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

PubMed

Jia, Xiuzhi; Li, Jingbo; Shi, Dejing; Zhao, Yu; Dong, Yucui; Ju, Huanyu; Yang, Jinfeng; Sun, Jianhua; Li, Xia; Ren, Huan

2014-01-01

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

Receptor Tyrosine Kinase MET Interactome and Neurodevelopmental Disorder Partners at the Developing Synapse.

PubMed

Xie, Zhihui; Li, Jing; Baker, Jonathan; Eagleson, Kathie L; Coba, Marcelo P; Levitt, Pat

2016-12-15

Atypical synapse development and plasticity are implicated in many neurodevelopmental disorders (NDDs). NDD-associated, high-confidence risk genes have been identified, yet little is known about functional relationships at the level of protein-protein interactions, which are the dominant molecular bases responsible for mediating circuit development. Proteomics in three independent developing neocortical synaptosomal preparations identified putative interacting proteins of the ligand-activated MET receptor tyrosine kinase, an autism risk gene that mediates synapse development. The candidates were translated into interactome networks and analyzed bioinformatically. Additionally, three independent quantitative proximity ligation assays in cultured neurons and four independent immunoprecipitation analyses of synaptosomes validated protein interactions. Approximately 11% (8/72) of MET-interacting proteins, including SHANK3, SYNGAP1, and GRIN2B, are associated with NDDs. Proteins in the MET interactome were translated into a novel MET interactome network based on human protein-protein interaction databases. High-confidence genes from different NDD datasets that encode synaptosomal proteins were analyzed for being enriched in MET interactome proteins. This was found for autism but not schizophrenia, bipolar disorder, major depressive disorder, or attention-deficit/hyperactivity disorder. There is correlated gene expression between MET and its interactive partners in developing human temporal and visual neocortices but not with highly expressed genes that are not in the interactome. Proximity ligation assays and biochemical analyses demonstrate that MET-protein partner interactions are dynamically regulated by receptor activation. The results provide a novel molecular framework for deciphering the functional relations of key regulators of synaptogenesis that contribute to both typical cortical development and to NDDs. Copyright © 2016 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

SInCRe—structural interactome computational resource for Mycobacterium tuberculosis

PubMed Central

Metri, Rahul; Hariharaputran, Sridhar; Ramakrishnan, Gayatri; Anand, Praveen; Raghavender, Upadhyayula S.; Ochoa-Montaño, Bernardo; Higueruelo, Alicia P.; Sowdhamini, Ramanathan; Chandra, Nagasuma R.; Blundell, Tom L.; Srinivasan, Narayanaswamy

2015-01-01

We have developed an integrated database for Mycobacterium tuberculosis H37Rv (Mtb) that collates information on protein sequences, domain assignments, functional annotation and 3D structural information along with protein–protein and protein–small molecule interactions. SInCRe (Structural Interactome Computational Resource) is developed out of CamBan (Cambridge and Bangalore) collaboration. The motivation for development of this database is to provide an integrated platform to allow easily access and interpretation of data and results obtained by all the groups in CamBan in the field of Mtb informatics. In-house algorithms and databases developed independently by various academic groups in CamBan are used to generate Mtb-specific datasets and are integrated in this database to provide a structural dimension to studies on tuberculosis. The SInCRe database readily provides information on identification of functional domains, genome-scale modelling of structures of Mtb proteins and characterization of the small-molecule binding sites within Mtb. The resource also provides structure-based function annotation, information on small-molecule binders including FDA (Food and Drug Administration)-approved drugs, protein–protein interactions (PPIs) and natural compounds that bind to pathogen proteins potentially and result in weakening or elimination of host–pathogen protein–protein interactions. Together they provide prerequisites for identification of off-target binding. Database URL: http://proline.biochem.iisc.ernet.in/sincre PMID:26130660

Inferring the Brassica rapa Interactome Using Protein–Protein Interaction Data from Arabidopsis thaliana

PubMed Central

Yang, Jianhua; Osman, Kim; Iqbal, Mudassar; Stekel, Dov J.; Luo, Zewei; Armstrong, Susan J.; Franklin, F. Chris H.

2013-01-01

Following successful completion of the Brassica rapa sequencing project, the next step is to investigate functions of individual genes/proteins. For Arabidopsis thaliana, large amounts of protein–protein interaction (PPI) data are available from the major PPI databases (DBs). It is known that Brassica crop species are closely related to A. thaliana. This provides an opportunity to infer the B. rapa interactome using PPI data available from A. thaliana. In this paper, we present an inferred B. rapa interactome that is based on the A. thaliana PPI data from two resources: (i) A. thaliana PPI data from three major DBs, BioGRID, IntAct, and TAIR. (ii) ortholog-based A. thaliana PPI predictions. Linking between B. rapa and A. thaliana was accomplished in three complementary ways: (i) ortholog predictions, (ii) identification of gene duplication based on synteny and collinearity, and (iii) BLAST sequence similarity search. A complementary approach was also applied, which used known/predicted domain–domain interaction data. Specifically, since the two species are closely related, we used PPI data from A. thaliana to predict interacting domains that might be conserved between the two species. The predicted interactome was investigated for the component that contains known A. thaliana meiotic proteins to demonstrate its usability. PMID:23293649

A Viral-Human Interactome Based on Structural Motif-Domain Interactions Captures the Human Infectome

PubMed Central

Guo, Xianwu; Rodríguez-Pérez, Mario A.

2013-01-01

Protein interactions between a pathogen and its host are fundamental in the establishment of the pathogen and underline the infection mechanism. In the present work, we developed a single predictive model for building a host-viral interactome based on the identification of structural descriptors from motif-domain interactions of protein complexes deposited in the Protein Data Bank (PDB). The structural descriptors were used for searching, in a database of protein sequences of human and five clinically important viruses; therefore, viral and human proteins sharing a descriptor were predicted as interacting proteins. The analysis of the host-viral interactome allowed to identify a set of new interactions that further explain molecular mechanism associated with viral infections and showed that it was able to capture human proteins already associated to viral infections (human infectome) and non-infectious diseases (human diseasome). The analysis of human proteins targeted by viral proteins in the context of a human interactome showed that their neighbors are enriched in proteins reported with differential expression under infection and disease conditions. It is expected that the findings of this work will contribute to the development of systems biology for infectious diseases, and help guide the rational identification and prioritization of novel drug targets. PMID:23951184

RISE: a database of RNA interactome from sequencing experiments

PubMed Central

Gong, Jing; Shao, Di; Xu, Kui

2018-01-01

Abstract We present RISE (http://rise.zhanglab.net), a database of RNA Interactome from Sequencing Experiments. RNA-RNA interactions (RRIs) are essential for RNA regulation and function. RISE provides a comprehensive collection of RRIs that mainly come from recent transcriptome-wide sequencing-based experiments like PARIS, SPLASH, LIGR-seq, and MARIO, as well as targeted studies like RIA-seq, RAP-RNA and CLASH. It also includes interactions aggregated from other primary databases and publications. The RISE database currently contains 328,811 RNA-RNA interactions mainly in human, mouse and yeast. While most existing RNA databases mainly contain interactions of miRNA targeting, notably, more than half of the RRIs in RISE are among mRNA and long non-coding RNAs. We compared different RRI datasets in RISE and found limited overlaps in interactions resolved by different techniques and in different cell lines. It may suggest technology preference and also dynamic natures of RRIs. We also analyzed the basic features of the human and mouse RRI networks and found that they tend to be scale-free, small-world, hierarchical and modular. The analysis may nominate important RNAs or RRIs for further investigation. Finally, RISE provides a Circos plot and several table views for integrative visualization, with extensive molecular and functional annotations to facilitate exploration of biological functions for any RRI of interest. PMID:29040625

Inborn errors of metabolism and the human interactome: a systems medicine approach.

PubMed

Woidy, Mathias; Muntau, Ania C; Gersting, Søren W

2018-02-05

The group of inborn errors of metabolism (IEM) displays a marked heterogeneity and IEM can affect virtually all functions and organs of the human organism; however, IEM share that their associated proteins function in metabolism. Most proteins carry out cellular functions by interacting with other proteins, and thus are organized in biological networks. Therefore, diseases are rarely the consequence of single gene mutations but of the perturbations caused in the related cellular network. Systematic approaches that integrate multi-omics and database information into biological networks have successfully expanded our knowledge of complex disorders but network-based strategies have been rarely applied to study IEM. We analyzed IEM on a proteome scale and found that IEM-associated proteins are organized as a network of linked modules within the human interactome of protein interactions, the IEM interactome. Certain IEM disease groups formed self-contained disease modules, which were highly interlinked. On the other hand, we observed disease modules consisting of proteins from many different disease groups in the IEM interactome. Moreover, we explored the overlap between IEM and non-IEM disease genes and applied network medicine approaches to investigate shared biological pathways, clinical signs and symptoms, and links to drug targets. The provided resources may help to elucidate the molecular mechanisms underlying new IEM, to uncover the significance of disease-associated mutations, to identify new biomarkers, and to develop novel therapeutic strategies.

hPDI: a database of experimental human protein-DNA interactions.

PubMed

Xie, Zhi; Hu, Shaohui; Blackshaw, Seth; Zhu, Heng; Qian, Jiang

2010-01-15

The human protein DNA Interactome (hPDI) database holds experimental protein-DNA interaction data for humans identified by protein microarray assays. The unique characteristics of hPDI are that it contains consensus DNA-binding sequences not only for nearly 500 human transcription factors but also for >500 unconventional DNA-binding proteins, which are completely uncharacterized previously. Users can browse, search and download a subset or the entire data via a web interface. This database is freely accessible for any academic purposes. http://bioinfo.wilmer.jhu.edu/PDI/.

Competing endogenous RNA and interactome bioinformatic analyses on human telomerase.

PubMed

Arancio, Walter; Pizzolanti, Giuseppe; Genovese, Swonild Ilenia; Baiamonte, Concetta; Giordano, Carla

2014-04-01

We present a classic interactome bioinformatic analysis and a study on competing endogenous (ce) RNAs for hTERT. The hTERT gene codes for the catalytic subunit and limiting component of the human telomerase complex. Human telomerase reverse transcriptase (hTERT) is essential for the integrity of telomeres. Telomere dysfunctions have been widely reported to be involved in aging, cancer, and cellular senescence. The hTERT gene network has been analyzed using the BioGRID interaction database (http://thebiogrid.org/) and related analysis tools such as Osprey (http://biodata.mshri.on.ca/osprey/servlet/Index) and GeneMANIA (http://genemania.org/). The network of interaction of hTERT transcripts has been further analyzed following the competing endogenous (ce) RNA hypotheses (messenger [m] RNAs cross-talk via micro [mi] RNAs) using the miRWalk database and tools (www.ma.uni-heidelberg.de/apps/zmf/mirwalk/). These analyses suggest a role for Akt, nuclear factor-κB (NF-κB), heat shock protein 90 (HSP90), p70/p80 autoantigen, 14-3-3 proteins, and dynein in telomere functions. Roles for histone acetylation/deacetylation and proteoglycan metabolism are also proposed.

A Systems Biology Approach to Reveal Putative Host-Derived Biomarkers of Periodontitis by Network Topology Characterization of MMP-REDOX/NO and Apoptosis Integrated Pathways.

PubMed

Zeidán-Chuliá, Fares; Gürsoy, Mervi; Neves de Oliveira, Ben-Hur; Özdemir, Vural; Könönen, Eija; Gürsoy, Ulvi K

2015-01-01

Periodontitis, a formidable global health burden, is a common chronic disease that destroys tooth-supporting tissues. Biomarkers of the early phase of this progressive disease are of utmost importance for global health. In this context, saliva represents a non-invasive biosample. By using systems biology tools, we aimed to (1) identify an integrated interactome between matrix metalloproteinase (MMP)-REDOX/nitric oxide (NO) and apoptosis upstream pathways of periodontal inflammation, and (2) characterize the attendant topological network properties to uncover putative biomarkers to be tested in saliva from patients with periodontitis. Hence, we first generated a protein-protein network model of interactions ("BIOMARK" interactome) by using the STRING 10 database, a search tool for the retrieval of interacting genes/proteins, with "Experiments" and "Databases" as input options and a confidence score of 0.400. Second, we determined the centrality values (closeness, stress, degree or connectivity, and betweenness) for the "BIOMARK" members by using the Cytoscape software. We found Ubiquitin C (UBC), Jun proto-oncogene (JUN), and matrix metalloproteinase-14 (MMP14) as the most central hub- and non-hub-bottlenecks among the 211 genes/proteins of the whole interactome. We conclude that UBC, JUN, and MMP14 are likely an optimal candidate group of host-derived biomarkers, in combination with oral pathogenic bacteria-derived proteins, for detecting periodontitis at its early phase by using salivary samples from patients. These findings therefore have broader relevance for systems medicine in global health as well.

PodNet, a protein-protein interaction network of the podocyte.

PubMed

Warsow, Gregor; Endlich, Nicole; Schordan, Eric; Schordan, Sandra; Chilukoti, Ravi K; Homuth, Georg; Moeller, Marcus J; Fuellen, Georg; Endlich, Karlhans

2013-07-01

Interactions between proteins crucially determine cellular structure and function. Differential analysis of the interactome may help elucidate molecular mechanisms during disease development; however, this analysis necessitates mapping of expression data on protein-protein interaction networks. These networks do not exist for the podocyte; therefore, we built PodNet, a literature-based mouse podocyte network in Cytoscape format. Using database protein-protein interactions, we expanded PodNet to XPodNet with enhanced connectivity. In order to test the performance of XPodNet in differential interactome analysis, we examined podocyte developmental differentiation and the effect of cell culture. Transcriptomes of podocytes in 10 different states were mapped on XPodNet and analyzed with the Cytoscape plugin ExprEssence, based on the law of mass action. Interactions between slit diaphragm proteins are most significantly upregulated during podocyte development and most significantly downregulated in culture. On the other hand, our analysis revealed that interactions lost during podocyte differentiation are not regained in culture, suggesting a loss rather than a reversal of differentiation for podocytes in culture. Thus, we have developed PodNet as a valuable tool for differential interactome analysis in podocytes, and we have identified established and unexplored regulated interactions in developing and cultured podocytes.

The extraction of drug-disease correlations based on module distance in incomplete human interactome.

PubMed

Yu, Liang; Wang, Bingbo; Ma, Xiaoke; Gao, Lin

2016-12-23

Extracting drug-disease correlations is crucial in unveiling disease mechanisms, as well as discovering new indications of available drugs, or drug repositioning. Both the interactome and the knowledge of disease-associated and drug-associated genes remain incomplete. We present a new method to predict the associations between drugs and diseases. Our method is based on a module distance, which is originally proposed to calculate distances between modules in incomplete human interactome. We first map all the disease genes and drug genes to a combined protein interaction network. Then based on the module distance, we calculate the distances between drug gene sets and disease gene sets, and take the distances as the relationships of drug-disease pairs. We also filter possible false positive drug-disease correlations by p-value. Finally, we validate the top-100 drug-disease associations related to six drugs in the predicted results. The overlapping between our predicted correlations with those reported in Comparative Toxicogenomics Database (CTD) and literatures, and their enriched Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways demonstrate our approach can not only effectively identify new drug indications, but also provide new insight into drug-disease discovery.

NABIC: A New Access Portal to Search, Visualize, and Share Agricultural Genomics Data.

PubMed

Seol, Young-Joo; Lee, Tae-Ho; Park, Dong-Suk; Kim, Chang-Kug

2016-01-01

The National Agricultural Biotechnology Information Center developed an access portal to search, visualize, and share agricultural genomics data with a focus on South Korean information and resources. The portal features an agricultural biotechnology database containing a wide range of omics data from public and proprietary sources. We collected 28.4 TB of data from 162 agricultural organisms, with 10 types of omics data comprising next-generation sequencing sequence read archive, genome, gene, nucleotide, DNA chip, expressed sequence tag, interactome, protein structure, molecular marker, and single-nucleotide polymorphism datasets. Our genomic resources contain information on five animals, seven plants, and one fungus, which is accessed through a genome browser. We also developed a data submission and analysis system as a web service, with easy-to-use functions and cutting-edge algorithms, including those for handling next-generation sequencing data.

TrypsNetDB: An integrated framework for the functional characterization of trypanosomatid proteins

PubMed Central

Gazestani, Vahid H.; Yip, Chun Wai; Nikpour, Najmeh; Berghuis, Natasha

2017-01-01

Trypanosomatid parasites cause serious infections in humans and production losses in livestock. Due to the high divergence from other eukaryotes, such as humans and model organisms, the functional roles of many trypanosomatid proteins cannot be predicted by homology-based methods, rendering a significant portion of their proteins as uncharacterized. Recent technological advances have led to the availability of multiple systematic and genome-wide datasets on trypanosomatid parasites that are informative regarding the biological role(s) of their proteins. Here, we report TrypsNetDB (http://trypsNetDB.org), a web-based resource for the functional annotation of 16 different species/strains of trypanosomatid parasites. The database not only visualizes the network context of the queried protein(s) in an intuitive way but also examines the response of the represented network in more than 50 different biological contexts and its enrichment for various biological terms and pathways, protein sequence signatures, and potential RNA regulatory elements. The interactome core of the database, as of Jan 23, 2017, contains 101,187 interactions among 13,395 trypanosomatid proteins inferred from 97 genome-wide and focused studies on the interactome of these organisms. PMID:28158179

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

PubMed

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

2018-04-27

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

NABIC: A New Access Portal to Search, Visualize, and Share Agricultural Genomics Data

PubMed Central

Seol, Young-Joo; Lee, Tae-Ho; Park, Dong-Suk; Kim, Chang-Kug

2016-01-01

The National Agricultural Biotechnology Information Center developed an access portal to search, visualize, and share agricultural genomics data with a focus on South Korean information and resources. The portal features an agricultural biotechnology database containing a wide range of omics data from public and proprietary sources. We collected 28.4 TB of data from 162 agricultural organisms, with 10 types of omics data comprising next-generation sequencing sequence read archive, genome, gene, nucleotide, DNA chip, expressed sequence tag, interactome, protein structure, molecular marker, and single-nucleotide polymorphism datasets. Our genomic resources contain information on five animals, seven plants, and one fungus, which is accessed through a genome browser. We also developed a data submission and analysis system as a web service, with easy-to-use functions and cutting-edge algorithms, including those for handling next-generation sequencing data. PMID:26848255

Domain-based prediction of the human isoform interactome provides insights into the functional impact of alternative splicing.

PubMed

Ghadie, Mohamed Ali; Lambourne, Luke; Vidal, Marc; Xia, Yu

2017-08-01

Alternative splicing is known to remodel protein-protein interaction networks ("interactomes"), yet large-scale determination of isoform-specific interactions remains challenging. We present a domain-based method to predict the isoform interactome from the reference interactome. First, we construct the domain-resolved reference interactome by mapping known domain-domain interactions onto experimentally-determined interactions between reference proteins. Then, we construct the isoform interactome by predicting that an isoform loses an interaction if it loses the domain mediating the interaction. Our prediction framework is of high-quality when assessed by experimental data. The predicted human isoform interactome reveals extensive network remodeling by alternative splicing. Protein pairs interacting with different isoforms of the same gene tend to be more divergent in biological function, tissue expression, and disease phenotype than protein pairs interacting with the same isoforms. Our prediction method complements experimental efforts, and demonstrates that integrating structural domain information with interactomes provides insights into the functional impact of alternative splicing.

Reconstruction of the experimentally supported human protein interactome: what can we learn?

PubMed

Klapa, Maria I; Tsafou, Kalliopi; Theodoridis, Evangelos; Tsakalidis, Athanasios; Moschonas, Nicholas K

2013-10-02

Understanding the topology and dynamics of the human protein-protein interaction (PPI) network will significantly contribute to biomedical research, therefore its systematic reconstruction is required. Several meta-databases integrate source PPI datasets, but the protein node sets of their networks vary depending on the PPI data combined. Due to this inherent heterogeneity, the way in which the human PPI network expands via multiple dataset integration has not been comprehensively analyzed. We aim at assembling the human interactome in a global structured way and exploring it to gain insights of biological relevance. First, we defined the UniProtKB manually reviewed human "complete" proteome as the reference protein-node set and then we mined five major source PPI datasets for direct PPIs exclusively between the reference proteins. We updated the protein and publication identifiers and normalized all PPIs to the UniProt identifier level. The reconstructed interactome covers approximately 60% of the human proteome and has a scale-free structure. No apparent differentiating gene functional classification characteristics were identified for the unrepresented proteins. The source dataset integration augments the network mainly in PPIs. Polyubiquitin emerged as the highest-degree node, but the inclusion of most of its identified PPIs may be reconsidered. The high number (>300) of connections of the subsequent fifteen proteins correlates well with their essential biological role. According to the power-law network structure, the unrepresented proteins should mainly have up to four connections with equally poorly-connected interactors. Reconstructing the human interactome based on the a priori definition of the protein nodes enabled us to identify the currently included part of the human "complete" proteome, and discuss the role of the proteins within the network topology with respect to their function. As the network expansion has to comply with the scale-free theory, we suggest that the core of the human interactome has essentially emerged. Thus, it could be employed in systems biology and biomedical research, despite the considerable number of currently unrepresented proteins. The latter are probably involved in specialized physiological conditions, justifying the scarcity of related PPI information, and their identification can assist in designing relevant functional experiments and targeted text mining algorithms.

