of protein interaction networks. To identify the main topological determinant of essentiality and to provide a biological explanation for the connection between the network topology and essentiality, we performed a rigorous analysis of six variants of the genomewide protein interaction network for Saccharomyces cerevisiae obtained using different techniques. We demonstrated that the majority of hubs are essential due to their involvement in Essential Complex Biological Modules, a group of densely connected proteins with shared biological function that are enriched in essential proteins. Moreover, we rejected two previously proposed explanations for the centrality-lethality rule, one relating the essentiality of hubs to their role in the overall network connectivity and another relying on the recently published essential protein interactions model.

  5. Intracellular Trafficking Network of Protein Nanocapsules: Endocytosis, Exocytosis and Autophagy

    Science.gov (United States)

    Zhang, Jinxie; Zhang, Xudong; Liu, Gan; Chang, Danfeng; Liang, Xin; Zhu, Xianbing; Tao, Wei; Mei, Lin

    2016-01-01

    The inner membrane vesicle system is a complex transport system that includes endocytosis, exocytosis and autophagy. However, the details of the intracellular trafficking pathway of nanoparticles in cells have been poorly investigated. Here, we investigate in detail the intracellular trafficking pathway of protein nanocapsules using more than 30 Rab proteins as markers of multiple trafficking vesicles in endocytosis, exocytosis and autophagy. We observed that FITC-labeled protein nanoparticles were internalized by the cells mainly through Arf6-dependent endocytosis and Rab34-mediated micropinocytosis. In addition to this classic pathway: early endosome (EEs)/late endosome (LEs) to lysosome, we identified two novel transport pathways: micropinocytosis (Rab34 positive)-LEs (Rab7 positive)-lysosome pathway and EEs-liposome (Rab18 positive)-lysosome pathway. Moreover, the cells use slow endocytosis recycling pathway (Rab11 and Rab35 positive vesicles) and GLUT4 exocytosis vesicles (Rab8 and Rab10 positive) transport the protein nanocapsules out of the cells. In addition, protein nanoparticles are observed in autophagosomes, which receive protein nanocapsules through multiple endocytosis vesicles. Using autophagy inhibitor to block these transport pathways could prevent the degradation of nanoparticles through lysosomes. Using Rab proteins as vesicle markers to investigation the detail intracellular trafficking of the protein nanocapsules, will provide new targets to interfere the cellular behaver of the nanoparticles, and improve the therapeutic effect of nanomedicine. PMID:27698943

  6. Reuse of structural domain–domain interactions in protein networks

    Directory of Open Access Journals (Sweden)

    Bateman Alex

    2007-07-01

    Full Text Available Abstract Background Protein interactions are thought to be largely mediated by interactions between structural domains. Databases such as iPfam relate interactions in protein structures to known domain families. Here, we investigate how the domain interactions from the iPfam database are distributed in protein interactions taken from the HPRD, MPact, BioGRID, DIP and IntAct databases. Results We find that known structural domain interactions can only explain a subset of 4–19% of the available protein interactions, nevertheless this fraction is still significantly bigger than expected by chance. There is a correlation between the frequency of a domain interaction and the connectivity of the proteins it occurs in. Furthermore, a large proportion of protein interactions can be attributed to a small number of domain interactions. We conclude that many, but not all, domain interactions constitute reusable modules of molecular recognition. A substantial proportion of domain interactions are conserved between E. coli, S. cerevisiae and H. sapiens. These domains are related to essential cellular functions, suggesting that many domain interactions were already present in the last universal common ancestor. Conclusion Our results support the concept of domain interactions as reusable, conserved building blocks of protein interactions, but also highlight the limitations currently imposed by the small number of available protein structures.

  7. Gene expression profiles on predicting protein interaction network and exploring of new treatments for lung cancer.

    Science.gov (United States)

    Yang, Zehui; Zheng, Rui; Gao, Yuan; Zhang, Qiang

    2014-12-01

    In the present study, we aimed to explore disease-associated genes and their functions in lung cancer. We downloaded the gene expression profile GSE4115 from Gene Expression Omnibus (GEO) database. Total 97 lung cancer and 90 adjacent non-tumor lung tissue (normal) samples were applied to identify the differentially expressed genes (DEGs) by paired t test and variance analysis in spectral angle mapper (SAM) package in R. Gene Ontology (GO) functional enrichment analysis of DEGs were performed with Database for Annotation Visualization and Integrated Discovery, followed by construction of protein-protein interaction (PPI) network from Human Protein Reference Database (HPRD). Finally, network modules were analyzed by the MCODE algorithm to detect protein complexes in the PPI network. Total 3,102 genes were identified as DEGs at FDR normal and cancer tissues, and exploring new treatments for lung cancer. PMID:25205123

  8. Increasing the efficiency of SAGE adaptor ligation by directed ligation chemistry

    Science.gov (United States)

    So, Austin P.; Turner, Robin F. B.; Haynes, Charles A.

    2004-01-01

    The ability of Serial Analysis of Gene Expression (SAGE) to provide a quantitative picture of global gene expression relies not only on the depth and accuracy of sequencing into the SAGE library, but also on the efficiency of each step required to generate the SAGE library from the starting mRNA material. The first critical step is the ligation of adaptors containing a Type IIS recognition sequence to the anchored 3′ end cDNA population that permits the release of short sequence tags (SSTs) from defined sites within the 3′ end of each transcript. Using an in vitro transcript as a template, we observed that only a small fraction of anchored 3′ end cDNA are successfully ligated with added SAGE adaptors under typical reaction conditions currently used in the SAGE protocol. Although the introduction of ∼500-fold molar excess of adaptor or the inclusion of 15% (w/v) PEG-8000 increased the yield of the adaptor-modified product, complete conversion to the desired adaptor:cDNA hetero-ligation product is not achieved. An alternative method of ligation, termed as directed ligation, is described which exploits a favourable mass-action condition created by the presence of NlaIII during ligation in combination with a novel SAGE adaptor containing a methylated base within the ligation site. Using this strategy, we were able to achieve near complete conversion of the anchored 3′ end cDNA into the desired adaptor-modified product. This new protocol therefore greatly increases the probability that a SST will be generated from every transcript, greatly enhancing the fidelity of SAGE. Directed ligation also provides a powerful means to achieve near-complete ligation of any appropriately designed adaptor to its respective target. PMID:15247329

  9. 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.

  10. Prediction of Protein Thermostability by an Efficient Neural Network Approach

    Directory of Open Access Journals (Sweden)

    Jalal Rezaeenour

    2016-10-01

    Full Text Available Introduction: Manipulation of protein stability is important for understanding the principles that govern protein thermostability, both in basic research and industrial applications. Various data mining techniques exist for prediction of thermostable proteins. Furthermore, ANN methods have attracted significant attention for prediction of thermostability, because they constitute an appropriate approach to mapping the non-linear input-output relationships and massive parallel computing. Method: An Extreme Learning Machine (ELM was applied to estimate thermal behavior of 1289 proteins. In the proposed algorithm, the parameters of ELM were optimized using a Genetic Algorithm (GA, which tuned a set of input variables, hidden layer biases, and input weights, to and enhance the prediction performance. The method was executed on a set of amino acids, yielding a total of 613 protein features. A number of feature selection algorithms were used to build subsets of the features. A total of 1289 protein samples and 613 protein features were calculated from UniProt database to understand features contributing to the enzymes’ thermostability and find out the main features that influence this valuable characteristic. Results:At the primary structure level, Gln, Glu and polar were the features that mostly contributed to protein thermostability. At the secondary structure level, Helix_S, Coil, and charged_Coil were the most important features affecting protein thermostability. These results suggest that the thermostability of proteins is mainly associated with primary structural features of the protein. According to the results, the influence of primary structure on the thermostabilty of a protein was more important than that of the secondary structure. It is shown that prediction accuracy of ELM (mean square error can improve dramatically using GA with error rates RMSE=0.004 and MAPE=0.1003. Conclusion: The proposed approach for forecasting problem

  11. Biophysical basis of the binding of WWOX tumor suppressor to WBP1 and WBP2 adaptors.

    Science.gov (United States)

    McDonald, Caleb B; Buffa, Laura; Bar-Mag, Tomer; Salah, Zaidoun; Bhat, Vikas; Mikles, David C; Deegan, Brian J; Seldeen, Kenneth L; Malhotra, Arun; Sudol, Marius; Aqeilan, Rami I; Nawaz, Zafar; Farooq, Amjad

    2012-09-01

    The WW-containing oxidoreductase (WWOX) tumor suppressor participates in a diverse array of cellular activities by virtue of its ability to recognize WW-binding protein 1 (WBP1) and WW-binding protein 2 (WBP2) signaling adaptors among a wide variety of other ligands. Herein, using a multitude of biophysical techniques, we provide evidence that while the WW1 domain of WWOX binds to PPXY motifs within WBP1 and WBP2 in a physiologically relevant manner, the WW2 domain exhibits no affinity toward any of these PPXY motifs. Importantly, our data suggest that while R25/W44 residues located within the binding pocket of a triple-stranded β-fold of WW1 domain are critical for the recognition of PPXY ligands, they are replaced by the chemically distinct E66/Y85 duo at structurally equivalent positions within the WW2 domain, thereby accounting for its failure to bind PPXY ligands. Predictably, not only does the introduction of E66R/Y85W double substitution within the WW2 domain result in gain of function but the resulting engineered domain, hereinafter referred to as WW2_RW, also appears to be a much stronger binding partner of WBP1 and WBP2 than the wild-type WW1 domain. We also show that while the WW1 domain is structurally disordered and folds upon ligand binding, the WW2 domain not only adopts a fully structured conformation but also aids stabilization and ligand binding to WW1 domain. This salient observation implies that the WW2 domain likely serves as a chaperone to augment the physiological function of WW1 domain within WWOX. Collectively, our study lays the groundwork for understanding the molecular basis of a key protein-protein interaction pertinent to human health and disease. PMID:22634283

  12. Prediction of beta-turns in proteins using neural networks.

    Science.gov (United States)

    McGregor, M J; Flores, T P; Sternberg, M J

    1989-05-01

    The use of neural networks to improve empirical secondary structure prediction is explored with regard to the identification of the position and conformational class of beta-turns, a four-residue chain reversal. Recently an algorithm was developed for beta-turn predictions based on the empirical approach of Chou and Fasman using different parameters for three classes (I, II and non-specific) of beta-turns. In this paper, using the same data, an alternative approach to derive an empirical prediction method is used based on neural networks which is a general learning algorithm extensively used in artificial intelligence. Thus the results of the two approaches can be compared. The most severe test of prediction accuracy is the percentage of turn predictions that are correct and the neural network gives an overall improvement from 20.6% to 26.0%. The proportion of correctly predicted residues is 71%, compared to a chance level of about 58%. Thus neural networks provide a method of obtaining more accurate predictions from empirical data than a simpler method of deriving propensities. PMID:2748568

  13. The architectural network for protein secondary structure prediction

    Directory of Open Access Journals (Sweden)

    Anindya Sundar Panja

    2016-07-01

    Full Text Available Over the past 25 years, the accuracy of proteins secondary structure prediction has improved substantially. Recently evolutionary information taken from the deviation of proteins in some structural family have again enhance prediction accuracy for all these residues predicted correctly is in one of the three sates helix, strands and others . The new methods developed over the past few years may be interesting in context of improvements which is achieved through combination of the existing methods. Evolutionary divergences profile posses’ adequate information to improve protein secondary structure prediction accuracy. These profiles can also able to correctly predict long stretches of identical residues in other secondary structure. This sequence structure relationship may help to help to developed tool which can efficiently predict the protein secondary structure from its amino acid sequence

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

    Science.gov (United States)

    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 non-incorporated protein in concert with numerous insect and plant proteins to regulate virus movem...