Proteome-scale human interactomics

PubMed Central

Luck, Katja; Sheynkman, Gloria M.; Zhang, Ivy; Vidal, Marc

2017-01-01

Cellular functions are mediated by complex interactome networks of physical, biochemical, and functional interactions between DNA sequences, RNA molecules, proteins, lipids, and small metabolites. A thorough understanding of cellular organization requires accurate and relatively complete models of interactome networks at proteome-scale. The recent publication of four human protein-protein interaction (PPI) maps represents a technological breakthrough and an unprecedented resource for the scientific community, heralding a new era of proteome-scale human interactomics. Our knowledge gained from these and complementary studies provides fresh insights into the opportunities and challenges when analyzing systematically generated interactome data, defines a clear roadmap towards the generation of a first reference interactome, and reveals new perspectives on the organization of cellular life. PMID:28284537

Interactome disassembly during apoptosis occurs independent of caspase cleavage.

PubMed

Scott, Nichollas E; Rogers, Lindsay D; Prudova, Anna; Brown, Nat F; Fortelny, Nikolaus; Overall, Christopher M; Foster, Leonard J

2017-01-12

Protein-protein interaction networks (interactomes) define the functionality of all biological systems. In apoptosis, proteolysis by caspases is thought to initiate disassembly of protein complexes and cell death. Here we used a quantitative proteomics approach, protein correlation profiling (PCP), to explore changes in cytoplasmic and mitochondrial interactomes in response to apoptosis initiation as a function of caspase activity. We measured the response to initiation of Fas-mediated apoptosis in 17,991 interactions among 2,779 proteins, comprising the largest dynamic interactome to date. The majority of interactions were unaffected early in apoptosis, but multiple complexes containing known caspase targets were disassembled. Nonetheless, proteome-wide analysis of proteolytic processing by terminal amine isotopic labeling of substrates (TAILS) revealed little correlation between proteolytic and interactome changes. Our findings show that, in apoptosis, significant interactome alterations occur before and independently of caspase activity. Thus, apoptosis initiation includes a tight program of interactome rearrangement, leading to disassembly of relatively few, select complexes. These early interactome alterations occur independently of cleavage of these protein by caspases. © 2017 The Authors. Published under the terms of the CC BY 4.0 license.

Functional integrative levels in the human interactome recapitulate organ organization.

PubMed

Souiai, Ouissem; Becker, Emmanuelle; Prieto, Carlos; Benkahla, Alia; De las Rivas, Javier; Brun, Christine

2011-01-01

Interactome networks represent sets of possible physical interactions between proteins. They lack spatio-temporal information by construction. However, the specialized functions of the differentiated cell types which are assembled into tissues or organs depend on the combinatorial arrangements of proteins and their physical interactions. Is tissue-specificity, therefore, encoded within the interactome? In order to address this question, we combined protein-protein interactions, expression data, functional annotations and interactome topology. We first identified a subnetwork formed exclusively of proteins whose interactions were observed in all tested tissues. These are mainly involved in housekeeping functions and are located at the topological center of the interactome. This 'Largest Common Interactome Network' represents a 'functional interactome core'. Interestingly, two types of tissue-specific interactions are distinguished when considering function and network topology: tissue-specific interactions involved in regulatory and developmental functions are central whereas tissue-specific interactions involved in organ physiological functions are peripheral. Overall, the functional organization of the human interactome reflects several integrative levels of functions with housekeeping and regulatory tissue-specific functions at the center and physiological tissue-specific functions at the periphery. This gradient of functions recapitulates the organization of organs, from cells to organs. Given that several gradients have already been identified across interactomes, we propose that gradients may represent a general principle of protein-protein interaction network organization.

Proteome-Scale Human Interactomics.

PubMed

Luck, Katja; Sheynkman, Gloria M; Zhang, Ivy; Vidal, Marc

2017-05-01

Cellular functions are mediated by complex interactome networks of physical, biochemical, and functional interactions between DNA sequences, RNA molecules, proteins, lipids, and small metabolites. A thorough understanding of cellular organization requires accurate and relatively complete models of interactome networks at proteome scale. The recent publication of four human protein-protein interaction (PPI) maps represents a technological breakthrough and an unprecedented resource for the scientific community, heralding a new era of proteome-scale human interactomics. Our knowledge gained from these and complementary studies provides fresh insights into the opportunities and challenges when analyzing systematically generated interactome data, defines a clear roadmap towards the generation of a first reference interactome, and reveals new perspectives on the organization of cellular life. Copyright © 2017 Elsevier Ltd. All rights reserved.

Functional Integrative Levels in the Human Interactome Recapitulate Organ Organization

PubMed Central

Prieto, Carlos; Benkahla, Alia; De Las Rivas, Javier; Brun, Christine

2011-01-01

Interactome networks represent sets of possible physical interactions between proteins. They lack spatio-temporal information by construction. However, the specialized functions of the differentiated cell types which are assembled into tissues or organs depend on the combinatorial arrangements of proteins and their physical interactions. Is tissue-specificity, therefore, encoded within the interactome? In order to address this question, we combined protein-protein interactions, expression data, functional annotations and interactome topology. We first identified a subnetwork formed exclusively of proteins whose interactions were observed in all tested tissues. These are mainly involved in housekeeping functions and are located at the topological center of the interactome. This ‘Largest Common Interactome Network’ represents a ‘functional interactome core’. Interestingly, two types of tissue-specific interactions are distinguished when considering function and network topology: tissue-specific interactions involved in regulatory and developmental functions are central whereas tissue-specific interactions involved in organ physiological functions are peripheral. Overall, the functional organization of the human interactome reflects several integrative levels of functions with housekeeping and regulatory tissue-specific functions at the center and physiological tissue-specific functions at the periphery. This gradient of functions recapitulates the organization of organs, from cells to organs. Given that several gradients have already been identified across interactomes, we propose that gradients may represent a general principle of protein-protein interaction network organization. PMID:21799769

Domain-based prediction of the human isoform interactome provides insights into the functional impact of alternative splicing

PubMed Central

Lambourne, Luke; Vidal, Marc

2017-01-01

Alternative splicing is known to remodel protein-protein interaction networks (“interactomes”), yet large-scale determination of isoform-specific interactions remains challenging. We present a domain-based method to predict the isoform interactome from the reference interactome. First, we construct the domain-resolved reference interactome by mapping known domain-domain interactions onto experimentally-determined interactions between reference proteins. Then, we construct the isoform interactome by predicting that an isoform loses an interaction if it loses the domain mediating the interaction. Our prediction framework is of high-quality when assessed by experimental data. The predicted human isoform interactome reveals extensive network remodeling by alternative splicing. Protein pairs interacting with different isoforms of the same gene tend to be more divergent in biological function, tissue expression, and disease phenotype than protein pairs interacting with the same isoforms. Our prediction method complements experimental efforts, and demonstrates that integrating structural domain information with interactomes provides insights into the functional impact of alternative splicing. PMID:28846689

The mRNA-bound proteome of the early fly embryo

PubMed Central

Wessels, Hans-Hermann; Imami, Koshi; Baltz, Alexander G.; Kolinski, Marcin; Beldovskaya, Anastasia; Selbach, Matthias; Small, Stephen; Ohler, Uwe; Landthaler, Markus

2016-01-01

Early embryogenesis is characterized by the maternal to zygotic transition (MZT), in which maternally deposited messenger RNAs are degraded while zygotic transcription begins. Before the MZT, post-transcriptional gene regulation by RNA-binding proteins (RBPs) is the dominant force in embryo patterning. We used two mRNA interactome capture methods to identify RBPs bound to polyadenylated transcripts within the first 2 h of Drosophila melanogaster embryogenesis. We identified a high-confidence set of 476 putative RBPs and confirmed RNA-binding activities for most of 24 tested candidates. Most proteins in the interactome are known RBPs or harbor canonical RBP features, but 99 exhibited previously uncharacterized RNA-binding activity. mRNA-bound RBPs and TFs exhibit distinct expression dynamics, in which the newly identified RBPs dominate the first 2 h of embryonic development. Integrating our resource with in situ hybridization data from existing databases showed that mRNAs encoding RBPs are enriched in posterior regions of the early embryo, suggesting their general importance in posterior patterning and germ cell maturation. PMID:27197210

System-wide identification of RNA-binding proteins by interactome capture.

PubMed

Castello, Alfredo; Horos, Rastislav; Strein, Claudia; Fischer, Bernd; Eichelbaum, Katrin; Steinmetz, Lars M; Krijgsveld, Jeroen; Hentze, Matthias W

2013-03-01

Owing to their preeminent biological functions, the repertoire of expressed RNA-binding proteins (RBPs) and their activity states are highly informative about cellular systems. We have developed a novel and unbiased technique, called interactome capture, for identifying the active RBPs of cultured cells. By making use of in vivo UV cross-linking of RBPs to polyadenylated RNAs, covalently bound proteins are captured with oligo(dT) magnetic beads. After stringent washes, the mRNA interactome is determined by quantitative mass spectrometry (MS). The protocol takes 3 working days for analysis of single proteins by western blotting, and about 2 weeks for the determination of complete cellular mRNA interactomes by MS. The most important advantage of interactome capture over other in vitro and in silico approaches is that only RBPs bound to RNA in a physiological environment are identified. When applied to HeLa cells, interactome capture revealed hundreds of novel RBPs. Interactome capture can also be broadly used to compare different biological states, including metabolic stress, cell cycle, differentiation, development or the response to drugs.

Interactome Networks and Human Disease

PubMed Central

Vidal, Marc; Cusick, Michael E.; Barabási, Albert-László

2011-01-01

Complex biological systems and cellular networks may underlie most genotype to phenotype relationships. Here we review basic concepts in network biology, discussing different types of interactome networks and the insights that can come from analyzing them. We elaborate on why interactome networks are important to consider in biology, how they can be mapped and integrated with each other, what global properties are starting to emerge from interactome network models, and how these properties may relate to human disease. PMID:21414488

The interactome of CCT complex - A computational analysis.

PubMed

Narayanan, Aswathy; Pullepu, Dileep; Kabir, M Anaul

2016-10-01

The eukaryotic chaperonin, CCT (Chaperonin Containing TCP1 or TriC-TCP-1 Ring Complex) has been subjected to physical and genetic analyses in S. cerevisiae which can be extrapolated to human CCT (hCCT), owing to its structural and functional similarities with yeast CCT (yCCT). Studies on hCCT and its interactome acquire an additional dimension, as it has been implicated in several disease conditions like neurodegeneration and cancer. We attempt to study its stress response role in general, which will be reflected in the aspects of human diseases and yeast physiology, through computational analysis of the interactome. Towards consolidating and analysing the interactome data, we prepared and compared the unique CCT-interacting protein lists for S. cerevisiae and H. sapiens, performed GO term classification and enrichment studies which provide information on the diversity in CCT interactome, in terms of protein classes in the data set. Enrichment with disease-associated proteins and pathways highlight the medical importance of CCT. Different analyses converge, suggesting the significance of WD-repeat proteins, protein kinases and cytoskeletal proteins in the interactome. The prevalence of proteasomal subunits and ribosomal proteins suggest a possible cross-talk between protein-synthesis, folding and degradation machinery. A network of chaperones and chaperonins that function in combination can also be envisaged from the CCT interactome-Hsp70 interactome analysis. Copyright © 2016 Elsevier Ltd. All rights reserved.

Reconstruction of the experimentally supported human protein interactome: what can we learn?

PubMed Central

2013-01-01

Background Understanding the topology and dynamics of the human protein-protein interaction (PPI) network will significantly contribute to biomedical research, therefore its systematic reconstruction is required. Several meta-databases integrate source PPI datasets, but the protein node sets of their networks vary depending on the PPI data combined. Due to this inherent heterogeneity, the way in which the human PPI network expands via multiple dataset integration has not been comprehensively analyzed. We aim at assembling the human interactome in a global structured way and exploring it to gain insights of biological relevance. Results First, we defined the UniProtKB manually reviewed human “complete” proteome as the reference protein-node set and then we mined five major source PPI datasets for direct PPIs exclusively between the reference proteins. We updated the protein and publication identifiers and normalized all PPIs to the UniProt identifier level. The reconstructed interactome covers approximately 60% of the human proteome and has a scale-free structure. No apparent differentiating gene functional classification characteristics were identified for the unrepresented proteins. The source dataset integration augments the network mainly in PPIs. Polyubiquitin emerged as the highest-degree node, but the inclusion of most of its identified PPIs may be reconsidered. The high number (>300) of connections of the subsequent fifteen proteins correlates well with their essential biological role. According to the power-law network structure, the unrepresented proteins should mainly have up to four connections with equally poorly-connected interactors. Conclusions Reconstructing the human interactome based on the a priori definition of the protein nodes enabled us to identify the currently included part of the human “complete” proteome, and discuss the role of the proteins within the network topology with respect to their function. As the network expansion has to comply with the scale-free theory, we suggest that the core of the human interactome has essentially emerged. Thus, it could be employed in systems biology and biomedical research, despite the considerable number of currently unrepresented proteins. The latter are probably involved in specialized physiological conditions, justifying the scarcity of related PPI information, and their identification can assist in designing relevant functional experiments and targeted text mining algorithms. PMID:24088582

Network biology discovers pathogen contact points in host protein-protein interactomes.

PubMed

Ahmed, Hadia; Howton, T C; Sun, Yali; Weinberger, Natascha; Belkhadir, Youssef; Mukhtar, M Shahid

2018-06-13

In all organisms, major biological processes are controlled by complex protein-protein interactions networks (interactomes), yet their structural complexity presents major analytical challenges. Here, we integrate a compendium of over 4300 phenotypes with Arabidopsis interactome (AI-1 MAIN ). We show that nodes with high connectivity and betweenness are enriched and depleted in conditional and essential phenotypes, respectively. Such nodes are located in the innermost layers of AI-1 MAIN and are preferential targets of pathogen effectors. We extend these network-centric analyses to Cell Surface Interactome (CSI LRR ) and predict its 35 most influential nodes. To determine their biological relevance, we show that these proteins physically interact with pathogen effectors and modulate plant immunity. Overall, our findings contrast with centrality-lethality rule, discover fast information spreading nodes, and highlight the structural properties of pathogen targets in two different interactomes. Finally, this theoretical framework could possibly be applicable to other inter-species interactomes to reveal pathogen contact points.

Interactome INSIDER: a structural interactome browser for genomic studies.

PubMed

Meyer, Michael J; Beltrán, Juan Felipe; Liang, Siqi; Fragoza, Robert; Rumack, Aaron; Liang, Jin; Wei, Xiaomu; Yu, Haiyuan

2018-01-01

We present Interactome INSIDER, a tool to link genomic variant information with structural protein-protein interactomes. Underlying this tool is the application of machine learning to predict protein interaction interfaces for 185,957 protein interactions with previously unresolved interfaces in human and seven model organisms, including the entire experimentally determined human binary interactome. Predicted interfaces exhibit functional properties similar to those of known interfaces, including enrichment for disease mutations and recurrent cancer mutations. Through 2,164 de novo mutagenesis experiments, we show that mutations of predicted and known interface residues disrupt interactions at a similar rate and much more frequently than mutations outside of predicted interfaces. To spur functional genomic studies, Interactome INSIDER (http://interactomeinsider.yulab.org) enables users to identify whether variants or disease mutations are enriched in known and predicted interaction interfaces at various resolutions. Users may explore known population variants, disease mutations, and somatic cancer mutations, or they may upload their own set of mutations for this purpose.

A TRPV2 interactome-based signature for prognosis in glioblastoma patients.

PubMed

Doñate-Macián, Pau; Gómez, Antonio; Dégano, Irene R; Perálvarez-Marín, Alex

2018-04-06

Proteomics aids to the discovery and expansion of protein-protein interaction networks, which are key to understand molecular mechanisms in physiology and physiopathology, but also to infer protein function in a guilt-by-association fashion. In this study we use a systematic protein-protein interaction membrane yeast two-hybrid method to expand the interactome of TRPV2, a cation channel related to nervous system development. After validation of the interactome in silico , we define a TRPV2-interactome signature combining proteomics with the available physio-pathological data in Disgenet to find interactome-disease associations, highlighting nervous system disorders and neoplasms. The TRPV2-interactome signature against available experimental data is capable of discriminating overall risk in glioblastoma multiforme prognosis, progression, recurrence, and chemotherapy resistance. Beyond the impact on glioblastoma physiopathology, this study shows that combining systematic proteomics with in silico methods and available experimental data is key to open new perspectives to define novel biomarkers for diagnosis, prognosis and therapeutics in disease.

A TRPV2 interactome-based signature for prognosis in glioblastoma patients

PubMed Central

Dégano, Irene R.; Perálvarez-Marín, Alex

2018-01-01

Proteomics aids to the discovery and expansion of protein-protein interaction networks, which are key to understand molecular mechanisms in physiology and physiopathology, but also to infer protein function in a guilt-by-association fashion. In this study we use a systematic protein-protein interaction membrane yeast two-hybrid method to expand the interactome of TRPV2, a cation channel related to nervous system development. After validation of the interactome in silico, we define a TRPV2-interactome signature combining proteomics with the available physio-pathological data in Disgenet to find interactome-disease associations, highlighting nervous system disorders and neoplasms. The TRPV2-interactome signature against available experimental data is capable of discriminating overall risk in glioblastoma multiforme prognosis, progression, recurrence, and chemotherapy resistance. Beyond the impact on glioblastoma physiopathology, this study shows that combining systematic proteomics with in silico methods and available experimental data is key to open new perspectives to define novel biomarkers for diagnosis, prognosis and therapeutics in disease. PMID:29719613

Prediction model of potential hepatocarcinogenicity of rat hepatocarcinogens using a large-scale toxicogenomics database

DOE Office of Scientific and Technical Information (OSTI.GOV)

Uehara, Takeki, E-mail: takeki.uehara@shionogi.co.jp; Toxicogenomics Informatics Project, National Institute of Biomedical Innovation, 7-6-8 Asagi, Ibaraki, Osaka 567-0085; Minowa, Yohsuke

2011-09-15

The present study was performed to develop a robust gene-based prediction model for early assessment of potential hepatocarcinogenicity of chemicals in rats by using our toxicogenomics database, TG-GATEs (Genomics-Assisted Toxicity Evaluation System developed by the Toxicogenomics Project in Japan). The positive training set consisted of high- or middle-dose groups that received 6 different non-genotoxic hepatocarcinogens during a 28-day period. The negative training set consisted of high- or middle-dose groups of 54 non-carcinogens. Support vector machine combined with wrapper-type gene selection algorithms was used for modeling. Consequently, our best classifier yielded prediction accuracies for hepatocarcinogenicity of 99% sensitivity and 97% specificitymore » in the training data set, and false positive prediction was almost completely eliminated. Pathway analysis of feature genes revealed that the mitogen-activated protein kinase p38- and phosphatidylinositol-3-kinase-centered interactome and the v-myc myelocytomatosis viral oncogene homolog-centered interactome were the 2 most significant networks. The usefulness and robustness of our predictor were further confirmed in an independent validation data set obtained from the public database. Interestingly, similar positive predictions were obtained in several genotoxic hepatocarcinogens as well as non-genotoxic hepatocarcinogens. These results indicate that the expression profiles of our newly selected candidate biomarker genes might be common characteristics in the early stage of carcinogenesis for both genotoxic and non-genotoxic carcinogens in the rat liver. Our toxicogenomic model might be useful for the prospective screening of hepatocarcinogenicity of compounds and prioritization of compounds for carcinogenicity testing. - Highlights: >We developed a toxicogenomic model to predict hepatocarcinogenicity of chemicals. >The optimized model consisting of 9 probes had 99% sensitivity and 97% specificity. >This model enables us to detect genotoxic as well as non-genotoxic hepatocarcinogens.« less

A predicted protein interactome identifies conserved global networks and disease resistance subnetworks in maize

USDA-ARS?s Scientific Manuscript database

An interactome is the genome-wide roadmap of protein-protein interactions that occur within an organism. Interactomes for humans, the fruit fly, and now plants such as Arabidopsis thaliana and Oryza sativa have been generated using high throughput experimental methods. It is possible to use these ...

Centrality in the host-pathogen interactome is associated with pathogen fitness during infection.