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

    OpenAIRE

    WANG Kun; Peng, Xiaojue; Ji, Yanxiao; Yang, Pingfang; Zhu, Yingguo; LI, SHAOQING

    2013-01-01

    Rice is one of the most important model crop plants whose heterosis has been well-exploited in commercial hybrid seed production via a variety of types of male-sterile lines. Hybrid rice cultivation area is steadily expanding around the world, especially in Southern Asia. Characterization of genes and proteins related to male sterility aims to understand how and why the male sterility occurs, and which proteins are the key players for microspores abortion. Recently, a series of genes and prot...

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

    Science.gov (United States)

    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.

  17. Discovery of intramolecular signal transduction network based on a new protein dynamics model of energy dissipation.

    Directory of Open Access Journals (Sweden)

    Cheng-Wei Ma

    Full Text Available A novel approach to reveal intramolecular signal transduction network is proposed in this work. To this end, a new algorithm of network construction is developed, which is based on a new protein dynamics model of energy dissipation. A key feature of this approach is that direction information is specified after inferring protein residue-residue interaction network involved in the process of signal transduction. This enables fundamental analysis of the regulation hierarchy and identification of regulation hubs of the signaling network. A well-studied allosteric enzyme, E. coli aspartokinase III, is used as a model system to demonstrate the new method. Comparison with experimental results shows that the new approach is able to predict all the sites that have been experimentally proved to desensitize allosteric regulation of the enzyme. In addition, the signal transduction network shows a clear preference for specific structural regions, secondary structural types and residue conservation. Occurrence of super-hubs in the network indicates that allosteric regulation tends to gather residues with high connection ability to collectively facilitate the signaling process. Furthermore, a new parameter of propagation coefficient is defined to determine the propagation capability of residues within a signal transduction network. In conclusion, the new approach is useful for fundamental understanding of the process of intramolecular signal transduction and thus has significant impact on rational design of novel allosteric proteins.

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

    Science.gov (United States)

    Spencer, Matt; Eickholt, Jesse; Cheng, Jianlin

    2014-01-01

    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% 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 data set of 198 proteins, achieving a Q3 accuracy of 80.7% and a Sov accuracy of 74.2%. PMID:25750595

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

    Directory of Open Access Journals (Sweden)

    Mingzhu Zhao

    2013-01-01

    Full Text Available The traditional Chinese medicine (TCM, which has thousands of years of clinical application among China and other Asian countries, is the pioneer of the “multicomponent-multitarget” and network pharmacology. Although there is no doubt of the efficacy, it is difficult to elucidate convincing underlying mechanism of TCM due to its complex composition and unclear pharmacology. The use of ligand-protein networks has been gaining significant value in the history of drug discovery while its application in TCM is still in its early stage. This paper firstly surveys TCM databases for virtual screening that have been greatly expanded in size and data diversity in recent years. On that basis, different screening methods and strategies for identifying active ingredients and targets of TCM are outlined based on the amount of network information available, both on sides of ligand bioactivity and the protein structures. Furthermore, applications of successful in silico target identification attempts are discussed in detail along with experiments in exploring the ligand-protein networks of TCM. Finally, it will be concluded that the prospective application of ligand-protein networks can be used not only to predict protein targets of a small molecule, but also to explore the mode of action of TCM.

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

    Directory of Open Access Journals (Sweden)

    Julie Baussand

    2009-09-01

    Full Text Available Communication between distant sites often defines the biological role of a protein: amino acid long-range interactions are as important in binding specificity, allosteric regulation and conformational change as residues directly contacting the substrate. The maintaining of functional and structural coupling of long-range interacting residues requires coevolution of these residues. Networks of interaction between coevolved residues can be reconstructed, and from the networks, one can possibly derive insights into functional mechanisms for the protein family. We propose a combinatorial method for mapping conserved networks of amino acid interactions in a protein which is based on the analysis of a set of aligned sequences, the associated distance tree and the combinatorics of its subtrees. The degree of coevolution of all pairs of coevolved residues is identified numerically, and networks are reconstructed with a dedicated clustering algorithm. The method drops the constraints on high sequence divergence limiting the range of applicability of the statistical approaches previously proposed. We apply the method to four protein families where we show an accurate detection of functional networks and the possibility to treat sets of protein sequences of variable divergence.

  1. Toward a rigorous network of protein-protein interactions of the model sulfate reducer Desulfovibrio vulgaris Hildenborough

    Energy Technology Data Exchange (ETDEWEB)

    Chhabra, S.R.; Joachimiak, M.P.; Petzold, C.J.; Zane, G.M.; Price, M.N.; Gaucher, S.; Reveco, S.A.; Fok, V.; Johanson, A.R.; Batth, T.S.; Singer, M.; Chandonia, J.M.; Joyner, D.; Hazen, T.C.; Arkin, A.P.; Wall, J.D.; Singh, A.K.; Keasling, J.D.

    2011-05-01

    Protein–protein interactions offer an insight into cellular processes beyond what may be obtained by the quantitative functional genomics tools of proteomics and transcriptomics. The aforementioned tools have been extensively applied to study E. coli and other aerobes and more recently to study the stress response behavior of Desulfovibrio 5 vulgaris Hildenborough, a model anaerobe and sulfate reducer. In this paper we present the first attempt to identify protein-protein interactions in an obligate anaerobic bacterium. We used suicide vector-assisted chromosomal modification of 12 open reading frames encoded by this sulfate reducer to append an eight amino acid affinity tag to the carboxy-terminus of the chosen proteins. Three biological replicates of the 10 ‘pulled-down’ proteins were separated and analyzed using liquid chromatography-mass spectrometry. Replicate agreement ranged between 35% and 69%. An interaction network among 12 bait and 90 prey proteins was reconstructed based on 134 bait-prey interactions computationally identified to be of high confidence. We discuss the biological significance of several unique metabolic features of D. vulgaris revealed by this protein-protein interaction data 15 and protein modifications that were observed. These include the distinct role of the putative carbon monoxide-induced hydrogenase, unique electron transfer routes associated with different oxidoreductases, and the possible role of methylation in regulating sulfate reduction.

  2. 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 t...... provide insight into the mutual interdependencies between the location of ordered water sites and the structural and chemical characteristics of the protein residues.......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...... 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...

  3. 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.

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

    Science.gov (United States)

    Han, Yuewen; Niu, Jun; Wang, Dong; Li, Yuanyuan

    2016-01-01

    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. PMID:27115606

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Science.gov (United States)

    Tedoldi, Sara; Paterson, Jennifer C; Hansmann, Martin-Leo; Natkunam, Yasodha; Rüdiger, Thomas; Angelisova, Pavla; Du, Ming Q; Roberton, Helen; Roncador, Giovanna; Sanchez, Lydia; Pozzobon, Michela; Masir, Noraidah; Barry, Richard; Pileri, Stefano; Mason, David Y; Marafioti, Teresa; Horejsí, Václav

    2006-01-01

    Transmembrane adaptor proteins (of which 7 have been identified so far) are involved in receptor signaling in immune cells. They have only a short extracellular region, with most of the molecule comprising a substantial intracytoplasmic region carrying multiple tyrosine residues that can be phosphorylated by Src- or Syk-family kinases. In this paper, we report an immunohistologic study of 6 of these molecules in normal and neoplastic human tissue sections and show that they are restricted to subpopulations of lymphoid cells, being present in either T cells (LAT, LIME, and TRIM), B cells (NTAL), or subsets of both cell types (PAG and SIT). Their expression in neoplastic lymphoid cells broadly reflects that of normal lymphoid tissue, including the positivity of plasma cells and myeloma/plasmacytoma for LIME, NTAL, PAG, and SIT. However, this study also revealed some reactions that may be of diagnostic/prognostic value. For example, lymphocytic lymphoma and mantle-cell lymphoma showed similar profiles but differed clearly from follicle-center lymphoma, whereas PAG tended to be selectively expressed in germinal center-derived subsets of diffuse large B-cell lymphoma. These molecules represent a potentially important addition to the panel of immunophenotypic markers detectable in routine biopsies that can be used in hematopathologic studies. PMID:16160011

  7. Predicting the binding patterns of hub proteins: a study using yeast protein interaction networks.

    Directory of Open Access Journals (Sweden)

    Carson M Andorf

    Full Text Available BACKGROUND: Protein-protein interactions are critical to elucidating the role played by individual proteins in important biological pathways. Of particular interest are hub proteins that can interact with large numbers of partners and often play essential roles in cellular control. Depending on the number of binding sites, protein hubs can be classified at a structural level as singlish-interface hubs (SIH with one or two binding sites, or multiple-interface hubs (MIH with three or more binding sites. In terms of kinetics, hub proteins can be classified as date hubs (i.e., interact with different partners at different times or locations or party hubs (i.e., simultaneously interact with multiple partners. METHODOLOGY: Our approach works in 3 phases: Phase I classifies if a protein is likely to bind with another protein. Phase II determines if a protein-binding (PB protein is a hub. Phase III classifies PB proteins as singlish-interface versus multiple-interface hubs and date versus party hubs. At each stage, we use sequence-based predictors trained using several standard machine learning techniques. CONCLUSIONS: Our method is able to predict whether a protein is a protein-binding protein with an accuracy of 94% and a correlation coefficient of 0.87; identify hubs from non-hubs with 100% accuracy for 30% of the data; distinguish date hubs/party hubs with 69% accuracy and area under ROC curve of 0.68; and SIH/MIH with 89% accuracy and area under ROC curve of 0.84. Because our method is based on sequence information alone, it can be used even in settings where reliable protein-protein interaction data or structures of protein-protein complexes are unavailable to obtain useful insights into the functional and evolutionary characteristics of proteins and their interactions. AVAILABILITY: We provide a web server for our three-phase approach: http://hybsvm.gdcb.iastate.edu.

  8. Yeast Interacting Proteins Database: YCL032W, YLR423C [Yeast Interacting Proteins Database

    Lifescience Database Archive (English)

    Full Text Available YCL032W STE50 Protein involved in mating response, invasive/filamentous growth, and...lved in mating response, invasive/filamentous growth, and osmotolerance, acts as an adaptor that links G pro

  9. Insights into biological information processing: structural and dynamical analysis of a human protein signalling network

    Energy Technology Data Exchange (ETDEWEB)

    Fuente, Alberto de la; Fotia, Giorgio; Maggio, Fabio; Mancosu, Gianmaria; Pieroni, Enrico [CRS4 Bioinformatica, Parco Tecnologico POLARIS, Ed.1, Loc Piscinamanna, Pula (Italy)], E-mail: alf@crs4.it

    2008-06-06

    We present an investigation on the structural and dynamical properties of a 'human protein signalling network' (HPSN). This biological network is composed of nodes that correspond to proteins and directed edges that represent signal flows. In order to gain insight into the organization of cell information processing this network is analysed taking into account explicitly the edge directions. We explore the topological properties of the HPSN at the global and the local scale, further applying the generating function formalism to provide a suitable comparative model. The relationship between the node degrees and the distribution of signals through the network is characterized using degree correlation profiles. Finally, we analyse the dynamical properties of small sub-graphs showing high correlation between their occurrence and dynamic stability.

  10. BioNetwork Bench: Database and Software for Storage, Query, and Analysis of Gene and Protein Networks

    OpenAIRE

    Oksana Kohutyuk; Fadi Towfic; M. Heather West Greenlee; Vasant Honavar

    2012-01-01

    Gene and protein networks offer a powerful approach for integration of the disparate yet complimentary types of data that result from high-throughput analyses. Although many tools and databases are currently available for accessing such data, they are left unutilized by bench scientists as they generally lack features for effective analysis and integration of both public and private datasets and do not offer an intuitive interface for use by scientists with limited computational expertise. We...

  11. Protein variants form a system of networks: microdiversity of IMP metallo-beta-lactamases.

    Directory of Open Access Journals (Sweden)

    Michael Widmann

    Full Text Available Genome and metagenome sequencing projects support the view that only a tiny portion of the total protein microdiversity in the biosphere has been sequenced yet, while the vast majority of existing protein variants is still unknown. By using a network approach, the microdiversity of 42 metallo-β-lactamases of the IMP family was investigated. In the networks, the nodes are formed by the variants, while the edges correspond to single mutations between pairs of variants. The 42 variants were assigned to 7 separate networks. By analyzing the networks and their relationships, the structure of sequence space was studied and existing, but still unknown, functional variants were predicted. The largest network consists of 10 variants with IMP-1 in its center and includes two ubiquitous mutations, V67F and S262G. By relating the corresponding pairs of variants, the networks were integrated into a single system of networks. The largest network also included a quartet of variants: IMP-1, two single mutants, and the respective double mutant. The existence of quartets indicates that if two mutations resulted in functional enzymes, the double mutant may also be active and stable. Therefore, quartet construction from triplets was applied to predict 15 functional variants. Further functional mutants were predicted by applying the two ubiquitous mutations in all networks. In addition, since the networks are separated from each other by 10-15 mutations on average, it is expected that a subset of the theoretical intermediates are functional, and therefore are supposed to exist in the biosphere. Finally, the network analysis helps to distinguish between epistatic and additive effects of mutations; while the presence of correlated mutations indicates a strong interdependency between the respective positions, the mutations V67F and S262G are ubiquitous and therefore background independent.

  12. ProtNet: a tool for stochastic simulations of protein interaction networks dynamics

    Science.gov (United States)

    Bernaschi, Massimo; Castiglione, Filippo; Ferranti, Alessandra; Gavrila, Caius; Tinti, Michele; Cesareni, Gianni

    2007-01-01

    Background Protein interactions support cell organization and mediate its response to any specific stimulus. Recent technological advances have produced large data-sets that aim at describing the cell interactome. These data are usually presented as graphs where proteins (nodes) are linked by edges to their experimentally determined partners. This representation reveals that protein-protein interaction (PPI) networks, like other kinds of complex networks, are not randomly organized and display properties that are typical of "hierarchical" networks, combining modularity and local clustering to scale free topology. However informative, this representation is static and provides no clue about the dynamic nature of protein interactions inside the cell. Results To fill this methodological gap, we designed and implemented a computer model that captures the discrete and stochastic nature of protein interactions. In ProtNet, our simplified model, the intracellular space is mapped onto either a two-dimensional or a three-dimensional lattice with each lattice site having a linear size (5 nm) comparable to the diameter of an average globular protein. The protein filled lattice has an occupancy (e.g. 20%) compatible with the estimated crowding of proteins in the cell cytoplasm. Proteins or protein complexes are free to translate and rotate on the lattice that represents a sort of naïve unstructured cell (devoid of compartments). At each time step, molecular entities (proteins or complexes) that happen to be in neighboring cells may interact and form larger complexes or dissociate depending on the interaction rules defined in an experimental protein interaction network. This whole procedure can be seen as a sort of "discrete molecular dynamics" applied to interacting proteins in a cell. We have tested our model by performing different simulations using as interaction rules those derived from an experimental interactome of Saccharomyces cerevisiae (1378 nodes, 2491 edges) and

  13. Relationships between predicted moonlighting proteins, human diseases and comorbidities from a network perspective.

    Directory of Open Access Journals (Sweden)

    Andreas eZanzoni

    2015-06-01

    Full Text Available Moonlighting proteins are a subset of multifunctional proteins characterized by their multiple, independent and unrelated biological functions. We recently set up a large-scale identification of moonlighting proteins using a protein-protein interaction network approach. We established that 3% of the current human interactome is composed of predicted moonlighting proteins. We found that disease-related genes are over-represented among those candidates. Here, by comparing moonlighting candidates to non-candidates as groups, we further show that (i they are significantly involved in more than one disease, (ii they contribute to complex rather than monogenic diseases, (iii the diseases in which they are involved are phenotypically different according to their annotations, finally, (iv they are enriched for diseases pairs showing statistically significant comorbidity patterns based on Medicare records. Altogether, our results suggest that some observed comorbidities between phenotypically different diseases could be due to a shared protein involved in unrelated biological processes.

  14. 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

  15. 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 sequ...

  16. 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 sequ...

  17. Eukaryotic LYR Proteins Interact with Mitochondrial Protein Complexes

    Directory of Open Access Journals (Sweden)

    Heike Angerer

    2015-02-01

    Full Text Available In eukaryotic cells, mitochondria host ancient essential bioenergetic and biosynthetic pathways. LYR (leucine/tyrosine/arginine motif proteins (LYRMs of the Complex1_LYR-like superfamily interact with protein complexes of bacterial origin. Many LYR proteins function as extra subunits (LYRM3 and LYRM6 or novel assembly factors (LYRM7, LYRM8, ACN9 and FMC1 of the oxidative phosphorylation (OXPHOS core complexes. Structural insights into complex I accessory subunits LYRM6 and LYRM3 have been provided by analyses of EM and X-ray structures of complex I from bovine and the yeast Yarrowia lipolytica, respectively. Combined structural and biochemical studies revealed that LYRM6 resides at the matrix arm close to the ubiquinone reduction site. For LYRM3, a position at the distal proton-pumping membrane arm facing the matrix space is suggested. Both LYRMs are supposed to anchor an acyl-carrier protein (ACPM independently to complex I. The function of this duplicated protein interaction of ACPM with respiratory complex I is still unknown. Analysis of protein-protein interaction screens, genetic analyses and predicted multi-domain LYRMs offer further clues on an interaction network and adaptor-like function of LYR proteins in mitochondria.

  18. Functional protein networks unifying limb girdle muscular dystrophy

    NARCIS (Netherlands)

    Morrée, Antoine de

    2011-01-01

    Limb Girdle Muscular Dystrophy (LGMD) is a rare progressive heterogeneous disorder that can be caused by mutations in at least 21 different genes. These genes are often widely expressed and encode proteins with highly differing functions. And yet mutations in all of them give rise to a similar clini

  19. Mass-action equilibrium and non-specific interactions in protein binding networks

    Science.gov (United States)

    Maslov, Sergei

    2009-03-01

    Large-scale protein binding networks serve as a paradigm of complex properties of living cells. These networks are naturally weighted with edges characterized by binding strength and protein-nodes -- by their concentrations. However, the state-of-the-art high-throughput experimental techniques generate just a binary (yes or no) information about individual interactions. As a result, most of the previous research concentrated just on topology of these networks. In a series of recent publications [1-4] my collaborators and I went beyond purely topological studies and calculated the mass-action equilibrium of a genome-wide binding network using experimentally determined protein concentrations, localizations, and reliable binding interactions in baker's yeast. We then studied how this equilibrium responds to large perturbations [1-2] and noise [3] in concentrations of proteins. We demonstrated that the change in the equilibrium concentration of a protein exponentially decays (and sign-alternates) with its network distance away from the perturbed node. This explains why, despite a globally connected topology, individual functional modules in such networks are able to operate fairly independently. In a separate study [4] we quantified the interplay between specific and non-specific binding interactions under crowded conditions inside living cells. We show how the need to limit the waste of resources constrains the number of types and concentrations of proteins that are present at the same time and at the same place in yeast cells. [1] S Maslov, I. Ispolatov, PNAS 104:13655 (2007). [2] S. Maslov, K. Sneppen, I. Ispolatov, New J. of Phys. 9: 273 (2007). [3] K-K. Yan, D. Walker, S. Maslov, PRL accepted (2008). [4] J. Zhang, S. Maslov, and E. I. Shakhnovich, Mol Syst Biol 4, 210 (2008).

  20. Dynamic Proteomic Characteristics and Network Integration Revealing Key Proteins for Two Kernel Tissue Developments in Popcorn.

    Science.gov (United States)

    Dong, Yongbin; Wang, Qilei; Zhang, Long; Du, Chunguang; Xiong, Wenwei; Chen, Xinjian; Deng, Fei; Ma, Zhiyan; Qiao, Dahe; Hu, Chunhui; Ren, Yangliu; Li, Yuling

    2015-01-01

    The formation and development of maize kernel is a complex dynamic physiological and biochemical process that involves the temporal and spatial expression of many proteins and the regulation of metabolic pathways. In this study, the protein profiles of the endosperm and pericarp at three important developmental stages were analyzed by isobaric tags for relative and absolute quantification (iTRAQ) labeling coupled with LC-MS/MS in popcorn inbred N04. Comparative quantitative proteomic analyses among developmental stages and between tissues were performed, and the protein networks were integrated. A total of 6,876 proteins were identified, of which 1,396 were nonredundant. Specific proteins and different expression patterns were observed across developmental stages and tissues. The functional annotation of the identified proteins revealed the importance of metabolic and cellular processes, and binding and catalytic activities for the development of the tissues. The whole, endosperm-specific and pericarp-specific protein networks integrated 125, 9 and 77 proteins, respectively, which were involved in 54 KEGG pathways and reflected their complex metabolic interactions. Confirmation for the iTRAQ endosperm proteins by two-dimensional gel electrophoresis showed that 44.44% proteins were commonly found. However, the concordance between mRNA level and the protein abundance varied across different proteins, stages, tissues and inbred lines, according to the gene cloning and expression analyses of four relevant proteins with important functions and different expression levels. But the result by western blot showed their same expression tendency for the four proteins as by iTRAQ. These results could provide new insights into the developmental mechanisms of endosperm and pericarp, and grain formation in maize. PMID:26587848

  1. Dynamic Proteomic Characteristics and Network Integration Revealing Key Proteins for Two Kernel Tissue Developments in Popcorn.