PubMed

Crua Asensio, Núria; Muñoz Giner, Elisabet; de Groot, Natalia Sánchez; Torrent Burgas, Marc

2017-01-16

To perform their functions proteins must interact with each other, but how these interactions influence bacterial infection remains elusive. Here we demonstrate that connectivity in the host-pathogen interactome is directly related to pathogen fitness during infection. Using Y. pestis as a model organism, we show that the centrality-lethality rule holds for pathogen fitness during infection but only when the host-pathogen interactome is considered. Our results suggest that the importance of pathogen proteins during infection is directly related to their number of interactions with the host. We also show that pathogen proteins causing an extensive rewiring of the host interactome have a higher impact in pathogen fitness during infection. Hence, we conclude that hubs in the host-pathogen interactome should be explored as promising targets for antimicrobial drug design.

Emerging role of the Jun N-terminal kinase interactome in human health.

PubMed

Guo, Xiao-Xi; An, Su; Yang, Yang; Liu, Ying; Hao, Qian; Tang, Tao; Xu, Tian-Rui

2018-02-08

The c-Jun N-terminal kinases (JNKs) are located downstream of Ras-mitogen activated protein kinase signaling cascades. More than 20 years of study has shown that JNKs control cell fate and many cellular functions. JNKs and their interacting proteins form a complicated network with diverse biological functions and physiological effects. Members of the JNK interactome include Jun, amyloid precursor protein, and insulin receptor substrate. Recent studies have shown that the JNK interactome is involved in tumorigenesis, neuron development, and insulin resistance. In this review, we summarize the features of the JNK interactome and classify its members into three groups: upstream regulators, downstream effectors, and scaffold partners. We also highlight the unique cellular signaling mechanisms of JNKs and provide more insights into the roles of the JNK interactome in human diseases. © 2018 International Federation for Cell Biology.

Centrality in the host-pathogen interactome is associated with pathogen fitness during infection

NASA Astrophysics Data System (ADS)

Crua Asensio, Núria; Muñoz Giner, Elisabet; de Groot, Natalia Sánchez; Torrent Burgas, Marc

2017-01-01

To perform their functions proteins must interact with each other, but how these interactions influence bacterial infection remains elusive. Here we demonstrate that connectivity in the host-pathogen interactome is directly related to pathogen fitness during infection. Using Y. pestis as a model organism, we show that the centrality-lethality rule holds for pathogen fitness during infection but only when the host-pathogen interactome is considered. Our results suggest that the importance of pathogen proteins during infection is directly related to their number of interactions with the host. We also show that pathogen proteins causing an extensive rewiring of the host interactome have a higher impact in pathogen fitness during infection. Hence, we conclude that hubs in the host-pathogen interactome should be explored as promising targets for antimicrobial drug design.

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

PubMed

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

2012-07-01

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

Heat Shock Partially Dissociates the Overlapping Modules of the Yeast Protein-Protein Interaction Network: A Systems Level Model of Adaptation

PubMed Central

Mihalik, Ágoston; Csermely, Peter

2011-01-01

Network analysis became a powerful tool giving new insights to the understanding of cellular behavior. Heat shock, the archetype of stress responses, is a well-characterized and simple model of cellular dynamics. S. cerevisiae is an appropriate model organism, since both its protein-protein interaction network (interactome) and stress response at the gene expression level have been well characterized. However, the analysis of the reorganization of the yeast interactome during stress has not been investigated yet. We calculated the changes of the interaction-weights of the yeast interactome from the changes of mRNA expression levels upon heat shock. The major finding of our study is that heat shock induced a significant decrease in both the overlaps and connections of yeast interactome modules. In agreement with this the weighted diameter of the yeast interactome had a 4.9-fold increase in heat shock. Several key proteins of the heat shock response became centers of heat shock-induced local communities, as well as bridges providing a residual connection of modules after heat shock. The observed changes resemble to a ‘stratus-cumulus’ type transition of the interactome structure, since the unstressed yeast interactome had a globally connected organization, similar to that of stratus clouds, whereas the heat shocked interactome had a multifocal organization, similar to that of cumulus clouds. Our results showed that heat shock induces a partial disintegration of the global organization of the yeast interactome. This change may be rather general occurring in many types of stresses. Moreover, other complex systems, such as single proteins, social networks and ecosystems may also decrease their inter-modular links, thus develop more compact modules, and display a partial disintegration of their global structure in the initial phase of crisis. Thus, our work may provide a model of a general, system-level adaptation mechanism to environmental changes. PMID:22022244

The protein interactome of collapsin response mediator protein-2 (CRMP2/DPYSL2) reveals novel partner proteins in brain tissue.

PubMed

Martins-de-Souza, Daniel; Cassoli, Juliana S; Nascimento, Juliana M; Hensley, Kenneth; Guest, Paul C; Pinzon-Velasco, Andres M; Turck, Christoph W

2015-10-01

Collapsin response mediator protein-2 (CRMP2) is a CNS protein involved in neuronal development, axonal and neuronal growth, cell migration, and protein trafficking. Recent studies have linked perturbations in CRMP2 function to neurodegenerative disorders such as Alzheimer's disease, neuropathic pain, and Batten disease, and to psychiatric disorders such as schizophrenia. Like most proteins, CRMP2 functions though interactions with a molecular network of proteins and other molecules. Here, we have attempted to identify additional proteins of the CRMP2 interactome to provide further leads about its roles in neurological functions. We used a combined co-immunoprecipitation and shotgun proteomic approach in order to identify CRMP2 protein partners. We identified 78 CRMP2 protein partners not previously reported in public protein interaction databases. These were involved in seven biological processes, which included cell signaling, growth, metabolism, trafficking, and immune function, according to Gene Ontology classifications. Furthermore, 32 different molecular functions were found to be associated with these proteins, such as RNA binding, ribosomal functions, transporter activity, receptor activity, serine/threonine phosphatase activity, cell adhesion, cytoskeletal protein binding and catalytic activity. In silico pathway interactome construction revealed a highly connected network with the most overrepresented functions corresponding to semaphorin interactions, along with axon guidance and WNT5A signaling. Taken together, these findings suggest that the CRMP2 pathway is critical for regulating neuronal and synaptic architecture. Further studies along these lines might uncover novel biomarkers and drug targets for use in drug discovery. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Systematic Differences in Signal Emitting and Receiving Revealed by PageRank Analysis of a Human Protein Interactome

PubMed Central

Li, Xiu-Qing

2012-01-01

Most protein PageRank studies do not use signal flow direction information in protein interactions because this information was not readily available in large protein databases until recently. Therefore, four questions have yet to be answered: A) What is the general difference between signal emitting and receiving in a protein interactome? B) Which proteins are among the top ranked in directional ranking? C) Are high ranked proteins more evolutionarily conserved than low ranked ones? D) Do proteins with similar ranking tend to have similar subcellular locations? In this study, we address these questions using the forward, reverse, and non-directional PageRank approaches to rank an information-directional network of human proteins and study their evolutionary conservation. The forward ranking gives credit to information receivers, reverse ranking to information emitters, and non-directional ranking mainly to the number of interactions. The protein lists generated by the forward and non-directional rankings are highly correlated, but those by the reverse and non-directional rankings are not. The results suggest that the signal emitting/receiving system is characterized by key-emittings and relatively even receivings in the human protein interactome. Signaling pathway proteins are frequent in top ranked ones. Eight proteins are both informational top emitters and top receivers. Top ranked proteins, except a few species-related novel-function ones, are evolutionarily well conserved. Protein-subunit ranking position reflects subunit function. These results demonstrate the usefulness of different PageRank approaches in characterizing protein networks and provide insights to protein interaction in the cell. PMID:23028653

Columbia University: Computational Human High-grade Glioblastoma Multiforme Interactome - miRNA (Post-transcriptional) Layer | Office of Cancer Genomics

Cancer.gov

The Human High-Grade Glioma Interactome (HGi) contains a genome-wide complement of molecular interactions that are Glioblastoma Multiforme (GBM)-specific. HGi v3 contains the post-transcriptional layer of the HGi, which includes the miRNA-target (RNA-RNA) layer of the interactome. Read the Abstract

The Topology of the Growing Human Interactome Data.

PubMed

Janjić, Vuk; Pržulj, Nataša

2014-06-01

We have long moved past the one-gene-one-function concept originally proposed by Beadle and Tatum back in 1941; but the full understanding of genotype-phenotype relations still largely relies on the analysis of static, snapshot-like, interaction data sets. Here, we look at what global patterns can be uncovered if we simply trace back the human interactome network over the last decade of protein-protein interaction (PPI) screening. We take a purely topological approach and find that as the human interactome is getting denser, it is not only gaining in structure (in terms of now being better fit by structured network models than before), but also there are patterns in the way in which it is growing: (a) newly added proteins tend to get linked to existing proteins in the interactome that are not know to interact; and (b) new proteins tend to link to already well connected proteins. Moreover, the alignment between human and yeast interactomes spanning over 40% of yeast's proteins - that are involved in regulation of transcription, RNA splicing and other cellcycle- related processes-suggests the existence of a part of the interactome which remains topologically and functionally unaffected through evolution. Furthermore, we find a small sub-network, specific to the "core" of the human interactome and involved in regulation of transcription and cancer development, whose wiring has not changed within the human interactome over the last 10 years of interacome data acquisition. Finally, we introduce a generalisation of the clustering coefficient of a network as a new measure called the cycle coefficient, and use it to show that PPI networks of human and model organisms are wired in a tight way which forbids the occurrence large cycles.

The topology of the growing human interactome data.

PubMed

Janjić, Vuk; Pržulj, Nataša

2014-06-23

We have long moved past the one-gene–one-function concept originally proposed by Beadle and Tatum back in 1941; but the full understanding of genotype–phenotype relations still largely relies on the analysis of static, snapshot-like, interaction data sets. Here, we look at what global patterns can be uncovered if we simply trace back the human interactome network over the last decade of protein- protein interaction (PPI) screening. We take a purely topological approach and find that as the human interactome is getting denser, it is not only gaining in structure (in terms of now being better fit by structured network models than before), but also there are patterns in the way in which it is growing: (a) newly added proteins tend to get linked to existing proteins in the interactome that are not know to interact; and (b) new proteins tend to link to already well connected proteins. Moreover, the alignment between human and yeast interactomes spanning over 40% of yeast’s proteins — that are involved in regulation of transcription, RNA splicing and other cellcycle-related processes—suggests the existence of a part of the interactome which remains topologically and functionally unaffected through evolution. Furthermore, we find a small sub-network, specific to the “core” of the human interactome and involved in regulation of transcription and cancer development, whose wiring has not changed within the human interactome over the last 10 years of interacome data acquisition. Finally, we introduce a generalisation of the clustering coefficient of a network as a new measure called the cycle coefficient, and use it to show that PPI networks of human and model organisms are wired in a tight way which forbids the occurrence large cycles.

The Protein Interactome of Streptococcus pneumoniae and Bacterial Meta-interactomes Improve Function Predictions.

PubMed

Wuchty, S; Rajagopala, S V; Blazie, S M; Parrish, J R; Khuri, S; Finley, R L; Uetz, P

2017-01-01

The functions of roughly a third of all proteins in Streptococcus pneumoniae , a significant human-pathogenic bacterium, are unknown. Using a yeast two-hybrid approach, we have determined more than 2,000 novel protein interactions in this organism. We augmented this network with meta-interactome data that we defined as the pool of all interactions between evolutionarily conserved proteins in other bacteria. We found that such interactions significantly improved our ability to predict a protein's function, allowing us to provide functional predictions for 299 S. pneumoniae proteins with previously unknown functions. IMPORTANCE Identification of protein interactions in bacterial species can help define the individual roles that proteins play in cellular pathways and pathogenesis. Very few protein interactions have been identified for the important human pathogen S. pneumoniae . We used an experimental approach to identify over 2,000 new protein interactions for S. pneumoniae , the most extensive interactome data for this bacterium to date. To predict protein function, we used our interactome data augmented with interactions from other closely related bacteria. The combination of the experimental data and meta-interactome data significantly improved the prediction results, allowing us to assign possible functions to a large number of poorly characterized proteins.

"Fuzziness" in the celular interactome: a historical perspective.

PubMed

Welch, G Rickey

2012-01-01

Some historical background is given for appreciating the impact of the empirical construct known as the cellular protein-protein interactome, which is a seemingly de novo entity that has arisen of late within the context of postgenomic systems biology. The approach here builds on a generalized principle of "fuzziness" in protein behavior, proposed by Tompa and Fuxreiter.(1) Recent controversies in the analysis and interpretation of the interactome studies are rationalized historically under the auspices of this concept. There is an extensive literature on protein-protein interactions, dating to the mid-1900s, which may help clarify the "fuzziness" in the interactome picture and, also, provide a basis for understanding the physiological importance of protein-protein interactions in vivo.

Towards Establishment of a Rice Stress Response Interactome

PubMed Central

Seo, Young-Su; Chern, Mawsheng; Bartley, Laura E.; Han, Muho; Jung, Ki-Hong; Lee, Insuk; Walia, Harkamal; Richter, Todd; Xu, Xia; Cao, Peijian; Bai, Wei; Ramanan, Rajeshwari; Amonpant, Fawn; Arul, Loganathan; Canlas, Patrick E.; Ruan, Randy; Park, Chang-Jin; Chen, Xuewei; Hwang, Sohyun; Jeon, Jong-Seong; Ronald, Pamela C.

2011-01-01

Rice (Oryza sativa) is a staple food for more than half the world and a model for studies of monocotyledonous species, which include cereal crops and candidate bioenergy grasses. A major limitation of crop production is imposed by a suite of abiotic and biotic stresses resulting in 30%–60% yield losses globally each year. To elucidate stress response signaling networks, we constructed an interactome of 100 proteins by yeast two-hybrid (Y2H) assays around key regulators of the rice biotic and abiotic stress responses. We validated the interactome using protein–protein interaction (PPI) assays, co-expression of transcripts, and phenotypic analyses. Using this interactome-guided prediction and phenotype validation, we identified ten novel regulators of stress tolerance, including two from protein classes not previously known to function in stress responses. Several lines of evidence support cross-talk between biotic and abiotic stress responses. The combination of focused interactome and systems analyses described here represents significant progress toward elucidating the molecular basis of traits of agronomic importance. PMID:21533176

Interactome of E. piscicida and grouper liver proteins reveals strategies of bacterial infection and host immune response.

PubMed

Li, Hui; Zhu, Qing-Feng; Peng, Xuan-Xian; Peng, Bo

2017-01-03

The occurrence of infectious diseases is related to heterogeneous protein interactions between a host and a microbe. Therefore, elucidating the host-pathogen interplay is essential. We previously revealed the protein interactome between Edwardsiella piscicida and fish gill cells, and the present study identified the protein interactome between E. piscicida and E. drummondhayi liver cells. E. drummondhayi liver cells and bacterial pull-down approaches were used to identify E. piscicida outer membrane proteins that bind to liver cells and fish liver cell proteins that interact with bacterial cells, respectively. Eight bacterial proteins and 11 fish proteins were characterized. Heterogeneous protein-protein interactions between these bacterial cells and fish liver cells were investigated through far-Western blotting and co-immunoprecipitation. A network was constructed based on 42 heterogeneous protein-protein interactions between seven bacterial proteins and 10 fish proteins. A comparison of the new interactome with the previously reported interactome showed that four bacterial proteins overlapped, whereas all of the identified fish proteins were new, suggesting a difference between bacterial tricks for evading host immunity and the host strategy for combating bacterial infection. Furthermore, these bacterial proteins were found to regulate the expression of host innate immune-related proteins. These findings indicate that the interactome contributes to bacterial infection and host immunity.

The Protein Interactome of Streptococcus pneumoniae and Bacterial Meta-interactomes Improve Function Predictions

PubMed Central

Rajagopala, S. V.; Blazie, S. M.; Parrish, J. R.; Khuri, S.; Finley, R. L.

2017-01-01

ABSTRACT The functions of roughly a third of all proteins in Streptococcus pneumoniae, a significant human-pathogenic bacterium, are unknown. Using a yeast two-hybrid approach, we have determined more than 2,000 novel protein interactions in this organism. We augmented this network with meta-interactome data that we defined as the pool of all interactions between evolutionarily conserved proteins in other bacteria. We found that such interactions significantly improved our ability to predict a protein’s function, allowing us to provide functional predictions for 299 S. pneumoniae proteins with previously unknown functions. IMPORTANCE Identification of protein interactions in bacterial species can help define the individual roles that proteins play in cellular pathways and pathogenesis. Very few protein interactions have been identified for the important human pathogen S. pneumoniae. We used an experimental approach to identify over 2,000 new protein interactions for S. pneumoniae, the most extensive interactome data for this bacterium to date. To predict protein function, we used our interactome data augmented with interactions from other closely related bacteria. The combination of the experimental data and meta-interactome data significantly improved the prediction results, allowing us to assign possible functions to a large number of poorly characterized proteins. PMID:28744484

iRefWeb: interactive analysis of consolidated protein interaction data and their supporting evidence

PubMed Central

Turner, Brian; Razick, Sabry; Turinsky, Andrei L.; Vlasblom, James; Crowdy, Edgard K.; Cho, Emerson; Morrison, Kyle; Wodak, Shoshana J.

2010-01-01

We present iRefWeb, a web interface to protein interaction data consolidated from 10 public databases: BIND, BioGRID, CORUM, DIP, IntAct, HPRD, MINT, MPact, MPPI and OPHID. iRefWeb enables users to examine aggregated interactions for a protein of interest, and presents various statistical summaries of the data across databases, such as the number of organism-specific interactions, proteins and cited publications. Through links to source databases and supporting evidence, researchers may gauge the reliability of an interaction using simple criteria, such as the detection methods, the scale of the study (high- or low-throughput) or the number of cited publications. Furthermore, iRefWeb compares the information extracted from the same publication by different databases, and offers means to follow-up possible inconsistencies. We provide an overview of the consolidated protein–protein interaction landscape and show how it can be automatically cropped to aid the generation of meaningful organism-specific interactomes. iRefWeb can be accessed at: http://wodaklab.org/iRefWeb. Database URL: http://wodaklab.org/iRefWeb/ PMID:20940177

Elucidation of the 14-3-3ζ interactome reveals critical roles of RNA-splicing factors during adipogenesis.

PubMed

Mugabo, Yves; Sadeghi, Mina; Fang, Nancy N; Mayor, Thibault; Lim, Gareth E

2018-05-04

Adipogenesis involves a complex signaling network requiring strict temporal and spatial organization of effector molecules. Molecular scaffolds, such as 14-3-3 proteins, facilitate such organization, and we have previously identified 14-3-3ζ as an essential scaffold in adipocyte differentiation. The interactome of 14-3-3ζ is large and diverse, and it is possible that novel adipogenic factors may be present within it, but this possibility has not yet been tested. Herein, we generated mouse embryonic fibroblasts from mice overexpressing a tandem affinity purification (TAP) epitope-tagged 14-3-3ζ molecule. After inducing adipogenesis, TAP-14-3-3ζ complexes were purified, followed by MS analysis to determine the 14-3-3ζ interactome. We observed more than 100 proteins that were unique to adipocyte differentiation, 56 of which were novel interacting partners. Among these, we were able to identify previously established regulators of adipogenesis ( i.e. Ptrf/Cavin1) within the 14-3-3ζ interactome, confirming the utility of this approach to detect adipogenic factors. We found that proteins related to RNA metabolism, processing, and splicing were enriched in the interactome. Analysis of transcriptomic data revealed that 14-3-3ζ depletion in 3T3-L1 cells affected alternative splicing of mRNA during adipocyte differentiation. siRNA-mediated depletion of RNA-splicing factors within the 14-3-3ζ interactome, that is, of Hnrpf, Hnrpk, Ddx6, and Sfpq, revealed that they have essential roles in adipogenesis and in the alternative splicing of Pparg and the adipogenesis-associated gene Lpin1 In summary, we have identified novel adipogenic factors within the 14-3-3ζ interactome. Further characterization of additional proteins within the 14-3-3ζ interactome may help identify novel targets to block obesity-associated expansion of adipose tissues. © 2018 by The American Society for Biochemistry and Molecular Biology, Inc.

Quantitative Tagless Copurification: A Method to Validate and Identify Protein-Protein Interactions

DOE PAGES

Shatsky, Maxim; Dong, Ming; Liu, Haichuan; ...