    Directory of Open Access Journals (Sweden)

    Yongbin Dong

    Full Text Available The formation and development of maize kernel is a complex dynamic physiological and biochemical process that involves the temporal and spatial expression of many proteins and the regulation of metabolic pathways. In this study, the protein profiles of the endosperm and pericarp at three important developmental stages were analyzed by isobaric tags for relative and absolute quantification (iTRAQ labeling coupled with LC-MS/MS in popcorn inbred N04. Comparative quantitative proteomic analyses among developmental stages and between tissues were performed, and the protein networks were integrated. A total of 6,876 proteins were identified, of which 1,396 were nonredundant. Specific proteins and different expression patterns were observed across developmental stages and tissues. The functional annotation of the identified proteins revealed the importance of metabolic and cellular processes, and binding and catalytic activities for the development of the tissues. The whole, endosperm-specific and pericarp-specific protein networks integrated 125, 9 and 77 proteins, respectively, which were involved in 54 KEGG pathways and reflected their complex metabolic interactions. Confirmation for the iTRAQ endosperm proteins by two-dimensional gel electrophoresis showed that 44.44% proteins were commonly found. However, the concordance between mRNA level and the protein abundance varied across different proteins, stages, tissues and inbred lines, according to the gene cloning and expression analyses of four relevant proteins with important functions and different expression levels. But the result by western blot showed their same expression tendency for the four proteins as by iTRAQ. These results could provide new insights into the developmental mechanisms of endosperm and pericarp, and grain formation in maize.

  2. Building and analyzing protein interactome networks by cross-species comparisons

    Directory of Open Access Journals (Sweden)

    Blackman Barron

    2010-03-01

    Full Text Available Abstract Background A genomic catalogue of protein-protein interactions is a rich source of information, particularly for exploring the relationships between proteins. Numerous systems-wide and small-scale experiments have been conducted to identify interactions; however, our knowledge of all interactions for any one species is incomplete, and alternative means to expand these network maps is needed. We therefore took a comparative biology approach to predict protein-protein interactions across five species (human, mouse, fly, worm, and yeast and developed InterologFinder for research biologists to easily navigate this data. We also developed a confidence score for interactions based on available experimental evidence and conservation across species. Results The connectivity of the resultant networks was determined to have scale-free distribution, small-world properties, and increased local modularity, indicating that the added interactions do not disrupt our current understanding of protein network structures. We show examples of how these improved interactomes can be used to analyze a genome-scale dataset (RNAi screen and to assign new function to proteins. Predicted interactions within this dataset were tested by co-immunoprecipitation, resulting in a high rate of validation, suggesting the high quality of networks produced. Conclusions Protein-protein interactions were predicted in five species, based on orthology. An InteroScore, a score accounting for homology, number of orthologues with evidence of interactions, and number of unique observations of interactions, is given to each known and predicted interaction. Our website http://www.interologfinder.org provides research biologists intuitive access to this data.

  3. Membrane tubule formation by banana-shaped proteins with or without transient network structure

    Science.gov (United States)

    Noguchi, Hiroshi

    2016-02-01

    In living cells, membrane morphology is regulated by various proteins. Many membrane reshaping proteins contain a Bin/Amphiphysin/Rvs (BAR) domain, which consists of a banana-shaped rod. The BAR domain bends the biomembrane along the rod axis and the features of this anisotropic bending have recently been studied. Here, we report on the role of the BAR protein rods in inducing membrane tubulation, using large-scale coarse-grained simulations. We reveal that a small spontaneous side curvature perpendicular to the rod can drastically alter the tubulation dynamics at high protein density, whereas no significant difference is obtained at low density. A percolated network is intermediately formed depending on the side curvature. This network suppresses tubule protrusion, leading to the slow formation of fewer tubules. Thus, the side curvature, which is generated by protein-protein and membrane-protein interactions, plays a significant role in tubulation dynamics. We also find that positive surface tensions and the vesicle membrane curvature can stabilize this network structure by suppressing the tubulation.

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

    Directory of Open Access Journals (Sweden)

    Sumeet Agarwal

    2010-06-01

    Full Text Available The idea of "date" and "party" hubs has been influential in the study of protein-protein interaction networks. Date hubs display low co-expression with their partners, whilst party hubs have high co-expression. It was proposed that party hubs are local coordinators whereas date hubs are global connectors. Here, we show that the reported importance of date hubs to network connectivity can in fact be attributed to a tiny subset of them. Crucially, these few, extremely central, hubs do not display particularly low expression correlation, undermining the idea of a link between this quantity and hub function. The date/party distinction was originally motivated by an approximately bimodal distribution of hub co-expression; we show that this feature is not always robust to methodological changes. Additionally, topological properties of hubs do not in general correlate with co-expression. However, we find significant correlations between interaction centrality and the functional similarity of the interacting proteins. We suggest that thinking in terms of a date/party dichotomy for hubs in protein interaction networks is not meaningful, and it might be more useful to conceive of roles for protein-protein interactions rather than for individual proteins.

  5. Multiplex matrix network analysis of protein complexes in the human TCR signalosome.

    Science.gov (United States)

    Smith, Stephen E P; Neier, Steven C; Reed, Brendan K; Davis, Tessa R; Sinnwell, Jason P; Eckel-Passow, Jeanette E; Sciallis, Gabriel F; Wieland, Carilyn N; Torgerson, Rochelle R; Gil, Diana; Neuhauser, Claudia; Schrum, Adam G

    2016-08-02

    Multiprotein complexes transduce cellular signals through extensive interaction networks, but the ability to analyze these networks in cells from small clinical biopsies is limited. To address this, we applied an adaptable multiplex matrix system to physiologically relevant signaling protein complexes isolated from a cell line or from human patient samples. Focusing on the proximal T cell receptor (TCR) signalosome, we assessed 210 pairs of PiSCES (proteins in shared complexes detected by exposed surface epitopes). Upon stimulation of Jurkat cells with superantigen-loaded antigen-presenting cells, this system produced high-dimensional data that enabled visualization of network activity. A comprehensive analysis platform generated PiSCES biosignatures by applying unsupervised hierarchical clustering, principal component analysis, an adaptive nonparametric with empirical cutoff analysis, and weighted correlation network analysis. We generated PiSCES biosignatures from 4-mm skin punch biopsies from control patients or patients with the autoimmune skin disease alopecia areata. This analysis distinguished disease patients from the controls, detected enhanced basal TCR signaling in the autoimmune patients, and identified a potential signaling network signature that may be indicative of disease. Thus, generation of PiSCES biosignatures represents an approach that can provide information about the activity of protein signaling networks in samples including low-abundance primary cells from clinical biopsies.

  6. Multiplex matrix network analysis of protein complexes in the human TCR signalosome.

    Science.gov (United States)

    Smith, Stephen E P; Neier, Steven C; Reed, Brendan K; Davis, Tessa R; Sinnwell, Jason P; Eckel-Passow, Jeanette E; Sciallis, Gabriel F; Wieland, Carilyn N; Torgerson, Rochelle R; Gil, Diana; Neuhauser, Claudia; Schrum, Adam G

    2016-01-01

    Multiprotein complexes transduce cellular signals through extensive interaction networks, but the ability to analyze these networks in cells from small clinical biopsies is limited. To address this, we applied an adaptable multiplex matrix system to physiologically relevant signaling protein complexes isolated from a cell line or from human patient samples. Focusing on the proximal T cell receptor (TCR) signalosome, we assessed 210 pairs of PiSCES (proteins in shared complexes detected by exposed surface epitopes). Upon stimulation of Jurkat cells with superantigen-loaded antigen-presenting cells, this system produced high-dimensional data that enabled visualization of network activity. A comprehensive analysis platform generated PiSCES biosignatures by applying unsupervised hierarchical clustering, principal component analysis, an adaptive nonparametric with empirical cutoff analysis, and weighted correlation network analysis. We generated PiSCES biosignatures from 4-mm skin punch biopsies from control patients or patients with the autoimmune skin disease alopecia areata. This analysis distinguished disease patients from the controls, detected enhanced basal TCR signaling in the autoimmune patients, and identified a potential signaling network signature that may be indicative of disease. Thus, generation of PiSCES biosignatures represents an approach that can provide information about the activity of protein signaling networks in samples including low-abundance primary cells from clinical biopsies. PMID:27485017

  7. A Study on Protein Residue Contacts Prediction by Recurrent Neural Network

    Institute of Scientific and Technical Information of China (English)

    Liu Gui-xia; Zhu Yuan-xian; Zhou Wen-gang; Huang Yan-xin; Zhou Chun-guang; Wang Rong-xing

    2005-01-01

    A new method was described for using a recurrent neural network with bias units to predict contact maps in proteins.The main inputs to the neural network include residues pairwise, residue classification according to hydrophobicity, polar,acidic, basic and secondary structure information and residue separation between two residues. In our work, a dataset was used which was composed of 53 globulin proteins of known 3D structure. An average predictive accuracy of 0. 29 was obtained. Our results demonstrate the viability of the approach for predicting contact maps.

  8. Dissecting spatio-temporal protein networks driving human heart development and related disorders

    DEFF Research Database (Denmark)

    Hansen, Kasper Lage; Mølgård, Kjeld; Greenway, Steven;

    2010-01-01

    of a developing organ identifying several novel signaling modules. Our results show that organ development relies on surprisingly few, extensively recycled, protein modules that integrate into complex higher-order networks. This design allows the formation of a complicated organ using simple building blocks...... development, we combined detailed phenotype information from deleterious mutations in 255 genes with high-confidence experimental interactome data, and coupled the results to thorough experimental validation. Hereby, we made the first systematic analysis of spatio-temporal protein networks driving many stages...

  9. ModuleRole: a tool for modulization, role determination and visualization in protein-protein interaction networks.

    Directory of Open Access Journals (Sweden)

    Guipeng Li

    Full Text Available Rapidly increasing amounts of (physical and genetic protein-protein interaction (PPI data are produced by various high-throughput techniques, and interpretation of these data remains a major challenge. In order to gain insight into the organization and structure of the resultant large complex networks formed by interacting molecules, using simulated annealing, a method based on the node connectivity, we developed ModuleRole, a user-friendly web server tool which finds modules in PPI network and defines the roles for every node, and produces files for visualization in Cytoscape and Pajek. For given proteins, it analyzes the PPI network from BioGRID database, finds and visualizes the modules these proteins form, and then defines the role every node plays in this network, based on two topological parameters Participation Coefficient and Z-score. This is the first program which provides interactive and very friendly interface for biologists to find and visualize modules and roles of proteins in PPI network. It can be tested online at the website http://www.bioinfo.org/modulerole/index.php, which is free and open to all users and there is no login requirement, with demo data provided by "User Guide" in the menu Help. Non-server application of this program is considered for high-throughput data with more than 200 nodes or user's own interaction datasets. Users are able to bookmark the web link to the result page and access at a later time. As an interactive and highly customizable application, ModuleRole requires no expert knowledge in graph theory on the user side and can be used in both Linux and Windows system, thus a very useful tool for biologist to analyze and visualize PPI networks from databases such as BioGRID.ModuleRole is implemented in Java and C, and is freely available at http://www.bioinfo.org/modulerole/index.php. Supplementary information (user guide, demo data is also available at this website. API for ModuleRole used for this

  10. Ascent Heating Thermal Analysis on Spacecraft Adaptor Fairings

    Science.gov (United States)

    Wang, Xiao Yen; Yuko, James; Motil, Brian

    2011-01-01

    When the Crew Exploration Vehicle (CEV) is launched, the spacecraft adaptor (SA) fairings that cover the CEV service module (SM) are exposed to aero heating. Thermal analysis is performed to compute the fairing temperatures and to investigate whether the temperatures are within the material limits for nominal ascent aeroheating case. The ascent heating is analyzed by using computational fluid dynamics (CFD) and engineering codes at Marshall Space Flight Center. The aeroheating environment data used for this work is known as Thermal Environment 3 (TE3) heating data. One of the major concerns is with the SA fairings covering the CEV SM and the SM/crew launch vehicle (CLV) flange interface. The TE3 heating rate is a function of time, wall temperature, and the spatial locations. The implementation of the TE3 heating rate as boundary conditions in the thermal analysis becomes challenging. The ascent heating thermal analysis on SA fairings and SM/CLV flange interface are performed using two commercial software packages: Cullimore & Ring (C&R) Thermal Desktop (TD) 5.1 and MSC Patran 2007r1 b. TD is the pre-and post-processor for SINDA, which is a finite-difference-based solver. In TD, the geometry is built and meshed, the boundary conditions are defined, and then SINDA is used to compute temperatures. MSC Pthermal is a finite-element- based thermal solver. MSC Patran is the pre- and post-processor for Pthermal. Regarding the boundary conditions, the convection, contact resistance, and heat load can be imposed in different ways in both programs. These two software packages are used to build the thermal model for the same analysis to validate each other and show the differences in the modeling details.

  11. Modification of gene duplicability during the evolution of protein interaction network.

    Directory of Open Access Journals (Sweden)

    Matteo D'Antonio

    2011-04-01

    Full Text Available Duplications of genes encoding highly connected and essential proteins are selected against in several species but not in human, where duplicated genes encode highly connected proteins. To understand when and how gene duplicability changed in evolution, we compare gene and network properties in four species (Escherichia coli, yeast, fly, and human that are representative of the increase in evolutionary complexity, defined as progressive growth in the number of genes, cells, and cell types. We find that the origin and conservation of a gene significantly correlates with the properties of the encoded protein in the protein-protein interaction network. All four species preserve a core of singleton and central hubs that originated early in evolution, are highly conserved, and accomplish basic biological functions. Another group of hubs appeared in metazoans and duplicated in vertebrates, mostly through vertebrate-specific whole genome duplication. Such recent and duplicated hubs are frequently targets of microRNAs and show tissue-selective expression, suggesting that these are alternative mechanisms to control their dosage. Our study shows how networks modified during evolution and contributes to explaining the occurrence of somatic genetic diseases, such as cancer, in terms of network perturbations.

  12. Topological robustness analysis of protein interaction networks reveals key targets for overcoming chemotherapy resistance in glioma

    Science.gov (United States)

    Azevedo, Hátylas; Moreira-Filho, Carlos Alberto

    2015-11-01

    Biological networks display high robustness against random failures but are vulnerable to targeted attacks on central nodes. Thus, network topology analysis represents a powerful tool for investigating network susceptibility against targeted node removal. Here, we built protein interaction networks associated with chemoresistance to temozolomide, an alkylating agent used in glioma therapy, and analyzed their modular structure and robustness against intentional attack. These networks showed functional modules related to DNA repair, immunity, apoptosis, cell stress, proliferation and migration. Subsequently, network vulnerability was assessed by means of centrality-based attacks based on the removal of node fractions in descending orders of degree, betweenness, or the product of degree and betweenness. This analysis revealed that removing nodes with high degree and high betweenness was more effective in altering networks’ robustness parameters, suggesting that their corresponding proteins may be particularly relevant to target temozolomide resistance. In silico data was used for validation and confirmed that central nodes are more relevant for altering proliferation rates in temozolomide-resistant glioma cell lines and for predicting survival in glioma patients. Altogether, these results demonstrate how the analysis of network vulnerability to topological attack facilitates target prioritization for overcoming cancer chemoresistance.

  13. Protein Secondary Structure Prediction using Pattern Recognition Neural Network

    Directory of Open Access Journals (Sweden)

    P.V. Nageswara Rao

    2010-06-01

    Full Text Available Proteins are key biological molecules with diverse functions. With newer technologies producing more data (genomics, proteomics than can be annotated manually, in silico methods of predicting their structure and thereafter their function has been christened the Holy Grail of structural bioinformatics. Successful secondary structureprediction provides a starting point for direct tertiary structure modeling; in addition it improves sequence analysis and sequence-structure binding for structure and function determination. Using machine learning and data mining process, we developed a pattern recognition technique based on statistical for predicting protein secondary structure from the component amino acid sequence. By applying this technique, a performance score of Q8=72.3% was achieved. This compares well with other established techniques, such as NN-I and GOR IV which achieved Q3 scores of 64.05% and 63.19% respectively when predictions are made on single sequence alone.

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

    Science.gov (United States)

    Patel, Maulika S; Mazumdar, Himanshu S

    2014-11-21

    Protein structure prediction is of great relevance given the abundant genomic and proteomic data generated by the genome sequencing projects. Protein secondary structure prediction is addressed as a sub task in determining the protein tertiary structure and function. In this paper, a novel algorithm, KB-PROSSP-NN, which is a combination of knowledge base and modeling of the exceptions in the knowledge base using neural networks for protein secondary structure prediction (PSSP), is proposed. The knowledge base is derived from a proteomic sequence-structure database and consists of the statistics of association between the 5-residue words and corresponding secondary structure. The predicted results obtained using knowledge base are refined with a Backpropogation neural network algorithm. Neural net models the exceptions of the knowledge base. The Q3 accuracy of 90% and 82% is achieved on the RS126 and CB396 test sets respectively which suggest improvement over existing state of art methods.

  15. Functional protein networks unifying limb girdle muscular dystrophy

    OpenAIRE

    de Morrée, Antoine

    2011-01-01

    Limb Girdle Muscular Dystrophy (LGMD) is a rare progressive heterogeneous disorder that can be caused by mutations in at least 21 different genes. These genes are often widely expressed and encode proteins with highly differing functions. And yet mutations in all of them give rise to a similar clinical presentation: adult onset muscle weakness, with muscles of the pelvic and shoulder girdle as predominantly affected muscle groups. This thesis explores a potential molecular mechanism that unif...

  16. 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.

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

    OpenAIRE

    Spencer, Matt; Eickholt, Jesse; Cheng, Jianlin

    2014-01-01

    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% 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 atte...

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

    Directory of Open Access Journals (Sweden)

    Yong Chern Han

    2012-12-01

    Full Text Available Abstract Background Protein complexes participate in many important cellular functions, so finding the set of existent complexes is essential for understanding the organization and regulation of processes in the cell. With the availability of large amounts of high-throughput protein-protein interaction (PPI data, many algorithms have been proposed to discover protein complexes from PPI networks. However, such approaches are hindered by the high rate of noise in high-throughput PPI data, including spurious and missing interactions. Furthermore, many transient interactions are detected between proteins that are not from the same complex, while not all proteins from the same complex may actually interact. As a result, predicted complexes often do not match true complexes well, and many true complexes go undetected. Results We address these challenges by integrating PPI data with other heterogeneous data sources to construct a composite protein network, and using a supervised maximum-likelihood approach to weight each edge based on its posterior probability of belonging to a complex. We then use six different clustering algorithms, and an aggregative clustering strategy, to discover complexes in the weighted network. We test our method on Saccharomyces cerevisiae and Homo sapiens, and show that complex discovery is improved: compared to previously proposed supervised and unsupervised weighting approaches, our method recalls more known complexes, achieves higher precision at all recall levels, and generates novel complexes of greater functional similarity. Furthermore, our maximum-likelihood approach allows learned parameters to be used to visualize and evaluate the evidence of novel predictions, aiding human judgment of their credibility. Conclusions Our approach integrates multiple data sources with supervised learning to create a weighted composite protein network, and uses six clustering algorithms with an aggregative clustering strategy to

  19. A restricted set of apical proteins recycle through the trans-Golgi network in MDCK cells.

    OpenAIRE

    Brändli, A W; Simons, K

    1989-01-01

    Sorting of newly synthesized proteins destined for the apical plasma membrane takes place in the trans-Golgi network (TGN) in MDCK cells. This process is most likely receptor mediated and requires components that recycle between both compartments. We have developed an assay to detect apical proteins that recycle through the sialyltransferase-containing TGN. Cell surface glycoproteins were exogalactosylated apically using a mutant cell line derived from MDCK, MDCKII-RCAr. The mutant exhibits i...

  20. A network model to investigate structural and electrical properties of proteins

    CERN Document Server

    Alfinito, E; Reggiani, L

    2007-01-01

    One of the main trend in to date research and development is the miniaturization of electronic devices. In this perspective, integrated nanodevices based on proteins or biomolecules are attracting a major interest. In fact, it has been shown that proteins like bacteriorhodopsin and azurin, manifest electrical properties which are promising for the development of active components in the field of molecular electronics. Here we focus on two relevant kinds of proteins: The bovine rhodopsin, prototype of GPCR protein, and the enzyme acetylcholinesterase (AChE), whose inhibition is one of the most qualified treatments of Alzheimer disease. Both these proteins exert their functioning starting with a conformational change of their native structure. Our guess is that such a change should be accompanied with a detectable variation of their electrical properties. To investigate this conjecture, we present an impedance network model of proteins, able to estimate the different electrical response associated with the diff...