2016-04-20

Identifying protein-protein interactions (PPIs) at an acceptable false discovery rate (FDR) is challenging. Previously we identified several hundred PPIs from affinity purification - mass spectrometry (AP-MS) data for the bacteria Escherichia coli and Desulfovibrio vulgaris. These two interactomes have lower FDRs than any of the nine interactomes proposed previously for bacteria and are more enriched in PPIs validated by other data than the nine earlier interactomes. To more thoroughly determine the accuracy of ours or other interactomes and to discover further PPIs de novo, here we present a quantitative tagless method that employs iTRAQ MS to measure the copurification ofmore » endogenous proteins through orthogonal chromatography steps. 5273 fractions from a four-step fractionation of a D. vulgaris protein extract were assayed, resulting in the detection of 1242 proteins. Protein partners from our D. vulgaris and E. coli AP-MS interactomes copurify as frequently as pairs belonging to three benchmark data sets of well-characterized PPIs. In contrast, the protein pairs from the nine other bacterial interactomes copurify two- to 20-fold less often. We also identify 200 high confidence D. vulgaris PPIs based on tagless copurification and colocalization in the genome. These PPIs are as strongly validated by other data as our AP-MS interactomes and overlap with our AP-MS interactome for D.vulgaris within 3% of expectation, once FDRs and false negative rates are taken into account. Finally, we reanalyzed data from two quantitative tagless screens of human cell extracts. We estimate that the novel PPIs reported in these studies have an FDR of at least 85% and find that less than 7% of the novel PPIs identified in each screen overlap. Our results establish that a quantitative tagless method can be used to validate and identify PPIs, but that such data must be analyzed carefully to minimize the FDR.« less

Quantitative Tagless Copurification: A Method to Validate and Identify Protein-Protein Interactions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shatsky, Maxim; Dong, Ming; Liu, Haichuan

Identifying protein-protein interactions (PPIs) at an acceptable false discovery rate (FDR) is challenging. Previously we identified several hundred PPIs from affinity purification - mass spectrometry (AP-MS) data for the bacteria Escherichia coli and Desulfovibrio vulgaris. These two interactomes have lower FDRs than any of the nine interactomes proposed previously for bacteria and are more enriched in PPIs validated by other data than the nine earlier interactomes. To more thoroughly determine the accuracy of ours or other interactomes and to discover further PPIs de novo, here we present a quantitative tagless method that employs iTRAQ MS to measure the copurification ofmore » endogenous proteins through orthogonal chromatography steps. 5273 fractions from a four-step fractionation of a D. vulgaris protein extract were assayed, resulting in the detection of 1242 proteins. Protein partners from our D. vulgaris and E. coli AP-MS interactomes copurify as frequently as pairs belonging to three benchmark data sets of well-characterized PPIs. In contrast, the protein pairs from the nine other bacterial interactomes copurify two- to 20-fold less often. We also identify 200 high confidence D. vulgaris PPIs based on tagless copurification and colocalization in the genome. These PPIs are as strongly validated by other data as our AP-MS interactomes and overlap with our AP-MS interactome for D.vulgaris within 3% of expectation, once FDRs and false negative rates are taken into account. Finally, we reanalyzed data from two quantitative tagless screens of human cell extracts. We estimate that the novel PPIs reported in these studies have an FDR of at least 85% and find that less than 7% of the novel PPIs identified in each screen overlap. Our results establish that a quantitative tagless method can be used to validate and identify PPIs, but that such data must be analyzed carefully to minimize the FDR.« less

A protein domain-based interactome network for C. elegans early embryogenesis

PubMed Central

Boxem, Mike; Maliga, Zoltan; Klitgord, Niels; Li, Na; Lemmens, Irma; Mana, Miyeko; de Lichtervelde, Lorenzo; Mul, Joram D.; van de Peut, Diederik; Devos, Maxime; Simonis, Nicolas; Yildirim, Muhammed A.; Cokol, Murat; Kao, Huey-Ling; de Smet, Anne-Sophie; Wang, Haidong; Schlaitz, Anne-Lore; Hao, Tong; Milstein, Stuart; Fan, Changyu; Tipsword, Mike; Drew, Kevin; Galli, Matilde; Rhrissorrakrai, Kahn; Drechsel, David; Koller, Daphne; Roth, Frederick P.; Iakoucheva, Lilia M.; Dunker, A. Keith; Bonneau, Richard; Gunsalus, Kristin C.; Hill, David E.; Piano, Fabio; Tavernier, Jan; van den Heuvel, Sander; Hyman, Anthony A.; Vidal, Marc

2008-01-01

Summary Many protein-protein interactions are mediated through independently folding modular domains. Proteome-wide efforts to model protein-protein interaction or “interactome” networks have largely ignored this modular organization of proteins. We developed an experimental strategy to efficiently identify interaction domains and generated a domain-based interactome network for proteins involved in C. elegans early embryonic cell divisions. Minimal interacting regions were identified for over 200 proteins, providing important information on their domain organization. Furthermore, our approach increased the sensitivity of the two-hybrid system, resulting in a more complete interactome network. This interactome modeling strategy revealed new insights into C. elegans centrosome function and is applicable to other biological processes in this and other organisms. PMID:18692475

Photocrosslinking approaches to interactome mapping

PubMed Central

Pham, Nam D.; Parker, Randy B.; Kohler, Jennifer J.

2012-01-01

Photocrosslinking approaches can be used to map interactome networks within the context of living cells. Photocrosslinking methods rely on use of metabolic engineering or genetic code expansion to incorporate photocrosslinking analogs of amino acids or sugars into cellular biomolecules. Immunological and mass spectrometry techniques are used to analyze crosslinked complexes, thereby defining specific interactomes. Because photocrosslinking can be conducted in native, cellular settings, it can be used to define context-dependent interactions. Photocrosslinking methods are also ideally suited for determining interactome dynamics, mapping interaction interfaces, and identifying transient interactions in which intrinsically disordered proteins and glycoproteins engage. Here we discuss the application of cell-based photocrosslinking to the study of specific problems in immune cell signaling, transcription, membrane protein dynamics, nucleocytoplasmic transport, and chaperone-assisted protein folding. PMID:23149092

The Hsp90 co-chaperone p23 of Toxoplasma gondii: Identification, functional analysis and dynamic interactome determination

PubMed Central

Echeverria, Pablo C.; Figueras, Maria J.; Vogler, Malvina; Kriehuber, Thomas; de Miguel, Natalia; Deng, Bin; Dalmasso, Maria C.; Matthews, Dwight E.; Matrajt, Mariana; Haslbeck, Martin; Buchner, Johannes; Angel, Sergio O.

2010-01-01

Toxoplasma gondii is among the most successful parasites, with nearly half of the human population chronically infected. Recently a link between the T. gondii Hsp90 chaperone machinery and parasite development was observed. Here, the T. gondii Hsp90 co-chaperones p23 and Hip were identified mining the Toxoplasma- database (www.toxodb.org). Their identity was confirmed by domain structure and blast analysis. Additionally, analysis of the secondary structure and studies on the chaperone function of the purified protein verified the p23 identity. Studies of co-immunoprecipitation (co-IP) identified two different types of complexes, one comprising at least Hip-Hsp70-Hsp90 and another containing at least p23-Hsp90. Indirect immunofluorescence assays showed that Hip is localized in the cytoplasm in tachyzoites and as well in bradyzoites. For p23 in contrast, a solely cytoplasmic localization was only observed in the tachyzoite stage whereas nuclear and cytosolic distribution and colocalization with Hsp90 was observed in bradyzoites. These results indicate that the T. gondii Hsp90-heterocomplex cycle is similar to the one proposed for higher eukaryotes, further highlighting the implication of the Hsp90/p23 in parasite development. Furthermore, co-IP experiments of tachyzoite/bradyzoite lysates with anti-p23 antiserum and identification of the complexed proteins together with the use of the curated interaction data available from different source (orthologs and Plasmodium databases) allowed us to construct an interaction network (interactome) covering the dynamics of the Hsp90 chaperone machinery. PMID:20403389

The distinctive cell division interactome of Neisseria gonorrhoeae.

PubMed

Zou, Yinan; Li, Yan; Dillon, Jo-Anne R

2017-12-12

Bacterial cell division is an essential process driven by the formation of a Z-ring structure, as a cytoskeletal scaffold at the mid-cell, followed by the recruitment of various proteins which form the divisome. The cell division interactome reflects the complement of different interactions between all divisome proteins. To date, only two cell division interactomes have been characterized, in Escherichia coli and in Streptococcus pneumoniae. The cell divison proteins encoded by Neisseria gonorrhoeae include FtsZ, FtsA, ZipA, FtsK, FtsQ, FtsI, FtsW, and FtsN. The purpose of the present study was to characterize the cell division interactome of N. gonorrhoeae using several different methods to identify protein-protein interactions. We also characterized the specific subdomains of FtsA implicated in interactions with FtsZ, FtsQ, FtsN and FtsW. Using a combination of bacterial two-hybrid (B2H), glutathione S-transferase (GST) pull-down assays, and surface plasmon resonance (SPR), nine interactions were observed among the eight gonococcal cell division proteins tested. ZipA did not interact with any other cell division proteins. Comparisons of the N. gonorrhoeae cell division interactome with the published interactomes from E. coli and S. pneumoniae indicated that FtsA-FtsZ and FtsZ-FtsK interactions were common to all three species. FtsA-FtsW and FtsK-FtsN interactions were only present in N. gonorrhoeae. The 2A and 2B subdomains of FtsA Ng were involved in interactions with FtsQ, FtsZ, and FtsN, and the 2A subdomain was involved in interaction with FtsW. Results from this research indicate that N. gonorrhoeae has a distinctive cell division interactome as compared with other microorganisms.

A convex optimization approach for identification of human tissue-specific interactomes.

PubMed

Mohammadi, Shahin; Grama, Ananth

2016-06-15

Analysis of organism-specific interactomes has yielded novel insights into cellular function and coordination, understanding of pathology, and identification of markers and drug targets. Genes, however, can exhibit varying levels of cell type specificity in their expression, and their coordinated expression manifests in tissue-specific function and pathology. Tissue-specific/tissue-selective interaction mechanisms have significant applications in drug discovery, as they are more likely to reveal drug targets. Furthermore, tissue-specific transcription factors (tsTFs) are significantly implicated in human disease, including cancers. Finally, disease genes and protein complexes have the tendency to be differentially expressed in tissues in which defects cause pathology. These observations motivate the construction of refined tissue-specific interactomes from organism-specific interactomes. We present a novel technique for constructing human tissue-specific interactomes. Using a variety of validation tests (Edge Set Enrichment Analysis, Gene Ontology Enrichment, Disease-Gene Subnetwork Compactness), we show that our proposed approach significantly outperforms state-of-the-art techniques. Finally, using case studies of Alzheimer's and Parkinson's diseases, we show that tissue-specific interactomes derived from our study can be used to construct pathways implicated in pathology and demonstrate the use of these pathways in identifying novel targets. http://www.cs.purdue.edu/homes/mohammas/projects/ActPro.html mohammadi@purdue.edu. © The Author 2016. Published by Oxford University Press.

A Rich-Club Organization in Brain Ischemia Protein Interaction Network

PubMed Central

Alawieh, Ali; Sabra, Zahraa; Sabra, Mohammed; Tomlinson, Stephen; Zaraket, Fadi A.

2015-01-01

Ischemic stroke involves multiple pathophysiological mechanisms with complex interactions. Efforts to decipher those mechanisms and understand the evolution of cerebral injury is key for developing successful interventions. In an innovative approach, we use literature mining, natural language processing and systems biology tools to construct, annotate and curate a brain ischemia interactome. The curated interactome includes proteins that are deregulated after cerebral ischemia in human and experimental stroke. Network analysis of the interactome revealed a rich-club organization indicating the presence of a densely interconnected hub structure of prominent contributors to disease pathogenesis. Functional annotation of the interactome uncovered prominent pathways and highlighted the critical role of the complement and coagulation cascade in the initiation and amplification of injury starting by activation of the rich-club. We performed an in-silico screen for putative interventions that have pleiotropic effects on rich-club components and we identified estrogen as a prominent candidate. Our findings show that complex network analysis of disease related interactomes may lead to a better understanding of pathogenic mechanisms and provide cost-effective and mechanism-based discovery of candidate therapeutics. PMID:26310627

RNA-Binding Proteins Revisited - The Emerging Arabidopsis mRNA Interactome.

PubMed

Köster, Tino; Marondedze, Claudius; Meyer, Katja; Staiger, Dorothee

2017-06-01

RNA-protein interaction is an important checkpoint to tune gene expression at the RNA level. Global identification of proteins binding in vivo to mRNA has been possible through interactome capture - where proteins are fixed to target RNAs by UV crosslinking and purified through affinity capture of polyadenylated RNA. In Arabidopsis over 500 RNA-binding proteins (RBPs) enriched in UV-crosslinked samples have been identified. As in mammals and yeast, the mRNA interactomes came with a few surprises. For example, a plethora of the proteins caught on RNA had not previously been linked to RNA-mediated processes, for example proteins of intermediary metabolism. Thus, the studies provide unprecedented insights into the composition of the mRNA interactome, highlighting the complexity of RNA-mediated processes. Copyright © 2017 Elsevier Ltd. All rights reserved.

Exosomes and Homeostatic Synaptic Plasticity Are Linked to Each other and to Huntington's, Parkinson's, and Other Neurodegenerative Diseases by Database-Enabled Analyses of Comprehensively Curated Datasets

PubMed Central

Wang, James K. T.; Langfelder, Peter; Horvath, Steve; Palazzolo, Michael J.

2017-01-01

Huntington's disease (HD) is a progressive and autosomal dominant neurodegeneration caused by CAG expansion in the huntingtin gene (HTT), but the pathophysiological mechanism of mutant HTT (mHTT) remains unclear. To study HD using systems biological methodologies on all published data, we undertook the first comprehensive curation of two key PubMed HD datasets: perturbation genes that impact mHTT-driven endpoints and therefore are putatively linked causally to pathogenic mechanisms, and the protein interactome of HTT that reflects its biology. We perused PubMed articles containing co-citation of gene IDs and MeSH terms of interest to generate mechanistic gene sets for iterative enrichment analyses and rank ordering. The HD Perturbation database of 1,218 genes highly overlaps the HTT Interactome of 1,619 genes, suggesting links between normal HTT biology and mHTT pathology. These two HD datasets are enriched for protein networks of key genes underlying two mechanisms not previously implicated in HD nor in each other: exosome synaptic functions and homeostatic synaptic plasticity. Moreover, proteins, possibly including HTT, and miRNA detected in exosomes from a wide variety of sources also highly overlap the HD datasets, suggesting both mechanistic and biomarker links. Finally, the HTT Interactome highly intersects protein networks of pathogenic genes underlying Parkinson's, Alzheimer's and eight non-HD polyglutamine diseases, ALS, and spinal muscular atrophy. These protein networks in turn highly overlap the exosome and homeostatic synaptic plasticity gene sets. Thus, we hypothesize that HTT and other neurodegeneration pathogenic genes form a large interlocking protein network involved in exosome and homeostatic synaptic functions, particularly where the two mechanisms intersect. Mutant pathogenic proteins cause dysfunctions at distinct points in this network, each altering the two mechanisms in specific fashion that contributes to distinct disease pathologies, depending on the gene mutation and the cellular and biological context. This protein network is rich with drug targets, and exosomes may provide disease biomarkers, thus enabling drug discovery. All the curated datasets are made available for other investigators. Elucidating the roles of pathogenic neurodegeneration genes in exosome and homeostatic synaptic functions may provide a unifying framework for the age-dependent, progressive and tissue selective nature of multiple neurodegenerative diseases. PMID:28611571

Exosomes and Homeostatic Synaptic Plasticity Are Linked to Each other and to Huntington's, Parkinson's, and Other Neurodegenerative Diseases by Database-Enabled Analyses of Comprehensively Curated Datasets.

PubMed

Wang, James K T; Langfelder, Peter; Horvath, Steve; Palazzolo, Michael J

2017-01-01

Huntington's disease (HD) is a progressive and autosomal dominant neurodegeneration caused by CAG expansion in the huntingtin gene ( HTT ), but the pathophysiological mechanism of mutant HTT (mHTT) remains unclear. To study HD using systems biological methodologies on all published data, we undertook the first comprehensive curation of two key PubMed HD datasets: perturbation genes that impact mHTT-driven endpoints and therefore are putatively linked causally to pathogenic mechanisms, and the protein interactome of HTT that reflects its biology. We perused PubMed articles containing co-citation of gene IDs and MeSH terms of interest to generate mechanistic gene sets for iterative enrichment analyses and rank ordering. The HD Perturbation database of 1,218 genes highly overlaps the HTT Interactome of 1,619 genes, suggesting links between normal HTT biology and mHTT pathology. These two HD datasets are enriched for protein networks of key genes underlying two mechanisms not previously implicated in HD nor in each other: exosome synaptic functions and homeostatic synaptic plasticity. Moreover, proteins, possibly including HTT, and miRNA detected in exosomes from a wide variety of sources also highly overlap the HD datasets, suggesting both mechanistic and biomarker links. Finally, the HTT Interactome highly intersects protein networks of pathogenic genes underlying Parkinson's, Alzheimer's and eight non-HD polyglutamine diseases, ALS, and spinal muscular atrophy. These protein networks in turn highly overlap the exosome and homeostatic synaptic plasticity gene sets. Thus, we hypothesize that HTT and other neurodegeneration pathogenic genes form a large interlocking protein network involved in exosome and homeostatic synaptic functions, particularly where the two mechanisms intersect. Mutant pathogenic proteins cause dysfunctions at distinct points in this network, each altering the two mechanisms in specific fashion that contributes to distinct disease pathologies, depending on the gene mutation and the cellular and biological context. This protein network is rich with drug targets, and exosomes may provide disease biomarkers, thus enabling drug discovery. All the curated datasets are made available for other investigators. Elucidating the roles of pathogenic neurodegeneration genes in exosome and homeostatic synaptic functions may provide a unifying framework for the age-dependent, progressive and tissue selective nature of multiple neurodegenerative diseases.

Photoreactive Stapled BH3 Peptides to Dissect the BCL-2 Family Interactome

PubMed Central

Braun, Craig R.; Mintseris, Julian; Gavathiotis, Evripidis; Bird, Gregory H.; Gygi, Steven P.; Walensky, Loren D.

2010-01-01

SUMMARY Defining protein interactions forms the basis for discovery of biological pathways, disease mechanisms, and opportunities for therapeutic intervention. To harness the robust binding affinity and selectivity of structured peptides for interactome discovery, we engineered photoreactive stapled BH3 peptide helices that covalently capture their physiologic BCL-2 family targets. The crosslinking α-helices covalently trap both static and dynamic protein interactors, and enable rapid identification of interaction sites, providing a critical link between interactome discovery and targeted drug design. PMID:21168768

A proteome-scale map of the human interactome network

PubMed Central

Rolland, Thomas; Taşan, Murat; Charloteaux, Benoit; Pevzner, Samuel J.; Zhong, Quan; Sahni, Nidhi; Yi, Song; Lemmens, Irma; Fontanillo, Celia; Mosca, Roberto; Kamburov, Atanas; Ghiassian, Susan D.; Yang, Xinping; Ghamsari, Lila; Balcha, Dawit; Begg, Bridget E.; Braun, Pascal; Brehme, Marc; Broly, Martin P.; Carvunis, Anne-Ruxandra; Convery-Zupan, Dan; Corominas, Roser; Coulombe-Huntington, Jasmin; Dann, Elizabeth; Dreze, Matija; Dricot, Amélie; Fan, Changyu; Franzosa, Eric; Gebreab, Fana; Gutierrez, Bryan J.; Hardy, Madeleine F.; Jin, Mike; Kang, Shuli; Kiros, Ruth; Lin, Guan Ning; Luck, Katja; MacWilliams, Andrew; Menche, Jörg; Murray, Ryan R.; Palagi, Alexandre; Poulin, Matthew M.; Rambout, Xavier; Rasla, John; Reichert, Patrick; Romero, Viviana; Ruyssinck, Elien; Sahalie, Julie M.; Scholz, Annemarie; Shah, Akash A.; Sharma, Amitabh; Shen, Yun; Spirohn, Kerstin; Tam, Stanley; Tejeda, Alexander O.; Trigg, Shelly A.; Twizere, Jean-Claude; Vega, Kerwin; Walsh, Jennifer; Cusick, Michael E.; Xia, Yu; Barabási, Albert-László; Iakoucheva, Lilia M.; Aloy, Patrick; De Las Rivas, Javier; Tavernier, Jan; Calderwood, Michael A.; Hill, David E.; Hao, Tong; Roth, Frederick P.; Vidal, Marc

2014-01-01

SUMMARY Just as reference genome sequences revolutionized human genetics, reference maps of interactome networks will be critical to fully understand genotype-phenotype relationships. Here, we describe a systematic map of ~14,000 high-quality human binary protein-protein interactions. At equal quality, this map is ~30% larger than what is available from small-scale studies published in the literature in the last few decades. While currently available information is highly biased and only covers a relatively small portion of the proteome, our systematic map appears strikingly more homogeneous, revealing a “broader” human interactome network than currently appreciated. The map also uncovers significant inter-connectivity between known and candidate cancer gene products, providing unbiased evidence for an expanded functional cancer landscape, while demonstrating how high quality interactome models will help “connect the dots” of the genomic revolution. PMID:25416956

Comparative analysis of protein-protein interactions in the defense response of rice and wheat.