  1. Metazoans evolved by taking domains from soluble proteins to expand intercellular communication network.

    Science.gov (United States)

    Nam, Hyun-Jun; Kim, Inhae; Bowie, James U; Kim, Sanguk

    2015-01-01

    A central question in animal evolution is how multicellular animals evolved from unicellular ancestors. We hypothesize that membrane proteins must be key players in the development of multicellularity because they are well positioned to form the cell-cell contacts and to provide the intercellular communication required for the creation of complex organisms. Here we find that a major mechanism for the necessary increase in membrane protein complexity in the transition from non-metazoan to metazoan life was the new incorporation of domains from soluble proteins. The membrane proteins that have incorporated soluble domains in metazoans are enriched in many of the functions unique to multicellular organisms such as cell-cell adhesion, signaling, immune defense and developmental processes. They also show enhanced protein-protein interaction (PPI) network complexity and centrality, suggesting an important role in the cellular diversification found in complex organisms. Our results expose an evolutionary mechanism that contributed to the development of higher life forms. PMID:25923201

  2. A multilayer protein-protein interaction network analysis of different life stages in Caenorhabditis elegans

    Science.gov (United States)

    Shinde, Pramod; Jalan, Sarika

    2015-12-01

    Molecular networks act as the backbone of cellular activities, providing an excellent opportunity to understand the developmental changes in an organism. While network data usually constitute only stationary network graphs, constructing a multilayer PPI network may provide clues to the particular developmental role at each stage of life and may unravel the importance of these developmental changes. The developmental biology model of Caenorhabditis elegans analyzed here provides a ripe platform to understand the patterns of evolution during the life stages of an organism. In the present study, the widely studied network properties exhibit overall similar statistics for all the PPI layers. Further, the analysis of the degree-degree correlation and spectral properties not only reveals crucial differences in each PPI layer but also indicates the presence of the varying complexity among them. The PPI layer of the nematode life stage exhibits various network properties different to the rest of the PPI layers, indicating the specific role of cellular diversity and developmental transitions at this stage. The framework presented here provides a direction to explore and understand the developmental changes occurring in the different life stages of an organism.

  3. Proteomic dissection of biological pathways/processes through profiling protein-protein interaction networks

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    Cellular functions, either under the normal or pathological conditions or under different stresses, are the results of the coordinated action of multiple proteins interacting in macromolecular complexes or assemblies. The precise determination of the specific composition of protein complexes, especially using scalable and high-throughput methods, represents a systematic approach toward revealing particular cellular biological functions. In this regard, the direct profiling protein-protein interactions (PPIs) represent an efficient way to dissect functional pathways for revealing novel protein functions. In this review, we illustrate the technological evolution for the large-scale and precise identification of PPIs toward higher physiologically relevant accuracy. These techniques aim at improving the efficiency of complex pull-down, the signal specificity and accuracy in distinguishing specific PPIs, and the accuracy of identifying physiological relevant PPIs. A newly developed streamline proteomic approach for mapping the binary relationship of PPIs in a protein complex is introduced.

  4. Interplay between Chaperones and Protein Disorder Promotes the Evolution of Protein Networks

    OpenAIRE

    Sebastian Pechmann; Judith Frydman

    2014-01-01

    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 p...

  5. Integration of relational and hierarchical network information for protein function prediction

    Directory of Open Access Journals (Sweden)

    Jiang Xiaoyu

    2008-08-01

    Full Text Available Abstract Background In the current climate of high-throughput computational biology, the inference of a protein's function from related measurements, such as protein-protein interaction relations, has become a canonical task. Most existing technologies pursue this task as a classification problem, on a term-by-term basis, for each term in a database, such as the Gene Ontology (GO database, a popular rigorous vocabulary for biological functions. However, ontology structures are essentially hierarchies, with certain top to bottom annotation rules which protein function predictions should in principle follow. Currently, the most common approach to imposing these hierarchical constraints on network-based classifiers is through the use of transitive closure to predictions. Results We propose a probabilistic framework to integrate information in relational data, in the form of a protein-protein interaction network, and a hierarchically structured database of terms, in the form of the GO database, for the purpose of protein function prediction. At the heart of our framework is a factorization of local neighborhood information in the protein-protein interaction network across successive ancestral terms in the GO hierarchy. We introduce a classifier within this framework, with computationally efficient implementation, that produces GO-term predictions that naturally obey a hierarchical 'true-path' consistency from root to leaves, without the need for further post-processing. Conclusion A cross-validation study, using data from the yeast Saccharomyces cerevisiae, shows our method offers substantial improvements over both standard 'guilt-by-association' (i.e., Nearest-Neighbor and more refined Markov random field methods, whether in their original form or when post-processed to artificially impose 'true-path' consistency. Further analysis of the results indicates that these improvements are associated with increased predictive capabilities (i.e., increased

  6. Protein coalitions in a core mammalian biochemical network linked by rapidly evolving proteins

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    Tsoka Sophia

    2011-05-01

    Full Text Available Abstract Background Cellular ATP levels are generated by glucose-stimulated mitochondrial metabolism and determine metabolic responses, such as glucose-stimulated insulin secretion (GSIS from the β-cells of pancreatic islets. We describe an analysis of the evolutionary processes affecting the core enzymes involved in glucose-stimulated insulin secretion in mammals. The proteins involved in this system belong to ancient enzymatic pathways: glycolysis, the TCA cycle and oxidative phosphorylation. Results We identify two sets of proteins, or protein coalitions, in this group of 77 enzymes with distinct evolutionary patterns. Members of the glycolysis, TCA cycle, metabolite transport, pyruvate and NADH shuttles have low rates of protein sequence evolution, as inferred from a human-mouse comparison, and relatively high rates of evolutionary gene duplication. Respiratory chain and glutathione pathway proteins evolve faster, exhibiting lower rates of gene duplication. A small number of proteins in the system evolve significantly faster than co-pathway members and may serve as rapidly evolving adapters, linking groups of co-evolving genes. Conclusions Our results provide insights into the evolution of the involved proteins. We find evidence for two coalitions of proteins and the role of co-adaptation in protein evolution is identified and could be used in future research within a functional context.

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

    OpenAIRE

    Liu Wei-chung; Lin Wen-hsien; Hwang Ming-jing

    2009-01-01

    Abstract Background 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 ...

  8. Enhancing the prioritization of disease-causing genes through tissue specific protein interaction networks.

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    Oded Magger

    Full Text Available The prioritization of candidate disease-causing genes is a fundamental challenge in the post-genomic era. Current state of the art methods exploit a protein-protein interaction (PPI network for this task. They are based on the observation that genes causing phenotypically-similar diseases tend to lie close to one another in a PPI network. However, to date, these methods have used a static picture of human PPIs, while diseases impact specific tissues in which the PPI networks may be dramatically different. Here, for the first time, we perform a large-scale assessment of the contribution of tissue-specific information to gene prioritization. By integrating tissue-specific gene expression data with PPI information, we construct tissue-specific PPI networks for 60 tissues and investigate their prioritization power. We find that tissue-specific PPI networks considerably improve the prioritization results compared to those obtained using a generic PPI network. Furthermore, they allow predicting novel disease-tissue associations, pointing to sub-clinical tissue effects that may escape early detection.

  9. SLIDER: A Generic Metaheuristic for the Discovery of Correlated Motifs in Protein-Protein Interaction Networks

    NARCIS (Netherlands)

    Boyen, P.; Dyck, van D.; Neven, F.; Ham, van R.C.H.J.; Dijk, van A.D.J.

    2011-01-01

    Correlated motif mining (CMM) is the problem of finding overrepresented pairs of patterns, called motifs, in sequences of interacting proteins. Algorithmic solutions for CMM thereby provide a computational method for predicting binding sites for protein interaction. In this paper, we adopt a motif-d

  10. Protein interaction network of alternatively spliced isoforms from brain links genetic risk factors for autism.

    Science.gov (United States)

    Corominas, Roser; Yang, Xinping; Lin, Guan Ning; Kang, Shuli; Shen, Yun; Ghamsari, Lila; Broly, Martin; Rodriguez, Maria; Tam, Stanley; Trigg, Shelly A; Fan, Changyu; Yi, Song; Tasan, Murat; Lemmens, Irma; Kuang, Xingyan; Zhao, Nan; Malhotra, Dheeraj; Michaelson, Jacob J; Vacic, Vladimir; Calderwood, Michael A; Roth, Frederick P; Tavernier, Jan; Horvath, Steve; Salehi-Ashtiani, Kourosh; Korkin, Dmitry; Sebat, Jonathan; Hill, David E; Hao, Tong; Vidal, Marc; Iakoucheva, Lilia M

    2014-04-11

    Increased risk for autism spectrum disorders (ASD) is attributed to hundreds of genetic loci. The convergence of ASD variants have been investigated using various approaches, including protein interactions extracted from the published literature. However, these datasets are frequently incomplete, carry biases and are limited to interactions of a single splicing isoform, which may not be expressed in the disease-relevant tissue. Here we introduce a new interactome mapping approach by experimentally identifying interactions between brain-expressed alternatively spliced variants of ASD risk factors. The Autism Spliceform Interaction Network reveals that almost half of the detected interactions and about 30% of the newly identified interacting partners represent contribution from splicing variants, emphasizing the importance of isoform networks. Isoform interactions greatly contribute to establishing direct physical connections between proteins from the de novo autism CNVs. Our findings demonstrate the critical role of spliceform networks for translating genetic knowledge into a better understanding of human diseases.

  11. A quantitative analysis of contractility in active cytoskeletal protein networks.

    Science.gov (United States)

    Bendix, Poul M; Koenderink, Gijsje H; Cuvelier, Damien; Dogic, Zvonimir; Koeleman, Bernard N; Brieher, William M; Field, Christine M; Mahadevan, L; Weitz, David A

    2008-04-15

    Cells actively produce contractile forces for a variety of processes including cytokinesis and motility. Contractility is known to rely on myosin II motors which convert chemical energy from ATP hydrolysis into forces on actin filaments. However, the basic physical principles of cell contractility remain poorly understood. We reconstitute contractility in a simplified model system of purified F-actin, muscle myosin II motors, and alpha-actinin cross-linkers. We show that contractility occurs above a threshold motor concentration and within a window of cross-linker concentrations. We also quantify the pore size of the bundled networks and find contractility to occur at a critical distance between the bundles. We propose a simple mechanism of contraction based on myosin filaments pulling neighboring bundles together into an aggregated structure. Observations of this reconstituted system in both bulk and low-dimensional geometries show that the contracting gels pull on and deform their surface with a contractile force of approximately 1 microN, or approximately 100 pN per F-actin bundle. Cytoplasmic extracts contracting in identical environments show a similar behavior and dependence on myosin as the reconstituted system. Our results suggest that cellular contractility can be sensitively regulated by tuning the (local) activity of molecular motors and the cross-linker density and binding affinity. PMID:18192374

  12. Elastic network model of allosteric regulation in protein kinase PDK1

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    Williams Gareth

    2010-05-01

    Full Text Available Abstract Background Structural switches upon binding of phosphorylated moieties underpin many signalling networks. The ligand activation is a form of allosteric modulation of the protein, where the binding site is remote from the structural change in the protein. Recently this structural switch has been elegantly demonstrated with the crystallisation of the activated form of 3-phosphoinositide-dependent protein kinase-1 (PDK1. The purpose of the present work is to determine whether the allosteric coupling in PDK1 emerges at the level of a simple coarse grained model of protein dynamics. Results It is shown here that the allosteric effects of the agonist binding to the small lobe upon the activation loop in the large lobe of PDK1 are explainable within a simple 'ball and spring' elastic network model (ENM of protein dynamics. In particular, the model shows that the bound phospho peptide mimetic fluctuations have a high degree of correlation with the activation loop of PDK1. Conclusions The ENM approach to small molecule activation of proteins may offer a first pass predictive methodology where affinity is encoded in residues remote from the active site, and aid in the design of specific protein agonists that enhance the allosteric coupling and antagonist that repress it.

  13. Salivary Defense Proteins: Their Network and Role in Innate and Acquired Oral Immunity

    Directory of Open Access Journals (Sweden)

    Gábor Fábián

    2012-04-01

    Full Text Available There are numerous defense proteins present in the saliva. Although some of these molecules are present in rather low concentrations, their effects are additive and/or synergistic, resulting in an efficient molecular defense network of the oral cavity. Moreover, local concentrations of these proteins near the mucosal surfaces (mucosal transudate, periodontal sulcus (gingival crevicular fluid and oral wounds and ulcers (transudate may be much greater, and in many cases reinforced by immune and/or inflammatory reactions of the oral mucosa. Some defense proteins, like salivary immunoglobulins and salivary chaperokine HSP70/HSPAs (70 kDa heat shock proteins, are involved in both innate and acquired immunity. Cationic peptides and other defense proteins like lysozyme, bactericidal/permeability increasing protein (BPI, BPI-like proteins, PLUNC (palate lung and nasal epithelial clone proteins, salivary amylase, cystatins, prolin-rich proteins, mucins, peroxidases, statherin and others are primarily responsible for innate immunity. In this paper, this complex system and function of the salivary defense proteins will be reviewed.

  14. Fuel combustion test in constant volume combustion chamber with built-in adaptor

    Institute of Scientific and Technical Information of China (English)

    JEONG; DongSoo; CHO; GyuBack; CHOI; SuJin; LEE; JinSoo

    2010-01-01

    Combustion tests of pre-mixture of methane and air in constant volume combustion chamber(CVCC) have been carried out by means of flame propagation photo and gas pressure measurement,the effects of CVCC body temperature,intake pressure of pre-mixture of methane and air,equivalence ratio and location of the built-in adaptor have been investigated.The whole combustion chamber can be divided into two parts,i.e.the upper combustion chamber and the lower combustion chamber,by the built-in adaptor with through hole.Owing to the built-in adaptor with through hole,jet ignition or compression ignition(auto-ignition) phenomena may occur in the lower combustion chamber,which is helpful to getting higher flame propagation velocity,higher combustion peak pressure,low cycle-to-cycle variation and more stable combustion process.

  15. Prioritizing cancer-related genes with aberrant methylation based on a weighted protein-protein interaction network

    Directory of Open Access Journals (Sweden)

    Lv Jie

    2011-10-01

    Full Text Available Abstract Background As an important epigenetic modification, DNA methylation plays a crucial role in the development of mammals and in the occurrence of complex diseases. Genes that interact directly or indirectly may have the same or similar functions in the biological processes in which they are involved and together contribute to the related disease phenotypes. The complicated relations between genes can be clearly represented using network theory. A protein-protein interaction (PPI network offers a platform from which to systematically identify disease-related genes from the relations between genes with similar functions. Results We constructed a weighted human PPI network (WHPN using DNA methylation correlations based on human protein-protein interactions. WHPN represents the relationships of DNA methylation levels in gene pairs for four cancer types. A cancer-associated subnetwork (CASN was obtained from WHPN by selecting genes associated with seed genes which were known to be methylated in the four cancers. We found that CASN had a more densely connected network community than WHPN, indicating that the genes in CASN were much closer to seed genes. We prioritized 154 potential cancer-related genes with aberrant methylation in CASN by neighborhood-weighting decision rule. A function enrichment analysis for GO and KEGG indicated that the optimized genes were mainly involved in the biological processes of regulating cell apoptosis and programmed cell death. An analysis of expression profiling data revealed that many of the optimized genes were expressed differentially in the four cancers. By examining the PubMed co-citations, we found 43 optimized genes were related with cancers and aberrant methylation, and 10 genes were validated to be methylated aberrantly in cancers. Of 154 optimized genes, 27 were as diagnostic markers and 20 as prognostic markers previously identified in literature for cancers and other complex diseases by searching Pub

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

    Directory of Open Access Journals (Sweden)

    Julien F Ollivier

    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.

  17. Protein-protein interaction network construction for cancer using a new L1/2-penalized Net-SVM model.

    Science.gov (United States)

    Chai, H; Huang, H H; Jiang, H K; Liang, Y; Xia, L Y

    2016-01-01

    Identifying biomarker genes and characterizing interaction pathways with high-dimensional and low-sample size microarray data is a major challenge in computational biology. In this field, the construction of protein-protein interaction (PPI) networks using disease-related selected genes has garnered much attention. Support vector machines (SVMs) are commonly used to classify patients, and a number of useful tools such as lasso, elastic net, SCAD, or other regularization methods can be combined with SVM models to select genes that are related to a disease. In the current study, we propose a new Net-SVM model that is different from other SVM models as it is combined with L1/2-norm regularization, which has good performance with high-dimensional and low-sample size microarray data for cancer classification, gene selection, and PPI network construction. Both simulation studies and real data experiments demonstrated that our proposed method outperformed other regularization methods such as lasso, SCAD, and elastic net. In conclusion, our model may help to select fewer but more relevant genes, and can be used to construct simple and informative PPI networks that are highly relevant to cancer. PMID:27525863

  18. Identification of Lung-Cancer-Related Genes with the Shortest Path Approach in a Protein-Protein Interaction Network

    Directory of Open Access Journals (Sweden)

    Bi-Qing Li

    2013-01-01

    Full Text Available Lung cancer is one of the leading causes of cancer mortality worldwide. The main types of lung cancer are small cell lung cancer (SCLC and nonsmall cell lung cancer (NSCLC. In this work, a computational method was proposed for identifying lung-cancer-related genes with a shortest path approach in a protein-protein interaction (PPI network. Based on the PPI data from STRING, a weighted PPI network was constructed. 54 NSCLC- and 84 SCLC-related genes were retrieved from associated KEGG pathways. Then the shortest paths between each pair of these 54 NSCLC genes and 84 SCLC genes were obtained with Dijkstra’s algorithm. Finally, all the genes on the shortest paths were extracted, and 25 and 38 shortest genes with a permutation P value less than 0.05 for NSCLC and SCLC were selected for further analysis. Some of the shortest path genes have been reported to be related to lung cancer. Intriguingly, the candidate genes we identified from the PPI network contained more cancer genes than those identified from the gene expression profiles. Furthermore, these genes possessed more functional similarity with the known cancer genes than those identified from the gene expression profiles. This study proved the efficiency of the proposed method and showed promising results.

  19. Transport vesicle tethering at the trans Golgi network: coiled coil proteins in action

    Directory of Open Access Journals (Sweden)

    Pak-yan Patricia Cheung

    2016-03-01

    Full Text Available The Golgi complex is decorated with so-called Golgin proteins that share a common feature: a large proportion of their amino acid sequences are predicted to form coiled-coil structures. The possible presence of extensive coiled coils implies that these proteins are highly elongated molecules that can extend a significant distance from the Golgi surface. This property would help them to capture or trap inbound transport vesicles and to tether Golgi mini-stacks together. This review will summarize our current understanding of coiled coil tethers that are needed for the receipt of transport vesicles at the trans Golgi network. How do long tethering proteins actually catch vesicles? Golgi-associated, coiled coil tethers contain numerous binding sites for small GTPases, SNARE proteins, and vesicle coat proteins. How are these interactions coordinated and are any or all of them important for the tethering process? Progress towards understanding these questions and remaining, unresolved mysteries will be discussed.

  20. Protein sequence for clustering DNA based on Artificial Neural Networks

    Directory of Open Access Journals (Sweden)

    Gamal. F. Elhadi

    2012-01-01

    Full Text Available DNA is a nucleic acid that contains the genetic instructions used in the development and functioning of all known living organisms and some viruses. Clustering is a process that groups a set of objects into clusters so that the similarity among objects in the same cluster is high, while that among the objects in different clusters is low. In this paper, we proposed an approach for clustering DNA sequences using Self-Organizing Map (SOM algorithm and Protein Sequence. The main objective is to analyze biological data and to bunch DNA to many clusters more easily and efficiently. We use the proposed approach to analyze both large and small amount of input DNA sequences. The results show that the similarity of the sequences does not depend on the amount of input sequences. Our approach depends on evaluating the degree of the DNA sequences similarity using the hierarchal representation Dendrogram. Representing large amount of data using hierarchal tree gives the ability to compare large sequences efficiently

  1. 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

  2. The G Protein-Coupled Receptor Heterodimer Network (GPCR-HetNet and Its Hub Components

    Directory of Open Access Journals (Sweden)

    Dasiel O. Borroto-Escuela

    2014-05-01

    Full Text Available G protein-coupled receptors (GPCRs oligomerization has emerged as a vital characteristic of receptor structure. Substantial experimental evidence supports the existence of GPCR-GPCR interactions in a coordinated and cooperative manner. However, despite the current development of experimental techniques for large-scale detection of GPCR heteromers, in order to understand their connectivity it is necessary to develop novel tools to study the global heteroreceptor networks. To provide insight into the overall topology of the GPCR heteromers and identify key players, a collective interaction network was constructed. Experimental interaction data for each of the individual human GPCR protomers was obtained manually from the STRING and SCOPUS databases. The interaction data were used to build and analyze the network using Cytoscape software. The network was treated as undirected throughout the study. It is comprised of 156 nodes, 260 edges and has a scale-free topology. Connectivity analysis reveals a significant dominance of intrafamily versus interfamily connections. Most of the receptors within the network are linked to each other by a small number of edges. DRD2, OPRM, ADRB2, AA2AR, AA1R, OPRK, OPRD and GHSR are identified as hubs. In a network representation 10 modules/clusters also appear as a highly interconnected group of nodes. Information on this GPCR network can improve our understanding of molecular integration. GPCR-HetNet has been implemented in Java and is freely available at http://www.iiia.csic.es/~ismel/GPCR-Nets/index.html.