PubMed

Cantu, Dario; Yang, Baoju; Ruan, Randy; Li, Kun; Menzo, Virginia; Fu, Daolin; Chern, Mawsheng; Ronald, Pamela C; Dubcovsky, Jorge

2013-03-12

Despite the importance of wheat as a major staple crop and the negative impact of diseases on its production worldwide, the genetic mechanisms and gene interactions involved in the resistance response in wheat are still poorly understood. The complete sequence of the rice genome has provided an extremely useful parallel road map for genetic and genomics studies in wheat. The recent construction of a defense response interactome in rice has the potential to further enhance the translation of advances in rice to wheat and other grasses. The objective of this study was to determine the degree of conservation in the protein-protein interactions in the rice and wheat defense response interactomes. As entry points we selected proteins that serve as key regulators of the rice defense response: the RAR1/SGT1/HSP90 protein complex, NPR1, XA21, and XB12 (XA21 interacting protein 12). Using available wheat sequence databases and phylogenetic analyses we identified and cloned the wheat orthologs of these four rice proteins, including recently duplicated paralogs, and their known direct interactors and tested 86 binary protein interactions using yeast-two-hybrid (Y2H) assays. All interactions between wheat proteins were further tested using in planta bimolecular fluorescence complementation (BiFC). Eighty three percent of the known rice interactions were confirmed when wheat proteins were tested with rice interactors and 76% were confirmed using wheat protein pairs. All interactions in the RAR1/SGT1/ HSP90, NPR1 and XB12 nodes were confirmed for the identified orthologous wheat proteins, whereas only forty four percent of the interactions were confirmed in the interactome node centered on XA21. We hypothesize that this reduction may be associated with a different sub-functionalization history of the multiple duplications that occurred in this gene family after the divergence of the wheat and rice lineages. The observed high conservation of interactions between proteins that serve as key regulators of the rice defense response suggests that the existing rice interactome can be used to predict interactions in wheat. Such predictions are less reliable for nodes that have undergone a different history of duplications and sub-functionalization in the two lineages.

Integrative Analysis of Brain Region-specific Shank3 Interactomes for Understanding the Heterogeneity of Neuronal Pathophysiology Related to SHANK3 Mutations

PubMed Central

Lee, Yeunkum; Kang, Hyojin; Lee, Bokyoung; Zhang, Yinhua; Kim, Yoonhee; Kim, Shinhyun; Kim, Won-Ki; Han, Kihoon

2017-01-01

Recent molecular genetic studies have identified 100s of risk genes for various neurodevelopmental and neuropsychiatric disorders. As the number of risk genes increases, it is becoming clear that different mutations of a single gene could cause different types of disorders. One of the best examples of such a gene is SHANK3, which encodes a core scaffold protein of the neuronal excitatory post-synapse. Deletions, duplications, and point mutations of SHANK3 are associated with autism spectrum disorders, intellectual disability, schizophrenia, bipolar disorder, and attention deficit hyperactivity disorder. Nevertheless, how the different mutations of SHANK3 can lead to such phenotypic diversity remains largely unknown. In this study, we investigated whether Shank3 could form protein complexes in a brain region-specific manner, which might contribute to the heterogeneity of neuronal pathophysiology caused by SHANK3 mutations. To test this, we generated a medial prefrontal cortex (mPFC) Shank3 in vivo interactome consisting of 211 proteins, and compared this protein list with a Shank3 interactome previously generated from mixed hippocampal and striatal (HP+STR) tissues. Unexpectedly, we found that only 47 proteins (about 20%) were common between the two interactomes, while 164 and 208 proteins were specifically identified in the mPFC and HP+STR interactomes, respectively. Each of the mPFC- and HP+STR-specific Shank3 interactomes represents a highly interconnected network. Upon comparing the brain region-enriched proteomes, we found that the large difference between the mPFC and HP+STR Shank3 interactomes could not be explained by differential protein expression profiles among the brain regions. Importantly, bioinformatic pathway analysis revealed that the representative biological functions of the mPFC- and HP+STR-specific Shank3 interactomes were different, suggesting that these interactors could mediate the brain region-specific functions of Shank3. Meanwhile, the same analysis on the common Shank3 interactors, including Homer and GKAP/SAPAP proteins, suggested that they could mainly function as scaffolding proteins at the post-synaptic density. Lastly, we found that the mPFC- and HP+STR-specific Shank3 interactomes contained a significant number of proteins associated with neurodevelopmental and neuropsychiatric disorders. These results suggest that Shank3 can form protein complexes in a brain region-specific manner, which might contribute to the pathophysiological and phenotypic diversity of disorders related to SHANK3 mutations. PMID:28469556

ARMOUR - A Rice miRNA: mRNA Interaction Resource.

PubMed

Sanan-Mishra, Neeti; Tripathi, Anita; Goswami, Kavita; Shukla, Rohit N; Vasudevan, Madavan; Goswami, Hitesh

2018-01-01

ARMOUR was developed as A Rice miRNA:mRNA interaction resource. This informative and interactive database includes the experimentally validated expression profiles of miRNAs under different developmental and abiotic stress conditions across seven Indian rice cultivars. This comprehensive database covers 689 known and 1664 predicted novel miRNAs and their expression profiles in more than 38 different tissues or conditions along with their predicted/known target transcripts. The understanding of miRNA:mRNA interactome in regulation of functional cellular machinery is supported by the sequence information of the mature and hairpin structures. ARMOUR provides flexibility to users in querying the database using multiple ways like known gene identifiers, gene ontology identifiers, KEGG identifiers and also allows on the fly fold change analysis and sequence search query with inbuilt BLAST algorithm. ARMOUR database provides a cohesive platform for novel and mature miRNAs and their expression in different experimental conditions and allows searching for their interacting mRNA targets, GO annotation and their involvement in various biological pathways. The ARMOUR database includes a provision for adding more experimental data from users, with an aim to develop it as a platform for sharing and comparing experimental data contributed by research groups working on rice.

Next-Generation Technologies for Multiomics Approaches Including Interactome Sequencing

PubMed Central

Ohashi, Hiroyuki; Miyamoto-Sato, Etsuko

2015-01-01

The development of high-speed analytical techniques such as next-generation sequencing and microarrays allows high-throughput analysis of biological information at a low cost. These techniques contribute to medical and bioscience advancements and provide new avenues for scientific research. Here, we outline a variety of new innovative techniques and discuss their use in omics research (e.g., genomics, transcriptomics, metabolomics, proteomics, and interactomics). We also discuss the possible applications of these methods, including an interactome sequencing technology that we developed, in future medical and life science research. PMID:25649523

Disease networks. Uncovering disease-disease relationships through the incomplete interactome.

PubMed

Menche, Jörg; Sharma, Amitabh; Kitsak, Maksim; Ghiassian, Susan Dina; Vidal, Marc; Loscalzo, Joseph; Barabási, Albert-László

2015-02-20

According to the disease module hypothesis, the cellular components associated with a disease segregate in the same neighborhood of the human interactome, the map of biologically relevant molecular interactions. Yet, given the incompleteness of the interactome and the limited knowledge of disease-associated genes, it is not obvious if the available data have sufficient coverage to map out modules associated with each disease. Here we derive mathematical conditions for the identifiability of disease modules and show that the network-based location of each disease module determines its pathobiological relationship to other diseases. For example, diseases with overlapping network modules show significant coexpression patterns, symptom similarity, and comorbidity, whereas diseases residing in separated network neighborhoods are phenotypically distinct. These tools represent an interactome-based platform to predict molecular commonalities between phenotypically related diseases, even if they do not share primary disease genes. Copyright © 2015, American Association for the Advancement of Science.

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

PubMed

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

2016-08-21

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

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

PubMed

Mechelli, Rosella; Umeton, Renato; Policano, Claudia; Annibali, Viviana; Coarelli, Giulia; Ricigliano, Vito A G; Vittori, Danila; Fornasiero, Arianna; Buscarinu, Maria Chiara; Romano, Silvia; Salvetti, Marco; Ristori, Giovanni

2013-01-01

Though difficult, the study of gene-environment interactions in multifactorial diseases is crucial for interpreting the relevance of non-heritable factors and prevents from overlooking genetic associations with small but measurable effects. We propose a "candidate interactome" (i.e. a group of genes whose products are known to physically interact with environmental factors that may be relevant for disease pathogenesis) analysis of genome-wide association data in multiple sclerosis. We looked for statistical enrichment of associations among interactomes that, at the current state of knowledge, may be representative of gene-environment interactions of potential, uncertain or unlikely relevance for multiple sclerosis pathogenesis: Epstein-Barr virus, human immunodeficiency virus, hepatitis B virus, hepatitis C virus, cytomegalovirus, HHV8-Kaposi sarcoma, H1N1-influenza, JC virus, human innate immunity interactome for type I interferon, autoimmune regulator, vitamin D receptor, aryl hydrocarbon receptor and a panel of proteins targeted by 70 innate immune-modulating viral open reading frames from 30 viral species. Interactomes were either obtained from the literature or were manually curated. The P values of all single nucleotide polymorphism mapping to a given interactome were obtained from the last genome-wide association study of the International Multiple Sclerosis Genetics Consortium & the Wellcome Trust Case Control Consortium, 2. The interaction between genotype and Epstein Barr virus emerges as relevant for multiple sclerosis etiology. However, in line with recent data on the coexistence of common and unique strategies used by viruses to perturb the human molecular system, also other viruses have a similar potential, though probably less relevant in epidemiological terms.

Rare disruptive variants in the DISC1 Interactome and Regulome: association with cognitive ability and schizophrenia.

PubMed

Teng, S; Thomson, P A; McCarthy, S; Kramer, M; Muller, S; Lihm, J; Morris, S; Soares, D C; Hennah, W; Harris, S; Camargo, L M; Malkov, V; McIntosh, A M; Millar, J K; Blackwood, D H; Evans, K L; Deary, I J; Porteous, D J; McCombie, W R

2018-05-01

Schizophrenia (SCZ), bipolar disorder (BD) and recurrent major depressive disorder (rMDD) are common psychiatric illnesses. All have been associated with lower cognitive ability, and show evidence of genetic overlap and substantial evidence of pleiotropy with cognitive function and neuroticism. Disrupted in schizophrenia 1 (DISC1) protein directly interacts with a large set of proteins (DISC1 Interactome) that are involved in brain development and signaling. Modulation of DISC1 expression alters the expression of a circumscribed set of genes (DISC1 Regulome) that are also implicated in brain biology and disorder. Here we report targeted sequencing of 59 DISC1 Interactome genes and 154 Regulome genes in 654 psychiatric patients and 889 cognitively-phenotyped control subjects, on whom we previously reported evidence for trait association from complete sequencing of the DISC1 locus. Burden analyses of rare and singleton variants predicted to be damaging were performed for psychiatric disorders, cognitive variables and personality traits. The DISC1 Interactome and Regulome showed differential association across the phenotypes tested. After family-wise error correction across all traits (FWER across ), an increased burden of singleton disruptive variants in the Regulome was associated with SCZ (FWER across P=0.0339). The burden of singleton disruptive variants in the DISC1 Interactome was associated with low cognitive ability at age 11 (FWER across P=0.0043). These results identify altered regulation of schizophrenia candidate genes by DISC1 and its core Interactome as an alternate pathway for schizophrenia risk, consistent with the emerging effects of rare copy number variants associated with intellectual disability.

A highly efficient approach to protein interactome mapping based on collaborative filtering framework.

PubMed

Luo, Xin; You, Zhuhong; Zhou, Mengchu; Li, Shuai; Leung, Hareton; Xia, Yunni; Zhu, Qingsheng

2015-01-09

The comprehensive mapping of protein-protein interactions (PPIs) is highly desired for one to gain deep insights into both fundamental cell biology processes and the pathology of diseases. Finely-set small-scale experiments are not only very expensive but also inefficient to identify numerous interactomes despite their high accuracy. High-throughput screening techniques enable efficient identification of PPIs; yet the desire to further extract useful knowledge from these data leads to the problem of binary interactome mapping. Network topology-based approaches prove to be highly efficient in addressing this problem; however, their performance deteriorates significantly on sparse putative PPI networks. Motivated by the success of collaborative filtering (CF)-based approaches to the problem of personalized-recommendation on large, sparse rating matrices, this work aims at implementing a highly efficient CF-based approach to binary interactome mapping. To achieve this, we first propose a CF framework for it. Under this framework, we model the given data into an interactome weight matrix, where the feature-vectors of involved proteins are extracted. With them, we design the rescaled cosine coefficient to model the inter-neighborhood similarity among involved proteins, for taking the mapping process. Experimental results on three large, sparse datasets demonstrate that the proposed approach outperforms several sophisticated topology-based approaches significantly.

A Highly Efficient Approach to Protein Interactome Mapping Based on Collaborative Filtering Framework

PubMed Central

Luo, Xin; You, Zhuhong; Zhou, Mengchu; Li, Shuai; Leung, Hareton; Xia, Yunni; Zhu, Qingsheng

2015-01-01

The comprehensive mapping of protein-protein interactions (PPIs) is highly desired for one to gain deep insights into both fundamental cell biology processes and the pathology of diseases. Finely-set small-scale experiments are not only very expensive but also inefficient to identify numerous interactomes despite their high accuracy. High-throughput screening techniques enable efficient identification of PPIs; yet the desire to further extract useful knowledge from these data leads to the problem of binary interactome mapping. Network topology-based approaches prove to be highly efficient in addressing this problem; however, their performance deteriorates significantly on sparse putative PPI networks. Motivated by the success of collaborative filtering (CF)-based approaches to the problem of personalized-recommendation on large, sparse rating matrices, this work aims at implementing a highly efficient CF-based approach to binary interactome mapping. To achieve this, we first propose a CF framework for it. Under this framework, we model the given data into an interactome weight matrix, where the feature-vectors of involved proteins are extracted. With them, we design the rescaled cosine coefficient to model the inter-neighborhood similarity among involved proteins, for taking the mapping process. Experimental results on three large, sparse datasets demonstrate that the proposed approach outperforms several sophisticated topology-based approaches significantly. PMID:25572661

The functional interactome of GSTP: A regulatory biomolecular network at the interface with the Nrf2 adaption response to oxidative stress.

PubMed

Bartolini, Desirée; Galli, Francesco

2016-04-15

Glutathione S-transferase P (GSTP), and possibly other members of the subfamily of cytosolic GSTs, are increasingly proposed to have roles far beyond the classical GSH-dependent enzymatic detoxification of electrophilic metabolites and xenobiotics. Emerging evidence suggests that these are essential components of the redox sensing and signaling platform of cells. GSTP monomers physically interact with cellular proteins, such as other cytosolic GSTs, signaling kinases and the membrane peroxidase peroxiredoxin 6. Other interactions reported in literature include that with regulatory proteins such as Fanconi anemia complementation group C protein, transglutaminase 2 and several members of the keratin family of genes. Transcription factors downstream of inflammatory and oxidative stress pathways, namely STAT3 and Nrf2, were recently identified to be further components of this interactome. Together these pieces of evidence suggest the existence of a regulatory biomolecular network in which GSTP represents a node of functional convergence and coordination of signaling and transcription proteins, namely the "GSTP interactome", associated with key cellular processes such as cell cycle regulation and the stress response. These aspects and the methodological approach to explore the cellular interactome(s) are discussed in this review paper. Copyright © 2016 Elsevier B.V. All rights reserved.

Identification of the PAK4 interactome reveals PAK4 phosphorylation of N-WASP and promotion of Arp2/3-dependent actin polymerization.

PubMed

Zhao, Miao; Spiess, Matthias; Johansson, Henrik J; Olofsson, Helene; Hu, Jianjiang; Lehtiö, Janne; Strömblad, Staffan

2017-09-29

p21-activated kinase 4 (PAK4) regulates cell proliferation, apoptosis, cell motility and F-actin remodeling, but the PAK4 interactome has not been systematically analyzed. Here, we comprehensively characterized the human PAK4 interactome by iTRAQ quantitative mass spectrometry of PAK4-immunoprecipitations. Consistent with its multiple reported functions, the PAK4 interactome was enriched in diverse protein networks, including the 14-3-3, proteasome, replication fork, CCT and Arp2/3 complexes. Because PAK4 co-immunoprecipitated most subunits of the Arp2/3 complex, we hypothesized that PAK4 may play a role in Arp2/3 dependent actin regulation. Indeed, we found that PAK4 interacts with and phosphorylates the nucleation promoting factor N-WASP at Ser484/Ser485 and promotes Arp2/3-dependent actin polymerization in vitro. Also, PAK4 ablation in vivo reduced N-WASP Ser484/Ser485 phosphorylation and altered the cellular balance between G- and F-actin as well as the actin organization. By presenting the PAK4 interactome, we here provide a powerful resource for further investigations and as proof of principle, we also indicate a novel mechanism by which PAK4 regulates actin cytoskeleton remodeling.

A Highly Efficient Approach to Protein Interactome Mapping Based on Collaborative Filtering Framework

NASA Astrophysics Data System (ADS)

Luo, Xin; You, Zhuhong; Zhou, Mengchu; Li, Shuai; Leung, Hareton; Xia, Yunni; Zhu, Qingsheng

2015-01-01

The comprehensive mapping of protein-protein interactions (PPIs) is highly desired for one to gain deep insights into both fundamental cell biology processes and the pathology of diseases. Finely-set small-scale experiments are not only very expensive but also inefficient to identify numerous interactomes despite their high accuracy. High-throughput screening techniques enable efficient identification of PPIs; yet the desire to further extract useful knowledge from these data leads to the problem of binary interactome mapping. Network topology-based approaches prove to be highly efficient in addressing this problem; however, their performance deteriorates significantly on sparse putative PPI networks. Motivated by the success of collaborative filtering (CF)-based approaches to the problem of personalized-recommendation on large, sparse rating matrices, this work aims at implementing a highly efficient CF-based approach to binary interactome mapping. To achieve this, we first propose a CF framework for it. Under this framework, we model the given data into an interactome weight matrix, where the feature-vectors of involved proteins are extracted. With them, we design the rescaled cosine coefficient to model the inter-neighborhood similarity among involved proteins, for taking the mapping process. Experimental results on three large, sparse datasets demonstrate that the proposed approach outperforms several sophisticated topology-based approaches significantly.

Determination of Protein Interactome of Transcription Factor Sox2 in Embryonic Stem Cells Engineered for Inducible Expression of Four Reprogramming Factors*

PubMed Central

Gao, Zhiguang; Cox, Jesse L.; Gilmore, Joshua M.; Ormsbee, Briana D.; Mallanna, Sunil K.; Washburn, Michael P.; Rizzino, Angie

2012-01-01

Unbiased proteomic screens provide a powerful tool for defining protein-protein interaction networks. Previous studies employed multidimensional protein identification technology to identify the Sox2-interactome in embryonic stem cells (ESC) undergoing differentiation in response to a small increase in the expression of epitope-tagged Sox2. Thus far the Sox2-interactome in ESC has not been determined. To identify the Sox2-interactome in ESC, we engineered ESC for inducible expression of different combinations of epitope-tagged Sox2 along with Oct4, Klf4, and c-Myc. Epitope-tagged Sox2 was used to circumvent the lack of suitable Sox2 antibodies needed to perform an unbiased proteomic screen of Sox2-associated proteins. Although i-OS-ESC differentiate when both Oct4 and Sox2 are elevated, i-OSKM-ESC do not differentiate even when the levels of the four transcription factors are coordinately elevated ∼2–3-fold. Our findings with i-OS-ESC and i-OSKM-ESC provide new insights into the reasons why ESC undergo differentiation when Sox2 and Oct4 are elevated in ESC. Importantly, the use of i-OSKM-ESC enabled us to identify the Sox2-interactome in undifferentiated ESC. Using multidimensional protein identification technology, we identified >70 proteins that associate with Sox2 in ESC. We extended these findings by testing the function of the Sox2-assoicated protein Smarcd1 and demonstrate that knockdown of Smarcd1 disrupts the self-renewal of ESC and induces their differentiation. Together, our work provides the first description of the Sox2-interactome in ESC and indicates that Sox2 along with other master regulators is part of a highly integrated protein-protein interaction landscape in ESC. PMID:22334693

The Protein Interactome of Mycobacteriophage Giles Predicts Functions for Unknown Proteins.