  3. The G protein-coupled receptor heterodimer network (GPCR-HetNet) and its hub components.

    Science.gov (United States)

    Borroto-Escuela, Dasiel O; Brito, Ismel; Romero-Fernandez, Wilber; Di Palma, Michael; Oflijan, Julia; Skieterska, Kamila; Duchou, Jolien; Van Craenenbroeck, Kathleen; Suárez-Boomgaard, Diana; Rivera, Alicia; Guidolin, Diego; Agnati, Luigi F; Fuxe, Kjell

    2014-05-14

    G protein-coupled receptors (GPCRs) oligomerization has emerged as a vital characteristic of receptor structure. Substantial experimental evidence supports the existence of GPCR-GPCR interactions in a coordinated and cooperative manner. However, despite the current development of experimental techniques for large-scale detection of GPCR heteromers, in order to understand their connectivity it is necessary to develop novel tools to study the global heteroreceptor networks. To provide insight into the overall topology of the GPCR heteromers and identify key players, a collective interaction network was constructed. Experimental interaction data for each of the individual human GPCR protomers was obtained manually from the STRING and SCOPUS databases. The interaction data were used to build and analyze the network using Cytoscape software. The network was treated as undirected throughout the study. It is comprised of 156 nodes, 260 edges and has a scale-free topology. Connectivity analysis reveals a significant dominance of intrafamily versus interfamily connections. Most of the receptors within the network are linked to each other by a small number of edges. DRD2, OPRM, ADRB2, AA2AR, AA1R, OPRK, OPRD and GHSR are identified as hubs. In a network representation 10 modules/clusters also appear as a highly interconnected group of nodes. Information on this GPCR network can improve our understanding of molecular integration. GPCR-HetNet has been implemented in Java and is freely available at http://www.iiia.csic.es/~ismel/GPCR-Nets/index.html.

  4. Local network topology in human protein interaction data predicts functional association.

    Directory of Open Access Journals (Sweden)

    Hua Li

    Full Text Available The use of high-throughput techniques to generate large volumes of protein-protein interaction (PPI data has increased the need for methods that systematically and automatically suggest functional relationships among proteins. In a yeast PPI network, previous work has shown that the local connection topology, particularly for two proteins sharing an unusually large number of neighbors, can predict functional association. In this study we improved the prediction scheme by developing a new algorithm and applied it on a human PPI network to make a genome-wide functional inference. We used the new algorithm to measure and reduce the influence of hub proteins on detecting function-associated protein pairs. We used the annotations of the Gene Ontology (GO and the Kyoto Encyclopedia of Genes and Genomes (KEGG as benchmarks to compare and evaluate the function relevance. The application of our algorithms to human PPI data yielded 4,233 significant functional associations among 1,754 proteins. Further functional comparisons between them allowed us to assign 466 KEGG pathway annotations to 274 proteins and 123 GO annotations to 114 proteins with estimated false discovery rates of <21% for KEGG and <30% for GO. We clustered 1,729 proteins by their functional associations and made functional inferences from detailed analysis on one subcluster highly enriched in the TGF-beta signaling pathway (P<10(-50. Analysis of another four subclusters also suggested potential new players in six signaling pathways worthy of further experimental investigations. Our study gives clear insight into the common neighbor-based prediction scheme and provides a reliable method for large-scale functional annotation in this post-genomic era.

  5. Stepping motor adaptor actuator for a commercial uhv linear motion feedthrough

    International Nuclear Information System (INIS)

    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

  6. Getting to the Edge: Protein dynamical networks as a new frontier in plant-microbe interactions

    Directory of Open Access Journals (Sweden)

    Cassandra C Garbutt

    2014-06-01

    Full Text Available A systems perspective on diverse phenotypes, mechanisms of infection, and responses to environmental stresses can lead to considerable advances in agriculture and medicine. A significant promise of systems biology within plants is the development of disease-resistant crop varieties, which would maximize yield output for food, clothing, building materials and biofuel production. A systems or -omics perspective frames the next frontier in the search for enhanced knowledge of plant network biology. The functional understanding of network structure and dynamics s is vital to expanding our knowledge of how the intercellular communication processes are executed. . This review article will systematically discuss various levels of organization of systems biology beginning with the building blocks termed –omes and ending with complex transcriptional and protein-protein interaction networks. We will also highlight the prevailing computational modeling approaches of biological regulatory network dynamics. The latest developments in the -omics approach will be reviewed and discussed to underline and highlight novel technologies and research directions in plant network biology.

  7. Identification of T1D susceptibility genes within the MHC region by combining protein interaction networks and SNP genotyping data

    DEFF Research Database (Denmark)

    Brorsson, C.; Hansen, Niclas Tue; Hansen, Kasper Lage;

    2009-01-01

    genes. We have developed a novel method that combines single nucleotide polymorphism (SNP) genotyping data with protein-protein interaction (ppi) networks to identify disease-associated network modules enriched for proteins encoded from the MHC region. Approximately 2500 SNPs located in the 4 Mb MHC...... of additional risk genes for T1D. Combining genetic data with knowledge about functional pathways provides new insight into mechanisms underlying T1D....

  8. The intriguing realm of protein biogenesis: Facing the green co-translational protein maturation networks.

    Science.gov (United States)

    Breiman, Adina; Fieulaine, Sonia; Meinnel, Thierry; Giglione, Carmela

    2016-05-01

    The ribosome is the cell's protein-making factory, a huge protein-RNA complex, that is essential to life. Determining the high-resolution structures of the stable "core" of this factory was among the major breakthroughs of the past decades, and was awarded the Nobel Prize in 2009. Now that the mysteries of the ribosome appear to be more traceable, detailed understanding of the mechanisms that regulate protein synthesis includes not only the well-known steps of initiation, elongation, and termination but also the less comprehended features of the co-translational events associated with the maturation of the nascent chains. The ribosome is a platform for co-translational events affecting the nascent polypeptide, including protein modifications, folding, targeting to various cellular compartments for integration into membrane or translocation, and proteolysis. These events are orchestrated by ribosome-associated protein biogenesis factors (RPBs), a group of a dozen or more factors that act as the "welcoming committee" for the nascent chain as it emerges from the ribosome. In plants these factors have evolved to fit the specificity of different cellular compartments: cytoplasm, mitochondria and chloroplast. This review focuses on the current state of knowledge of these factors and their interaction around the exit tunnel of dedicated ribosomes. Particular attention has been accorded to the plant system, highlighting the similarities and differences with other organisms.

  9. Detection of alpha-rod protein repeats using a neural network and application to huntingtin.

    Directory of Open Access Journals (Sweden)

    Gareth A Palidwor

    2009-03-01

    Full Text Available A growing number of solved protein structures display an elongated structural domain, denoted here as alpha-rod, composed of stacked pairs of anti-parallel alpha-helices. Alpha-rods are flexible and expose a large surface, which makes them suitable for protein interaction. Although most likely originating by tandem duplication of a two-helix unit, their detection using sequence similarity between repeats is poor. Here, we show that alpha-rod repeats can be detected using a neural network. The network detects more repeats than are identified by domain databases using multiple profiles, with a low level of false positives (<10%. We identify alpha-rod repeats in approximately 0.4% of proteins in eukaryotic genomes. We then investigate the results for all human proteins, identifying alpha-rod repeats for the first time in six protein families, including proteins STAG1-3, SERAC1, and PSMD1-2 & 5. We also characterize a short version of these repeats in eight protein families of Archaeal, Bacterial, and Fungal species. Finally, we demonstrate the utility of these predictions in directing experimental work to demarcate three alpha-rods in huntingtin, a protein mutated in Huntington's disease. Using yeast two hybrid analysis and an immunoprecipitation technique, we show that the huntingtin fragments containing alpha-rods associate with each other. This is the first definition of domains in huntingtin and the first validation of predicted interactions between fragments of huntingtin, which sets up directions toward functional characterization of this protein. An implementation of the repeat detection algorithm is available as a Web server with a simple graphical output: http://www.ogic.ca/projects/ard. This can be further visualized using BiasViz, a graphic tool for representation of multiple sequence alignments.

  10. 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.

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

    International Nuclear Information System (INIS)

    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.

  12. Distinct configurations of protein complexes and biochemical pathways revealed by epistatic interaction network motifs

    LENUS (Irish Health Repository)

    Casey, Fergal

    2011-08-22

    Abstract Background Gene and protein interactions are commonly represented as networks, with the genes or proteins comprising the nodes and the relationship between them as edges. Motifs, or small local configurations of edges and nodes that arise repeatedly, can be used to simplify the interpretation of networks. Results We examined triplet motifs in a network of quantitative epistatic genetic relationships, and found a non-random distribution of particular motif classes. Individual motif classes were found to be associated with different functional properties, suggestive of an underlying biological significance. These associations were apparent not only for motif classes, but for individual positions within the motifs. As expected, NNN (all negative) motifs were strongly associated with previously reported genetic (i.e. synthetic lethal) interactions, while PPP (all positive) motifs were associated with protein complexes. The two other motif classes (NNP: a positive interaction spanned by two negative interactions, and NPP: a negative spanned by two positives) showed very distinct functional associations, with physical interactions dominating for the former but alternative enrichments, typical of biochemical pathways, dominating for the latter. Conclusion We present a model showing how NNP motifs can be used to recognize supportive relationships between protein complexes, while NPP motifs often identify opposing or regulatory behaviour between a gene and an associated pathway. The ability to use motifs to point toward underlying biological organizational themes is likely to be increasingly important as more extensive epistasis mapping projects in higher organisms begin.

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

    Directory of Open Access Journals (Sweden)

    Kirouac Daniel C

    2012-05-01

    Full Text Available Abstract Background Understanding the information-processing capabilities of signal transduction networks, how those networks are disrupted in disease, and rationally designing therapies to manipulate diseased states require systematic and accurate reconstruction of network topology. Data on networks central to human physiology, such as the inflammatory signalling networks analyzed here, are found in a multiplicity of on-line resources of pathway and interactome databases (Cancer CellMap, GeneGo, KEGG, NCI-Pathway Interactome Database (NCI-PID, PANTHER, Reactome, I2D, and STRING. We sought to determine whether these databases contain overlapping information and whether they can be used to construct high reliability prior knowledge networks for subsequent modeling of experimental data. Results We have assembled an ensemble network from multiple on-line sources representing a significant portion of all machine-readable and reconcilable human knowledge on proteins and protein interactions involved in inflammation. This ensemble network has many features expected of complex signalling networks assembled from high-throughput data: a power law dis