PubMed

Mehla, Jitender; Dedrick, Rebekah M; Caufield, J Harry; Siefring, Rachel; Mair, Megan; Johnson, Allison; Hatfull, Graham F; Uetz, Peter

2015-08-01

Mycobacteriophages are viruses that infect mycobacterial hosts and are prevalent in the environment. Nearly 700 mycobacteriophage genomes have been completely sequenced, revealing considerable diversity and genetic novelty. Here, we have determined the protein complement of mycobacteriophage Giles by mass spectrometry and mapped its genome-wide protein interactome to help elucidate the roles of its 77 predicted proteins, 50% of which have no known function. About 22,000 individual yeast two-hybrid (Y2H) tests with four different Y2H vectors, followed by filtering and retest screens, resulted in 324 reproducible protein-protein interactions, including 171 (136 nonredundant) high-confidence interactions. The complete set of high-confidence interactions among Giles proteins reveals new mechanistic details and predicts functions for unknown proteins. The Giles interactome is the first for any mycobacteriophage and one of just five known phage interactomes so far. Our results will help in understanding mycobacteriophage biology and aid in development of new genetic and therapeutic tools to understand Mycobacterium tuberculosis. Mycobacterium tuberculosis causes over 9 million new cases of tuberculosis each year. Mycobacteriophages, viruses of mycobacterial hosts, hold considerable potential to understand phage diversity, evolution, and mycobacterial biology, aiding in the development of therapeutic tools to control mycobacterial infections. The mycobacteriophage Giles protein-protein interaction network allows us to predict functions for unknown proteins and shed light on major biological processes in phage biology. For example, Giles gp76, a protein of unknown function, is found to associate with phage packaging and maturation. The functions of mycobacteriophage-derived proteins may suggest novel therapeutic approaches for tuberculosis. Our ORFeome clone set of Giles proteins and the interactome data will be useful resources for phage interactomics. Copyright © 2015, American Society for Microbiology. All Rights Reserved.

Next-generation sequencing coupled with a cell-free display technology for high-throughput production of reliable interactome data

PubMed Central

Fujimori, Shigeo; Hirai, Naoya; Ohashi, Hiroyuki; Masuoka, Kazuyo; Nishikimi, Akihiko; Fukui, Yoshinori; Washio, Takanori; Oshikubo, Tomohiro; Yamashita, Tatsuhiro; Miyamoto-Sato, Etsuko

2012-01-01

Next-generation sequencing (NGS) has been applied to various kinds of omics studies, resulting in many biological and medical discoveries. However, high-throughput protein-protein interactome datasets derived from detection by sequencing are scarce, because protein-protein interaction analysis requires many cell manipulations to examine the interactions. The low reliability of the high-throughput data is also a problem. Here, we describe a cell-free display technology combined with NGS that can improve both the coverage and reliability of interactome datasets. The completely cell-free method gives a high-throughput and a large detection space, testing the interactions without using clones. The quantitative information provided by NGS reduces the number of false positives. The method is suitable for the in vitro detection of proteins that interact not only with the bait protein, but also with DNA, RNA and chemical compounds. Thus, it could become a universal approach for exploring the large space of protein sequences and interactome networks. PMID:23056904

Quantitative interactome reveals that porcine reproductive and respiratory syndrome virus nonstructural protein 2 forms a complex with viral nucleocapsid protein and cellular vimentin.

PubMed

Song, Tao; Fang, Liurong; Wang, Dang; Zhang, Ruoxi; Zeng, Songlin; An, Kang; Chen, Huanchun; Xiao, Shaobo

2016-06-16

Porcine reproductive and respiratory syndrome virus (PRRSV) is an Arterivirus that has heavily impacted the global swine industry. The PRRSV nonstructural protein 2 (nsp2) plays crucial roles in viral replication and host immune regulation, most likely by interacting with viral or cellular proteins that have not yet been identified. In this study, a quantitative interactome approach based on immunoprecipitation and stable isotope labeling with amino acids in cell culture (SILAC) was performed to identify nsp2-interacting proteins in PRRSV-infected cells with an nsp2-specific monoclonal antibody. Nine viral proteins and 62 cellular proteins were identified as potential nsp2-interacting partners. Our data demonstrate that the PRRSV nsp1α, nsp1β, and nucleocapsid proteins all interact directly with nsp2. Nsp2-interacting cellular proteins were classified into different functional groups and an interactome network of nsp2 was generated. Interestingly, cellular vimentin, a known receptor for PRRSV, forms a complex with nsp2 by using viral nucleocapsid protein as an intermediate. Taken together, the nsp2 interactome under the condition of virus infection clarifies a role of nsp2 in PRRSV replication and immune evasion. Viral proteins must interact with other virus-encoded proteins and/or host cellular proteins to function, and interactome analysis is an ideal approach for identifying such interacting proteins. In this study, we used the quantitative interactome methodology to identify the viral and cellular proteins that potentially interact with the nonstructural protein 2 (nsp2) of porcine reproductive and respiratory syndrome virus (PRRSV) under virus infection conditions, thus providing a rich source of potential viral and cellular interaction partners for PRRSV nsp2. Based on the interactome data, we further demonstrated that PRRSV nsp2 and nucleocapsid protein together with cellular vimentin, form a complex that may be essential for viral attachment and replication, which partly explains the role of nsp2 in PRRSV replication and immune evasion. Copyright © 2016 Elsevier B.V. All rights reserved.

Rearrangement of the Protein Phosphatase 1 Interactome During Heart Failure Progression.

PubMed

Chiang, David Y; Alsina, Katherina M; Corradini, Eleonora; Fitzpatrick, Martin; Ni, Li; Lahiri, Satadru K; Reynolds, Julia; Pan, Xiaolu; Scott, Larry; Heck, Albert J R; Wehrens, Xander H

2018-04-18

Background -Heart failure (HF) is a complex disease with a rising prevalence despite advances in treatment. Protein phosphatase 1 (PP1) has long been implicated in HF pathogenesis but its exact role is both unclear and controversial. Most previous studies measured only the PP1 catalytic subunit (PP1c) without investigating its diverse set of interactors, which confer localization and substrate specificity to the holoenzyme. In this study we define the PP1 interactome in cardiac tissue and test the hypothesis that this interactome becomes rearranged during HF progression at the level of specific PP1c interactors. Methods -Mice were subjected to transverse aortic constriction and grouped based on ejection fraction (EF) into sham, hypertrophy, moderate HF (EF 30-40%), and severe HF (EF<30%). Cardiac lysates were subjected to affinity-purification using anti-PP1c antibodies followed by high-resolution mass spectrometry. Ppp1r7 was knocked down in mouse cardiomyocytes and HeLa cells using adeno-associated virus serotype 9 (AAV9) and siRNA, respectively. Calcium imaging was performed on isolated ventricular myocytes. Results -Seventy-one and 98 PP1c interactors were quantified from mouse cardiac and HeLa lysates, respectively, including many novel interactors and protein complexes. This represents the largest reproducible PP1 interactome dataset ever captured from any tissue, including both primary and secondary/tertiary interactors. Nine PP1c interactors with changes in their binding to PP1c were strongly associated with HF progression including two known (Ppp1r7, Ppp1r18) and 7 novel interactors. Within the entire cardiac PP1 interactome, Ppp1r7 had the highest binding to PP1c. Cardiac-specific knockdown in mice led to cardiac dysfunction and disruption of calcium release from the sarcoplasmic reticulum. Conclusions -PP1 is best studied at the level of its interactome, which undergoes significant rearrangement during HF progression. The nine key interactors that are associated with HF progression may represent potential targets in HF therapy. In particular, Ppp1r7 may play a central role in regulating the PP1 interactome by acting as a competitive molecular "sponge" of PP1c.

Evidence for network evolution in an arabidopsis interactome map

USDA-ARS?s Scientific Manuscript database

Plants have unique features that evolved in response to their environments and ecosystems. A full account of the complex cellular networks that underlie plant-specific functions is still missing. We describe a proteome-wide binary protein-protein interaction map for the interactome network of the pl...

Functional proteomic and interactome analysis of proteins associated with beef tenderness in angus cattle

USDA-ARS?s Scientific Manuscript database

Beef is a source of high quality protein for the human population, and beef tenderness has significant influence on beef palatability, consumer expectation and industry profitability. To further elucidate the factors affecting beef tenderness, functional proteomics and bioinformatics interactome ana...

Comprehensive interactome of Otx2 in the adult mouse neural retina.

PubMed

Fant, Bruno; Samuel, Alexander; Audebert, Stéphane; Couzon, Agnès; El Nagar, Salsabiel; Billon, Nathalie; Lamonerie, Thomas

2015-11-01

The Otx2 homeodomain transcription factor exerts multiple functions in specific developmental contexts, probably through the regulation of different sets of genes. Protein partners of Otx2 have been shown to modulate its activity. Therefore, the Otx2 interactome may play a key role in selecting a precise target-gene repertoire, hence determining its function in a specific tissue. To address the nature of Otx2 interactome, we generated a new recombinant Otx2(CTAP-tag) mouse line, designed for protein complexes purification. We validated this mouse line by establishing the Otx2 interactome in the adult neural retina. In this tissue, Otx2 is thought to have overlapping function with its paralog Crx. Our analysis revealed that, in contrary to Crx, Otx2 did not develop interactions with proteins that are known to regulate phototransduction genes but showed specific partnership with factors associated with retinal development. The relationship between Otx2 and Crx in the neural retina should therefore be considered as complementarity rather than redundancy. Furthermore, study of the Otx2 interactome revealed strong associations with RNA processing and translation machineries, suggesting unexpected roles for Otx2 in the regulation of selected target genes all along the transcription/translation pathway. The Otx2(CTAP-tag) line, therefore, appears suitable for a systematic approach to Otx2 protein-protein interactions. genesis 53:685-694, 2015. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

∆F508 CFTR interactome remodelling promotes rescue of cystic fibrosis.

PubMed

Pankow, Sandra; Bamberger, Casimir; Calzolari, Diego; Martínez-Bartolomé, Salvador; Lavallée-Adam, Mathieu; Balch, William E; Yates, John R

2015-12-24

Deletion of phenylalanine 508 of the cystic fibrosis transmembrane conductance regulator (∆F508 CFTR) is the major cause of cystic fibrosis, one of the most common inherited childhood diseases. The mutated CFTR anion channel is not fully glycosylated and shows minimal activity in bronchial epithelial cells of patients with cystic fibrosis. Low temperature or inhibition of histone deacetylases can partly rescue ∆F508 CFTR cellular processing defects and function. A favourable change of ∆F508 CFTR protein-protein interactions was proposed as a mechanism of rescue; however, CFTR interactome dynamics during temperature shift and inhibition of histone deacetylases are unknown. Here we report the first comprehensive analysis of the CFTR and ∆F508 CFTR interactome and its dynamics during temperature shift and inhibition of histone deacetylases. By using a novel deep proteomic analysis method, we identify 638 individual high-confidence CFTR interactors and discover a ∆F508 deletion-specific interactome, which is extensively remodelled upon rescue. Detailed analysis of the interactome remodelling identifies key novel interactors, whose loss promote ∆F508 CFTR channel function in primary cystic fibrosis epithelia or which are critical for CFTR biogenesis. Our results demonstrate that global remodelling of ∆F508 CFTR interactions is crucial for rescue, and provide comprehensive insight into the molecular disease mechanisms of cystic fibrosis caused by deletion of F508.

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

PubMed

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

2017-01-01

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

Identification and functional analysis of the BIM interactome; new clues on its possible involvement in Epstein-Barr Virus-associated diseases.

PubMed

Rouka, Erasmia; Kyriakou, Despoina

2015-12-01

Epigenetic deregulation is a common feature in the pathogenesis of Epstein-Barr Virus (EBV)-related lymphomas and carcinomas. Previous studies have demonstrated a strong association between EBV latency in B-cells and epigenetic silencing of the tumor suppressor gene BIM. This study aimed to the construction and functional analysis of the BIM interactome in order to identify novel host genes that may be targeted by EBV. Fifty-nine unique interactors were found to compose the BIM gene network. Ontological analysis at the pathway level highlighted infectious diseases along with neuropathologies. These results underline the possible interplay between the BIM interactome and EBV-associated disorders.

Rapid, Optimized Interactomic Screening

PubMed Central

Hakhverdyan, Zhanna; Domanski, Michal; Hough, Loren; Oroskar, Asha A.; Oroskar, Anil R.; Keegan, Sarah; Dilworth, David J.; Molloy, Kelly R.; Sherman, Vadim; Aitchison, John D.; Fenyö, David; Chait, Brian T.; Jensen, Torben Heick; Rout, Michael P.; LaCava, John

2015-01-01

We must reliably map the interactomes of cellular macromolecular complexes in order to fully explore and understand biological systems. However, there are no methods to accurately predict how to capture a given macromolecular complex with its physiological binding partners. Here, we present a screen that comprehensively explores the parameters affecting the stability of interactions in affinity-captured complexes, enabling the discovery of physiological binding partners and the elucidation of their functional interactions in unparalleled detail. We have implemented this screen on several macromolecular complexes from a variety of organisms, revealing novel profiles even for well-studied proteins. Our approach is robust, economical and automatable, providing an inroad to the rigorous, systematic dissection of cellular interactomes. PMID:25938370

The Endogenous GRP78 Interactome in Human Head and Neck Cancers: A Deterministic Role of Cell Surface GRP78 in Cancer Stemness.

PubMed

Chen, Hsin-Ying; Chang, Joseph Tung-Chieh; Chien, Kun-Yi; Lee, Yun-Shien; You, Guo-Rung; Cheng, Ann-Joy

2018-01-11

Cell surface glucose regulated protein 78 (GRP78), an endoplasmic reticulum (ER) chaperone, was suggested to be a cancer stem cell marker, but the influence of this molecule on cancer stemness is poorly characterized. In this study, we developed a mass spectrometry platform to detect the endogenous interactome of GRP78 and investigated its role in cancer stemness. The interactome results showed that cell surface GRP78 associates with multiple molecules. The influence of cell population heterogeneity of head and neck cancer cell lines (OECM1, FaDu, and BM2) according to the cell surface expression levels of GRP78 and the GRP78 interactome protein, Progranulin, was investigated. The four sorted cell groups exhibited distinct cell cycle distributions, asymmetric/symmetric cell divisions, and different relative expression levels of stemness markers. Our results demonstrate that cell surface GRP78 promotes cancer stemness, whereas drives cells toward a non-stemlike phenotype when it chaperones Progranulin. We conclude that cell surface GRP78 is a chaperone exerting a deterministic influence on cancer stemness.

Comprehensive Identification of RNA-Binding Proteins by RNA Interactome Capture.

PubMed

Castello, Alfredo; Horos, Rastislav; Strein, Claudia; Fischer, Bernd; Eichelbaum, Katrin; Steinmetz, Lars M; Krijgsveld, Jeroen; Hentze, Matthias W

2016-01-01

RNA associates with RNA-binding proteins (RBPs) from synthesis to decay, forming dynamic ribonucleoproteins (RNPs). In spite of the preeminent role of RBPs regulating RNA fate, the scope of cellular RBPs has remained largely unknown. We have recently developed a novel and comprehensive method to identify the repertoire of active RBPs of cultured cells, called RNA interactome capture. Using in vivo UV cross-linking on cultured cells, proteins are covalently bound to RNA if the contact between the two is direct ("zero distance"). Protein-RNA complexes are purified by poly(A) tail-dependent oligo(dT) capture and analyzed by quantitative mass spectrometry. Because UV irradiation is applied to living cells and purification is performed using highly stringent washes, RNA interactome capture identifies physiologic and direct protein-RNA interactions. Applied to HeLa cells, this protocol revealed the near-complete repertoire of RBPs, including hundreds of novel RNA binders. Apart from its RBP discovery capacity, quantitative and comparative RNA interactome capture can also be used to study the responses of the RBP repertoire to different physiological cues and processes, including metabolic stress, differentiation, development, or the response to drugs.

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

PubMed

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

2018-05-08

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

Deriving Heterospecific Self-Assembling Protein-Protein Interactions Using a Computational Interactome Screen.

PubMed

Crooks, Richard O; Baxter, Daniel; Panek, Anna S; Lubben, Anneke T; Mason, Jody M

2016-01-29

Interactions between naturally occurring proteins are highly specific, with protein-network imbalances associated with numerous diseases. For designed protein-protein interactions (PPIs), required specificity can be notoriously difficult to engineer. To accelerate this process, we have derived peptides that form heterospecific PPIs when combined. This is achieved using software that generates large virtual libraries of peptide sequences and searches within the resulting interactome for preferentially interacting peptides. To demonstrate feasibility, we have (i) generated 1536 peptide sequences based on the parallel dimeric coiled-coil motif and varied residues known to be important for stability and specificity, (ii) screened the 1,180,416 member interactome for predicted Tm values and (iii) used predicted Tm cutoff points to isolate eight peptides that form four heterospecific PPIs when combined. This required that all 32 hypothetical off-target interactions within the eight-peptide interactome be disfavoured and that the four desired interactions pair correctly. Lastly, we have verified the approach by characterising all 36 pairs within the interactome. In analysing the output, we hypothesised that several sequences are capable of adopting antiparallel orientations. We subsequently improved the software by removing sequences where doing so led to fully complementary electrostatic pairings. Our approach can be used to derive increasingly large and therefore complex sets of heterospecific PPIs with a wide range of potential downstream applications from disease modulation to the design of biomaterials and peptides in synthetic biology. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Simultaneously measuring multiple protein interactions and their correlations in a cell by Protein-interactome Footprinting

PubMed Central

Luo, Si-Wei; Liang, Zhi; Wu, Jia-Rui

2017-01-01

Quantitatively detecting correlations of multiple protein-protein interactions (PPIs) in vivo is a big challenge. Here we introduce a novel method, termed Protein-interactome Footprinting (PiF), to simultaneously measure multiple PPIs in one cell. The principle of PiF is that each target physical PPI in the interactome is simultaneously transcoded into a specific DNA sequence based on dimerization of the target proteins fused with DNA-binding domains. The interaction intensity of each target protein is quantified as the copy number of the specific DNA sequences bound by each fusion protein dimers. Using PiF, we quantitatively reveal dynamic patterns of PPIs and their correlation network in E. coli two-component systems. PMID:28338015

MitProNet: A Knowledgebase and Analysis Platform of Proteome, Interactome and Diseases for Mammalian Mitochondria

PubMed Central

Mao, Song; Chai, Xiaoqiang; Hu, Yuling; Hou, Xugang; Tang, Yiheng; Bi, Cheng; Li, Xiao

2014-01-01

Mitochondrion plays a central role in diverse biological processes in most eukaryotes, and its dysfunctions are critically involved in a large number of diseases and the aging process. A systematic identification of mitochondrial proteomes and characterization of functional linkages among mitochondrial proteins are fundamental in understanding the mechanisms underlying biological functions and human diseases associated with mitochondria. Here we present a database MitProNet which provides a comprehensive knowledgebase for mitochondrial proteome, interactome and human diseases. First an inventory of mammalian mitochondrial proteins was compiled by widely collecting proteomic datasets, and the proteins were classified by machine learning to achieve a high-confidence list of mitochondrial proteins. The current version of MitProNet covers 1124 high-confidence proteins, and the remainders were further classified as middle- or low-confidence. An organelle-specific network of functional linkages among mitochondrial proteins was then generated by integrating genomic features encoded by a wide range of datasets including genomic context, gene expression profiles, protein-protein interactions, functional similarity and metabolic pathways. The functional-linkage network should be a valuable resource for the study of biological functions of mitochondrial proteins and human mitochondrial diseases. Furthermore, we utilized the network to predict candidate genes for mitochondrial diseases using prioritization algorithms. All proteins, functional linkages and disease candidate genes in MitProNet were annotated according to the information collected from their original sources including GO, GEO, OMIM, KEGG, MIPS, HPRD and so on. MitProNet features a user-friendly graphic visualization interface to present functional analysis of linkage networks. As an up-to-date database and analysis platform, MitProNet should be particularly helpful in comprehensive studies of complicated biological mechanisms underlying mitochondrial functions and human mitochondrial diseases. MitProNet is freely accessible at http://bio.scu.edu.cn:8085/MitProNet. PMID:25347823

Proteomic analysis of sweet algerian apricot kernels (Prunus armeniaca L.) by combinatorial peptide ligand libraries and LC-MS/MS.

PubMed

Ghorab, Hamida; Lammi, Carmen; Arnoldi, Anna; Kabouche, Zahia; Aiello, Gilda

2018-01-15

An investigation on the proteome of the sweet kernel of apricot, based on equalisation with combinatorial peptide ligand libraries (CPLLs), SDS-PAGE, nLC-ESI-MS/MS, and database search, permitted identifying 175 proteins. Gene ontology analysis indicated that their main molecular functions are in nucleotide binding (20.9%), hydrolase activities (10.6%), kinase activities (7%), and catalytic activity (5.6%). A protein-protein association network analysis using STRING software permitted to build an interactomic map of all detected proteins, characterised by 34 interactions. In order to forecast the potential health benefits deriving from the consumption of these proteins, the two most abundant, i.e. Prunin 1 and 2, were enzymatically digested in silico predicting 10 and 14 peptides, respectively. Searching their sequences in the database BIOPEP, it was possible to suggest a variety of bioactivities, including dipeptidyl peptidase-IV (DPP-IV) and angiotensin converting enzyme I (ACE) inhibition, glucose uptake stimulation and antioxidant properties. Copyright © 2017 Elsevier Ltd. All rights reserved.

Computer applications making rapid advances in high throughput microbial proteomics (HTMP).

PubMed

Anandkumar, Balakrishna; Haga, Steve W; Wu, Hui-Fen

2014-02-01

The last few decades have seen the rise of widely-available proteomics tools. From new data acquisition devices, such as MALDI-MS and 2DE to new database searching softwares, these new products have paved the way for high throughput microbial proteomics (HTMP). These tools are enabling researchers to gain new insights into microbial metabolism, and are opening up new areas of study, such as protein-protein interactions (interactomics) discovery. Computer software is a key part of these emerging fields. This current review considers: 1) software tools for identifying the proteome, such as MASCOT or PDQuest, 2) online databases of proteomes, such as SWISS-PROT, Proteome Web, or the Proteomics Facility of the Pathogen Functional Genomics Resource Center, and 3) software tools for applying proteomic data, such as PSI-BLAST or VESPA. These tools allow for research in network biology, protein identification, functional annotation, target identification/validation, protein expression, protein structural analysis, metabolic pathway engineering and drug discovery.

The role of the interactome in the maintenance of deleterious variability in human populations

PubMed Central

Garcia-Alonso, Luz; Jiménez-Almazán, Jorge; Carbonell-Caballero, Jose; Vela-Boza, Alicia; Santoyo-López, Javier; Antiñolo, Guillermo; Dopazo, Joaquin

2014-01-01

Recent genomic projects have revealed the existence of an unexpectedly large amount of deleterious variability in the human genome. Several hypotheses have been proposed to explain such an apparently high mutational load. However, the mechanisms by which deleterious mutations in some genes cause a pathological effect but are apparently innocuous in other genes remain largely unknown. This study searched for deleterious variants in the 1,000 genomes populations, as well as in a newly sequenced population of 252 healthy Spanish individuals. In addition, variants causative of monogenic diseases and somatic variants from 41 chronic lymphocytic leukaemia patients were analysed. The deleterious variants found were analysed in the context of the interactome to understand the role of network topology in the maintenance of the observed mutational load. Our results suggest that one of the mechanisms whereby the effect of these deleterious variants on the phenotype is suppressed could be related to the configuration of the protein interaction network. Most of the deleterious variants observed in healthy individuals are concentrated in peripheral regions of the interactome, in combinations that preserve their connectivity, and have a marginal effect on interactome integrity. On the contrary, likely pathogenic cancer somatic deleterious variants tend to occur in internal regions of the interactome, often with associated structural consequences. Finally, variants causative of monogenic diseases seem to occupy an intermediate position. Our observations suggest that the real pathological potential of a variant might be more a systems property rather than an intrinsic property of individual proteins. PMID:25261458

The role of the interactome in the maintenance of deleterious variability in human populations.

PubMed

Garcia-Alonso, Luz; Jiménez-Almazán, Jorge; Carbonell-Caballero, Jose; Vela-Boza, Alicia; Santoyo-López, Javier; Antiñolo, Guillermo; Dopazo, Joaquin

2014-09-26

Recent genomic projects have revealed the existence of an unexpectedly large amount of deleterious variability in the human genome. Several hypotheses have been proposed to explain such an apparently high mutational load. However, the mechanisms by which deleterious mutations in some genes cause a pathological effect but are apparently innocuous in other genes remain largely unknown. This study searched for deleterious variants in the 1,000 genomes populations, as well as in a newly sequenced population of 252 healthy Spanish individuals. In addition, variants causative of monogenic diseases and somatic variants from 41 chronic lymphocytic leukaemia patients were analysed. The deleterious variants found were analysed in the context of the interactome to understand the role of network topology in the maintenance of the observed mutational load. Our results suggest that one of the mechanisms whereby the effect of these deleterious variants on the phenotype is suppressed could be related to the configuration of the protein interaction network. Most of the deleterious variants observed in healthy individuals are concentrated in peripheral regions of the interactome, in combinations that preserve their connectivity, and have a marginal effect on interactome integrity. On the contrary, likely pathogenic cancer somatic deleterious variants tend to occur in internal regions of the interactome, often with associated structural consequences. Finally, variants causative of monogenic diseases seem to occupy an intermediate position. Our observations suggest that the real pathological potential of a variant might be more a systems property rather than an intrinsic property of individual proteins. © 2014 The Authors. Published under the terms of the CC BY 4.0 license.

Next Generation Protein Interactomes for Plant Systems Biology and Biomass Feedstock Research

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ecker, Joseph Robert; Trigg, Shelly; Garza, Renee

Biofuel crop cultivation is a necessary step in heading towards a sustainable future, making their genomic studies a priority. While technology platforms that currently exist for studying non-model crop species, like switch-grass or sorghum, have yielded large quantities of genomic and expression data, still a large gap exists between molecular mechanism and phenotype. The aspect of molecular activity at the level of protein-protein interactions has recently begun to bridge this gap, providing a more global perspective. Interactome analysis has defined more specific functional roles of proteins based on their interaction partners, neighborhoods, and other network features, making it possible tomore » distinguish unique modules of immune response to different plant pathogens(Jiang, Dong, and Zhang 2016). As we work towards cultivating heartier biofuel crops, interactome data will lead to uncovering crop-specific defense and development networks. However, the collection of protein interaction data has been limited to expensive, time-consuming, hard-to-scale assays that mostly require cloned ORF collections. For these reasons, we have successfully developed a highly scalable, economical, and sensitive yeast two-hybrid assay, ProCREate, that can be universally applied to generate proteome-wide primary interactome data. ProCREate enables en masse pooling and massively paralleled sequencing for the identification of interacting proteins by exploiting Cre-lox recombination. ProCREate can be used to screen ORF/cDNA libraries from feedstock plant tissues. The interactome data generated will yield deeper insight into many molecular processes and pathways that can be used to guide improvement of feedstock productivity and sustainability.« less

CrossCheck: an open-source web tool for high-throughput screen data analysis.

PubMed

Najafov, Jamil; Najafov, Ayaz

2017-07-19

Modern high-throughput screening methods allow researchers to generate large datasets that potentially contain important biological information. However, oftentimes, picking relevant hits from such screens and generating testable hypotheses requires training in bioinformatics and the skills to efficiently perform database mining. There are currently no tools available to general public that allow users to cross-reference their screen datasets with published screen datasets. To this end, we developed CrossCheck, an online platform for high-throughput screen data analysis. CrossCheck is a centralized database that allows effortless comparison of the user-entered list of gene symbols with 16,231 published datasets. These datasets include published data from genome-wide RNAi and CRISPR screens, interactome proteomics and phosphoproteomics screens, cancer mutation databases, low-throughput studies of major cell signaling mediators, such as kinases, E3 ubiquitin ligases and phosphatases, and gene ontological information. Moreover, CrossCheck includes a novel database of predicted protein kinase substrates, which was developed using proteome-wide consensus motif searches. CrossCheck dramatically simplifies high-throughput screen data analysis and enables researchers to dig deep into the published literature and streamline data-driven hypothesis generation. CrossCheck is freely accessible as a web-based application at http://proteinguru.com/crosscheck.

NRF2-ome: an integrated web resource to discover protein interaction and regulatory networks of NRF2.

PubMed

Türei, Dénes; Papp, Diána; Fazekas, Dávid; Földvári-Nagy, László; Módos, Dezső; Lenti, Katalin; Csermely, Péter; Korcsmáros, Tamás

2013-01-01

NRF2 is the master transcriptional regulator of oxidative and xenobiotic stress responses. NRF2 has important roles in carcinogenesis, inflammation, and neurodegenerative diseases. We developed an online resource, NRF2-ome, to provide an integrated and systems-level database for NRF2. The database contains manually curated and predicted interactions of NRF2 as well as data from external interaction databases. We integrated NRF2 interactome with NRF2 target genes, NRF2 regulating TFs, and miRNAs. We connected NRF2-ome to signaling pathways to allow mapping upstream NRF2 regulatory components that could directly or indirectly influence NRF2 activity totaling 35,967 protein-protein and signaling interactions. The user-friendly website allows researchers without computational background to search, browse, and download the database. The database can be downloaded in SQL, CSV, BioPAX, SBML, PSI-MI, and in a Cytoscape CYS file formats. We illustrated the applicability of the website by suggesting a posttranscriptional negative feedback of NRF2 by MAFG protein and raised the possibility of a connection between NRF2 and the JAK/STAT pathway through STAT1 and STAT3. NRF2-ome can also be used as an evaluation tool to help researchers and drug developers to understand the hidden regulatory mechanisms in the complex network of NRF2.

Targets of drugs are generally, and targets of drugs having side effects are specifically good spreaders of human interactome perturbations.

PubMed

Perez-Lopez, Áron R; Szalay, Kristóf Z; Türei, Dénes; Módos, Dezső; Lenti, Katalin; Korcsmáros, Tamás; Csermely, Peter

2015-05-11

Network-based methods are playing an increasingly important role in drug design. Our main question in this paper was whether the efficiency of drug target proteins to spread perturbations in the human interactome is larger if the binding drugs have side effects, as compared to those which have no reported side effects. Our results showed that in general, drug targets were better spreaders of perturbations than non-target proteins, and in particular, targets of drugs with side effects were also better spreaders of perturbations than targets of drugs having no reported side effects in human protein-protein interaction networks. Colorectal cancer-related proteins were good spreaders and had a high centrality, while type 2 diabetes-related proteins showed an average spreading efficiency and had an average centrality in the human interactome. Moreover, the interactome-distance between drug targets and disease-related proteins was higher in diabetes than in colorectal cancer. Our results may help a better understanding of the network position and dynamics of drug targets and disease-related proteins, and may contribute to develop additional, network-based tests to increase the potential safety of drug candidates.

Expanding the Interactome of TES by Exploiting TES Modules with Different Subcellular Localizations.

PubMed

Sala, Stefano; Van Troys, Marleen; Medves, Sandrine; Catillon, Marie; Timmerman, Evy; Staes, An; Schaffner-Reckinger, Elisabeth; Gevaert, Kris; Ampe, Christophe

2017-05-05

The multimodular nature of many eukaryotic proteins underlies their temporal or spatial engagement in a range of protein cocomplexes. Using the multimodule protein testin (TES), we here report a proteomics approach to increase insight in cocomplex diversity. The LIM-domain containing and tumor suppressor protein TES is present at different actin cytoskeleton adhesion structures in cells and influences cell migration, adhesion and spreading. TES module accessibility has been proposed to vary due to conformational switching and variants of TES lacking specific domains target to different subcellular locations. By applying iMixPro AP-MS ("intelligent Mixing of Proteomes"-affinity purification-mass spectrometry) to a set of tagged-TES modular variants, we identified proteins residing in module-specific cocomplexes. The obtained distinct module-specific interactomes combine to a global TES interactome that becomes more extensive and richer in information. Applying pathway analysis to the module interactomes revealed expected actin-related canonical pathways and also less expected pathways. We validated two new TES cocomplex partners: TGFB1I1 and a short form of the glucocorticoid receptor. TES and TGFB1I1 are shown to oppositely affect cell spreading providing biological validity for their copresence in complexes since they act in similar processes.

The interactome of the copper transporter ATP7A belongs to a network of neurodevelopmental and neurodegeneration factors

PubMed Central

Comstra, Heather S; McArthy, Jacob; Rudin-Rush, Samantha; Hartwig, Cortnie; Gokhale, Avanti; Zlatic, Stephanie A; Blackburn, Jessica B; Werner, Erica; Petris, Michael; D’Souza, Priya; Panuwet, Parinya; Barr, Dana Boyd; Lupashin, Vladimir; Vrailas-Mortimer, Alysia; Faundez, Victor

2017-01-01

Genetic and environmental factors, such as metals, interact to determine neurological traits. We reasoned that interactomes of molecules handling metals in neurons should include novel metal homeostasis pathways. We focused on copper and its transporter ATP7A because ATP7A null mutations cause neurodegeneration. We performed ATP7A immunoaffinity chromatography and identified 541 proteins co-isolating with ATP7A. The ATP7A interactome concentrated gene products implicated in neurodegeneration and neurodevelopmental disorders, including subunits of the Golgi-localized conserved oligomeric Golgi (COG) complex. COG null cells possess altered content and subcellular localization of ATP7A and CTR1 (SLC31A1), the transporter required for copper uptake, as well as decreased total cellular copper, and impaired copper-dependent metabolic responses. Changes in the expression of ATP7A and COG subunits in Drosophila neurons altered synapse development in larvae and copper-induced mortality of adult flies. We conclude that the ATP7A interactome encompasses a novel COG-dependent mechanism to specify neuronal development and survival. DOI: http://dx.doi.org/10.7554/eLife.24722.001 PMID:28355134

Characterization of chromosomal architecture in Arabidopsis by chromosome conformation capture

PubMed Central

2013-01-01

Background The packaging of long chromatin fibers in the nucleus poses a major challenge, as it must fulfill both physical and functional requirements. Until recently, insights into the chromosomal architecture of plants were mainly provided by cytogenetic studies. Complementary to these analyses, chromosome conformation capture technologies promise to refine and improve our view on chromosomal architecture and to provide a more generalized description of nuclear organization. Results Employing circular chromosome conformation capture, this study describes chromosomal architecture in Arabidopsis nuclei from a genome-wide perspective. Surprisingly, the linear organization of chromosomes is reflected in the genome-wide interactome. In addition, we study the interplay of the interactome and epigenetic marks and report that the heterochromatic knob on the short arm of chromosome 4 maintains a pericentromere-like interaction profile and interactome despite its euchromatic surrounding. Conclusion Despite the extreme condensation that is necessary to pack the chromosomes into the nucleus, the Arabidopsis genome appears to be packed in a predictive manner, according to the following criteria: heterochromatin and euchromatin represent two distinct interactomes; interactions between chromosomes correlate with the linear position on the chromosome arm; and distal chromosome regions have a higher potential to interact with other chromosomes. PMID:24267747

Targets of drugs are generally, and targets of drugs having side effects are specifically good spreaders of human interactome perturbations

NASA Astrophysics Data System (ADS)

Perez-Lopez, Áron R.; Szalay, Kristóf Z.; Türei, Dénes; Módos, Dezső; Lenti, Katalin; Korcsmáros, Tamás; Csermely, Peter

2015-05-01

Network-based methods are playing an increasingly important role in drug design. Our main question in this paper was whether the efficiency of drug target proteins to spread perturbations in the human interactome is larger if the binding drugs have side effects, as compared to those which have no reported side effects. Our results showed that in general, drug targets were better spreaders of perturbations than non-target proteins, and in particular, targets of drugs with side effects were also better spreaders of perturbations than targets of drugs having no reported side effects in human protein-protein interaction networks. Colorectal cancer-related proteins were good spreaders and had a high centrality, while type 2 diabetes-related proteins showed an average spreading efficiency and had an average centrality in the human interactome. Moreover, the interactome-distance between drug targets and disease-related proteins was higher in diabetes than in colorectal cancer. Our results may help a better understanding of the network position and dynamics of drug targets and disease-related proteins, and may contribute to develop additional, network-based tests to increase the potential safety of drug candidates.

Mapping the Small Molecule Interactome by Mass Spectrometry.

PubMed

Flaxman, Hope A; Woo, Christina M

2018-01-16

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

SPRINT: ultrafast protein-protein interaction prediction of the entire human interactome.

PubMed

Li, Yiwei; Ilie, Lucian

2017-11-15

Proteins perform their functions usually by interacting with other proteins. Predicting which proteins interact is a fundamental problem. Experimental methods are slow, expensive, and have a high rate of error. Many computational methods have been proposed among which sequence-based ones are very promising. However, so far no such method is able to predict effectively the entire human interactome: they require too much time or memory. We present SPRINT (Scoring PRotein INTeractions), a new sequence-based algorithm and tool for predicting protein-protein interactions. We comprehensively compare SPRINT with state-of-the-art programs on seven most reliable human PPI datasets and show that it is more accurate while running orders of magnitude faster and using very little memory. SPRINT is the only sequence-based program that can effectively predict the entire human interactome: it requires between 15 and 100 min, depending on the dataset. Our goal is to transform the very challenging problem of predicting the entire human interactome into a routine task. The source code of SPRINT is freely available from https://github.com/lucian-ilie/SPRINT/ and the datasets and predicted PPIs from www.csd.uwo.ca/faculty/ilie/SPRINT/ .

Systematic analyses of the ultraviolet radiation resistance-associated gene product (UVRAG) protein interactome by tandem affinity purification.

PubMed

Son, Ji-Hye; Hwang, Eurim C; Kim, Joungmok

2016-03-01

Ultraviolet radiation resistance-associated gene product (UVRAG) was originally identified as a protein involved in cellular responses to UV irradiation. Subsequent studies have demonstrated that UVRAG plays as an important role in autophagy, a lysosome-dependent catabolic program, as a part of a pro-autophagy PIK3C3/VPS34 lipid kinase complex. Several recent studies have shown that UVRAG is also involved in autophagy-independent cellular functions, such as DNA repair/stability and vesicular trafficking/fusion. Here, we examined the UVRAG protein interactome to obtain information about its functional network. To this end, we screened UVRAG-interacting proteins using a tandem affinity purification method coupled with MALDI-TOF/MS analysis. Our results demonstrate that UVRAG interacts with various proteins involved in a wide spectrum of cellular functions, including genome stability, protein translational elongation, protein localization (trafficking), vacuole organization, transmembrane transport as well as autophagy. Notably, the interactome list of high-confidence UVRAG-interacting proteins is enriched for proteins involved in the regulation of genome stability. Our systematic UVRAG interactome analysis should provide important clues for understanding a variety of UVRAG functions.

The IBD interactome: an integrated view of aetiology, pathogenesis and therapy.

PubMed

de Souza, Heitor S P; Fiocchi, Claudio; Iliopoulos, Dimitrios

2017-12-01

Crohn's disease and ulcerative colitis are prototypical complex diseases characterized by chronic and heterogeneous manifestations, induced by interacting environmental, genomic, microbial and immunological factors. These interactions result in an overwhelming complexity that cannot be tackled by studying the totality of each pathological component (an '-ome') in isolation without consideration of the interaction among all relevant -omes that yield an overall 'network effect'. The outcome of this effect is the 'IBD interactome', defined as a disease network in which dysregulation of individual -omes causes intestinal inflammation mediated by dysfunctional molecular modules. To define the IBD interactome, new concepts and tools are needed to implement a systems approach; an unbiased data-driven integration strategy that reveals key players of the system, pinpoints the central drivers of inflammation and enables development of targeted therapies. Powerful bioinformatics tools able to query and integrate multiple -omes are available, enabling the integration of genomic, epigenomic, transcriptomic, proteomic, metabolomic and microbiome information to build a comprehensive molecular map of IBD. This approach will enable identification of IBD molecular subtypes, correlations with clinical phenotypes and elucidation of the central hubs of the IBD interactome that will aid discovery of compounds that can specifically target the hubs that control the disease.

Network Approach to Disease Diagnosis

NASA Astrophysics Data System (ADS)

Sharma, Amitabh; Bashan, Amir; Barabasi, Alber-Laszlo

2014-03-01

Human diseases could be viewed as perturbations of the underlying biological system. A thorough understanding of the topological and dynamical properties of the biological system is crucial to explain the mechanisms of many complex diseases. Recently network-based approaches have provided a framework for integrating multi-dimensional biological data that results in a better understanding of the pathophysiological state of complex diseases. Here we provide a network-based framework to improve the diagnosis of complex diseases. This framework is based on the integration of transcriptomics and the interactome. We analyze the overlap between the differentially expressed (DE) genes and disease genes (DGs) based on their locations in the molecular interaction network (''interactome''). Disease genes and their protein products tend to be much more highly connected than random, hence defining a disease sub-graph (called disease module) in the interactome. DE genes, even though different from the known set of DGs, may be significantly associated with the disease when considering their closeness to the disease module in the interactome. This new network approach holds the promise to improve the diagnosis of patients who cannot be diagnosed using conventional tools. Support was provided by HL066289 and HL105339 grants from the U.S. National Institutes of Health.

Targets of drugs are generally, and targets of drugs having side effects are specifically good spreaders of human interactome perturbations

PubMed Central

Perez-Lopez, Áron R.; Szalay, Kristóf Z.; Türei, Dénes; Módos, Dezső; Lenti, Katalin; Korcsmáros, Tamás; Csermely, Peter

2015-01-01

Network-based methods are playing an increasingly important role in drug design. Our main question in this paper was whether the efficiency of drug target proteins to spread perturbations in the human interactome is larger if the binding drugs have side effects, as compared to those which have no reported side effects. Our results showed that in general, drug targets were better spreaders of perturbations than non-target proteins, and in particular, targets of drugs with side effects were also better spreaders of perturbations than targets of drugs having no reported side effects in human protein-protein interaction networks. Colorectal cancer-related proteins were good spreaders and had a high centrality, while type 2 diabetes-related proteins showed an average spreading efficiency and had an average centrality in the human interactome. Moreover, the interactome-distance between drug targets and disease-related proteins was higher in diabetes than in colorectal cancer. Our results may help a better understanding of the network position and dynamics of drug targets and disease-related proteins, and may contribute to develop additional, network-based tests to increase the potential safety of drug candidates. PMID:25960144

Bacterial Interactomes: Interacting Protein Partners Share Similar Function and Are Validated in Independent Assays More Frequently Than Previously Reported*

PubMed Central

Shatsky, Maxim; Allen, Simon; Gold, Barbara L.; Liu, Nancy L.; Juba, Thomas R.; Reveco, Sonia A.; Elias, Dwayne A.; Prathapam, Ramadevi; He, Jennifer; Yang, Wenhong; Szakal, Evelin D.; Liu, Haichuan; Singer, Mary E.; Geller, Jil T.; Lam, Bonita R.; Saini, Avneesh; Trotter, Valentine V.; Hall, Steven C.; Fisher, Susan J.; Brenner, Steven E.; Chhabra, Swapnil R.; Hazen, Terry C.; Wall, Judy D.; Witkowska, H. Ewa; Biggin, Mark D.; Chandonia, John-Marc; Butland, Gareth

2016-01-01

Numerous affinity purification-mass spectrometry (AP-MS) and yeast two-hybrid screens have each defined thousands of pairwise protein-protein interactions (PPIs), most of which are between functionally unrelated proteins. The accuracy of these networks, however, is under debate. Here, we present an AP-MS survey of the bacterium Desulfovibrio vulgaris together with a critical reanalysis of nine published bacterial yeast two-hybrid and AP-MS screens. We have identified 459 high confidence PPIs from D. vulgaris and 391 from Escherichia coli. Compared with the nine published interactomes, our two networks are smaller, are much less highly connected, and have significantly lower false discovery rates. In addition, our interactomes are much more enriched in protein pairs that are encoded in the same operon, have similar functions, and are reproducibly detected in other physical interaction assays than the pairs reported in prior studies. Our work establishes more stringent benchmarks for the properties of protein interactomes and suggests that bona fide PPIs much more frequently involve protein partners that are annotated with similar functions or that can be validated in independent assays than earlier studies suggested. PMID:26873250

Perturbation of the mutated EGFR interactome identifies vulnerabilities and resistance mechanisms.

PubMed

Li, Jiannong; Bennett, Keiryn; Stukalov, Alexey; Fang, Bin; Zhang, Guolin; Yoshida, Takeshi; Okamoto, Isamu; Kim, Jae-Young; Song, Lanxi; Bai, Yun; Qian, Xiaoning; Rawal, Bhupendra; Schell, Michael; Grebien, Florian; Winter, Georg; Rix, Uwe; Eschrich, Steven; Colinge, Jacques; Koomen, John; Superti-Furga, Giulio; Haura, Eric B

2013-11-05

We hypothesized that elucidating the interactome of epidermal growth factor receptor (EGFR) forms that are mutated in lung cancer, via global analysis of protein-protein interactions, phosphorylation, and systematically perturbing the ensuing network nodes, should offer a new, more systems-level perspective of the molecular etiology. Here, we describe an EGFR interactome of 263 proteins and offer a 14-protein core network critical to the viability of multiple EGFR-mutated lung cancer cells. Cells with acquired resistance to EGFR tyrosine kinase inhibitors (TKIs) had differential dependence of the core network proteins based on the underlying molecular mechanisms of resistance. Of the 14 proteins, 9 are shown to be specifically associated with survival of EGFR-mutated lung cancer cell lines. This included EGFR, GRB2, MK12, SHC1, ARAF, CD11B, ARHG5, GLU2B, and CD11A. With the use of a drug network associated with the core network proteins, we identified two compounds, midostaurin and lestaurtinib, that could overcome drug resistance through direct EGFR inhibition when combined with erlotinib. Our results, enabled by interactome mapping, suggest new targets and combination therapies that could circumvent EGFR TKI resistance.

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

PubMed

Alanis-Lobato, Gregorio

2015-01-01

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.

SH3 interactome conserves general function over specific form

PubMed Central

Xin, Xiaofeng; Gfeller, David; Cheng, Jackie; Tonikian, Raffi; Sun, Lin; Guo, Ailan; Lopez, Lianet; Pavlenco, Alevtina; Akintobi, Adenrele; Zhang, Yingnan; Rual, Jean-François; Currell, Bridget; Seshagiri, Somasekar; Hao, Tong; Yang, Xinping; Shen, Yun A; Salehi-Ashtiani, Kourosh; Li, Jingjing; Cheng, Aaron T; Bouamalay, Dryden; Lugari, Adrien; Hill, David E; Grimes, Mark L; Drubin, David G; Grant, Barth D; Vidal, Marc; Boone, Charles; Sidhu, Sachdev S; Bader, Gary D

2013-01-01

Src homology 3 (SH3) domains bind peptides to mediate protein–protein interactions that assemble and regulate dynamic biological processes. We surveyed the repertoire of SH3 binding specificity using peptide phage display in a metazoan, the worm Caenorhabditis elegans, and discovered that it structurally mirrors that of the budding yeast Saccharomyces cerevisiae. We then mapped the worm SH3 interactome using stringent yeast two-hybrid and compared it with the equivalent map for yeast. We found that the worm SH3 interactome resembles the analogous yeast network because it is significantly enriched for proteins with roles in endocytosis. Nevertheless, orthologous SH3 domain-mediated interactions are highly rewired. Our results suggest a model of network evolution where general function of the SH3 domain network is conserved over its specific form. PMID:23549480

The Activation-Induced Assembly of an RNA/Protein Interactome Centered on the Splicing Factor U2AF2 Regulates Gene Expression in Human CD4 T Cells.

PubMed

Whisenant, Thomas C; Peralta, Eigen R; Aarreberg, Lauren D; Gao, Nina J; Head, Steven R; Ordoukhanian, Phillip; Williamson, Jamie R; Salomon, Daniel R

2015-01-01

Activation of CD4 T cells is a reaction to challenges such as microbial pathogens, cancer and toxins that defines adaptive immune responses. The roles of T cell receptor crosslinking, intracellular signaling, and transcription factor activation are well described, but the importance of post-transcriptional regulation by RNA-binding proteins (RBPs) has not been considered in depth. We describe a new model expanding and activating primary human CD4 T cells and applied this to characterizing activation-induced assembly of splicing factors centered on U2AF2. We immunoprecipitated U2AF2 to identify what mRNA transcripts were bound as a function of activation by TCR crosslinking and costimulation. In parallel, mass spectrometry revealed the proteins incorporated into the U2AF2-centered RNA/protein interactome. Molecules that retained interaction with the U2AF2 complex after RNAse treatment were designated as "central" interactome members (CIMs). Mass spectrometry also identified a second class of activation-induced proteins, "peripheral" interactome members (PIMs), that bound to the same transcripts but were not in physical association with U2AF2 or its partners. siRNA knockdown of two CIMs and two PIMs caused changes in activation marker expression, cytokine secretion, and gene expression that were unique to each protein and mapped to pathways associated with key aspects of T cell activation. While knocking down the PIM, SYNCRIP, impacts a limited but immunologically important set of U2AF2-bound transcripts, knockdown of U2AF1 significantly impairs assembly of the majority of protein and mRNA components in the activation-induced interactome. These results demonstrated that CIMs and PIMs, either directly or indirectly through RNA, assembled into activation-induced U2AF2 complexes and play roles in post-transcriptional regulation of genes related to cytokine secretion. These data suggest an additional layer of regulation mediated by the activation-induced assembly of RNA splicing interactomes that is important for understanding T cell activation.

The Activation-Induced Assembly of an RNA/Protein Interactome Centered on the Splicing Factor U2AF2 Regulates Gene Expression in Human CD4 T Cells

PubMed Central

Aarreberg, Lauren D.; Gao, Nina J.; Head, Steven R.; Ordoukhanian, Phillip; Williamson, Jamie R.; Salomon, Daniel R.

2015-01-01

Activation of CD4 T cells is a reaction to challenges such as microbial pathogens, cancer and toxins that defines adaptive immune responses. The roles of T cell receptor crosslinking, intracellular signaling, and transcription factor activation are well described, but the importance of post-transcriptional regulation by RNA-binding proteins (RBPs) has not been considered in depth. We describe a new model expanding and activating primary human CD4 T cells and applied this to characterizing activation-induced assembly of splicing factors centered on U2AF2. We immunoprecipitated U2AF2 to identify what mRNA transcripts were bound as a function of activation by TCR crosslinking and costimulation. In parallel, mass spectrometry revealed the proteins incorporated into the U2AF2-centered RNA/protein interactome. Molecules that retained interaction with the U2AF2 complex after RNAse treatment were designated as “central” interactome members (CIMs). Mass spectrometry also identified a second class of activation-induced proteins, “peripheral” interactome members (PIMs), that bound to the same transcripts but were not in physical association with U2AF2 or its partners. siRNA knockdown of two CIMs and two PIMs caused changes in activation marker expression, cytokine secretion, and gene expression that were unique to each protein and mapped to pathways associated with key aspects of T cell activation. While knocking down the PIM, SYNCRIP, impacts a limited but immunologically important set of U2AF2-bound transcripts, knockdown of U2AF1 significantly impairs assembly of the majority of protein and mRNA components in the activation-induced interactome. These results demonstrated that CIMs and PIMs, either directly or indirectly through RNA, assembled into activation-induced U2AF2 complexes and play roles in post-transcriptional regulation of genes related to cytokine secretion. These data suggest an additional layer of regulation mediated by the activation-induced assembly of RNA splicing interactomes that is important for understanding T cell activation. PMID:26641092

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

PubMed

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

2017-10-23

An organism's protein interactome, or complete network of protein-protein interactions, defines the protein complexes that drive cellular processes. Techniques for studying protein complexes have traditionally applied targeted strategies such as yeast two-hybrid or affinity purification-mass spectrometry to assess protein interactions. However, given the vast number of protein complexes, more scalable methods are necessary to accelerate interaction discovery and to construct whole interactomes. We recently developed a complementary technique based on the use of protein correlation profiling (PCP) and stable isotope labeling in amino acids in cell culture (SILAC) to assess chromatographic co-elution as evidence of interacting proteins. Importantly, PCP-SILAC is also capable of measuring protein interactions simultaneously under multiple biological conditions, allowing the detection of treatment-specific changes to an interactome. Given the uniqueness and high dimensionality of co-elution data, new tools are needed to compare protein elution profiles, control false discovery rates, and construct an accurate interactome. Here we describe a freely available bioinformatics pipeline, PrInCE, for the analysis of co-elution data. PrInCE is a modular, open-source library that is computationally inexpensive, able to use label and label-free data, and capable of detecting tens of thousands of protein-protein interactions. Using a machine learning approach, PrInCE offers greatly reduced run time, more predicted interactions at the same stringency, prediction of protein complexes, and greater ease of use over previous bioinformatics tools for co-elution data. PrInCE is implemented in Matlab (version R2017a). Source code and standalone executable programs for Windows and Mac OSX are available at https://github.com/fosterlab/PrInCE , where usage instructions can be found. An example dataset and output are also provided for testing purposes. PrInCE is the first fast and easy-to-use data analysis pipeline that predicts interactomes and protein complexes from co-elution data. PrInCE allows researchers without bioinformatics expertise to analyze high-throughput co-elution datasets.

Bioinformatics Analysis Reveals Distinct Molecular Characteristics of Hepatitis B-Related Hepatocellular Carcinomas from Very Early to Advanced Barcelona Clinic Liver Cancer Stages.

PubMed

Kong, Fan-Yun; Wei, Xiao; Zhou, Kai; Hu, Wei; Kou, Yan-Bo; You, Hong-Juan; Liu, Xiao-Mei; Zheng, Kui-Yang; Tang, Ren-Xian

2016-01-01

Hepatocellular carcinoma (HCC)is the fifth most common malignancy associated with high mortality. One of the risk factors for HCC is chronic hepatitis B virus (HBV) infection. The treatment strategy for the disease is dependent on the stage of HCC, and the Barcelona clinic liver cancer (BCLC) staging system is used in most HCC cases. However, the molecular characteristics of HBV-related HCC in different BCLC stages are still unknown. Using GSE14520 microarray data from HBV-related HCC cases with BCLC stages from 0 (very early stage) to C (advanced stage) in the gene expression omnibus (GEO) database, differentially expressed genes (DEGs), including common DEGs and unique DEGs in different BCLC stages, were identified. These DEGs were located on different chromosomes. The molecular functions and biology pathways of DEGs were identified by gene ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, and the interactome networks of DEGs were constructed using the NetVenn online tool. The results revealed that both common DEGs and stage-specific DEGs were associated with various molecular functions and were involved in special biological pathways. In addition, several hub genes were found in the interactome networks of DEGs. The identified DEGs and hub genes promote our understanding of the molecular mechanisms underlying the development of HBV-related HCC through the different BCLC stages, and might be used as staging biomarkers or molecular targets for the treatment of HCC with HBV infection.

What model organisms and interactomics can reveal about the genetics of human obesity.

PubMed

Williams, Michael J; Almén, Markus S; Fredriksson, Robert; Schiöth, Helgi B

2012-11-01

Genome-wide association studies have identified a number of genes associated with human body weight. While some of these genes are large fields within obesity research, such as MC4R, POMC, FTO and BDNF, the majority do not have a clearly defined functional role explaining why they may affect body weight. Here, we searched biological databases and discovered 33 additional genes associated with human obesity (CADM2, GIPR, GPCR5B, LRP1B, NEGR1, NRXN3, SH2B1, FANCL, GNPDA2, HMGCR, MAP2K5, NUDT3, PRKD1, QPCTL, TNNI3K, MTCH2, DNAJC27, SLC39A8, MTIF3, RPL27A, SEC16B, ETV5, HMGA1, TFAP2B, TUB, ZNF608, FAIM2, KCTD15, LINGO2, POC5, PTBP2, TMEM18, TMEM160). We find that the majority have orthologues in distant species, such as D. melanogaster and C. elegans, suggesting that they are important for the biology of most bilateral species. Intriguingly, signalling cascade genes and transcription factors are enriched among these obesity genes, and several of the genes show properties that could be useful for potential drug discovery. In this review, we demonstrate how information from several distant model species, interactomics and signalling pathway analysis represents an important way to better understand the functional diversity of the surprisingly high number of molecules that seem to be important for human obesity.

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

PubMed Central

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

2015-01-01

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

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

PubMed

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

2014-01-01

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

Expression of DISC1-Interactome Members Correlates with Cognitive Phenotypes Related to Schizophrenia

PubMed Central

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

2014-01-01

Cognitive dysfunction is central to the schizophrenia phenotype. Genetic and functional studies have implicated Disrupted-in-Schizophrenia 1 (DISC1), a leading candidate gene for schizophrenia and related psychiatric conditions, in cognitive function. Altered expression of DISC1 and DISC1-interactors has been identified in schizophrenia. Dysregulated expression of DISC1-interactome genes might, therefore, contribute to schizophrenia susceptibility via disruption of molecular systems required for normal cognitive function. Here, the blood RNA expression levels of DISC1 and DISC1-interacting proteins were measured in 63 control subjects. Cognitive function was assessed using neuropsychiatric tests and functional magnetic resonance imaging was used to assess the activity of prefrontal cortical regions during the N-back working memory task, which is abnormal in schizophrenia. Pairwise correlations between gene expression levels and the relationship between gene expression levels and cognitive function and N-back-elicited brain activity were assessed. Finally, the expression levels of DISC1, AKAP9, FEZ1, NDEL1 and PCM1 were compared between 63 controls and 69 schizophrenic subjects. We found that DISC1-interactome genes showed correlated expression in the blood of healthy individuals. The expression levels of several interactome members were correlated with cognitive performance and N-back-elicited activity in the prefrontal cortex. In addition, DISC1 and NDEL1 showed decreased expression in schizophrenic subjects compared to healthy controls. Our findings highlight the importance of the coordinated expression of DISC1-interactome genes for normal cognitive function and suggest that dysregulated DISC1 and NDEL1 expression might, in part, contribute to susceptibility for schizophrenia via disruption of prefrontal cortex-dependent cognitive functions. PMID:24940743

Rewiring of the inferred protein interactome during blood development studied with the tool PPICompare.

PubMed

Will, Thorsten; Helms, Volkhard

2017-04-04

Differential analysis of cellular conditions is a key approach towards understanding the consequences and driving causes behind biological processes such as developmental transitions or diseases. The progress of whole-genome expression profiling enabled to conveniently capture the state of a cell's transcriptome and to detect the characteristic features that distinguish cells in specific conditions. In contrast, mapping the physical protein interactome for many samples is experimentally infeasible at the moment. For the understanding of the whole system, however, it is equally important how the interactions of proteins are rewired between cellular states. To overcome this deficiency, we recently showed how condition-specific protein interaction networks that even consider alternative splicing can be inferred from transcript expression data. Here, we present the differential network analysis tool PPICompare that was specifically designed for isoform-sensitive protein interaction networks. Besides detecting significant rewiring events between the interactomes of grouped samples, PPICompare infers which alterations to the transcriptome caused each rewiring event and what is the minimal set of alterations necessary to explain all between-group changes. When applied to the development of blood cells, we verified that a reasonable amount of rewiring events were reported by the tool and found that differential gene expression was the major determinant of cellular adjustments to the interactome. Alternative splicing events were consistently necessary in each developmental step to explain all significant alterations and were especially important for rewiring in the context of transcriptional control. Applying PPICompare enabled us to investigate the dynamics of the human protein interactome during developmental transitions. A platform-independent implementation of the tool PPICompare is available at https://sourceforge.net/projects/ppicompare/ .

Towards Personalized Medicine Mediated by in Vitro Virus-Based Interactome Approaches

PubMed Central

Ohashi, Hiroyuki; Miyamoto-Sato, Etsuko

2014-01-01

We have developed a simple in vitro virus (IVV) selection system based on cell-free co-translation, using a highly stable and efficient mRNA display method. The IVV system is applicable to the high-throughput and comprehensive analysis of proteins and protein–ligand interactions. Huge amounts of genomic sequence data have been generated over the last decade. The accumulated genetic alterations and the interactome networks identified within cells represent a universal feature of a disease, and knowledge of these aspects can help to determine the optimal therapy for the disease. The concept of the “integrome” has been developed as a means of integrating large amounts of data. We have developed an interactome analysis method aimed at providing individually-targeted health care. We also consider future prospects for this system. PMID:24756093

Preparation of Gap Junctions in Membrane Microdomains for Immunoprecipitation and Mass Spectrometry Interactome Analysis.

PubMed

Fowler, Stephanie; Akins, Mark; Bennett, Steffany A L

2016-01-01

Protein interaction networks at gap junction plaques are increasingly implicated in a variety of intracellular signaling cascades. Identifying protein interactions of integral membrane proteins is a valuable tool for determining channel function. However, several technical challenges exist. Subcellular fractionation of the bait protein matrix is usually required to identify less abundant proteins in complex homogenates. Sufficient solvation of the lipid environment without perturbation of the protein interactome must also be achieved. The present chapter describes the flotation of light and heavy liver tissue membrane microdomains to facilitate the identification and analysis of endogenous gap junction proteins and includes technical notes for translation to other integral membrane proteins, tissues, or cell culture models. These procedures are valuable tools for the enrichment of gap junction membrane compartments and for the identification of gap junction signaling interactomes.

In silico prediction of protein-protein interactions in human macrophages

PubMed Central

2014-01-01

Background Protein-protein interaction (PPI) network analyses are highly valuable in deciphering and understanding the intricate organisation of cellular functions. Nevertheless, the majority of available protein-protein interaction networks are context-less, i.e. without any reference to the spatial, temporal or physiological conditions in which the interactions may occur. In this work, we are proposing a protocol to infer the most likely protein-protein interaction (PPI) network in human macrophages. Results We integrated the PPI dataset from the Agile Protein Interaction DataAnalyzer (APID) with different meta-data to infer a contextualized macrophage-specific interactome using a combination of statistical methods. The obtained interactome is enriched in experimentally verified interactions and in proteins involved in macrophage-related biological processes (i.e. immune response activation, regulation of apoptosis). As a case study, we used the contextualized interactome to highlight the cellular processes induced upon Mycobacterium tuberculosis infection. Conclusion Our work confirms that contextualizing interactomes improves the biological significance of bioinformatic analyses. More specifically, studying such inferred network rather than focusing at the gene expression level only, is informative on the processes involved in the host response. Indeed, important immune features such as apoptosis are solely highlighted when the spotlight is on the protein interaction level. PMID:24636261

Comparative analysis of protein interactome networks prioritizes candidate genes with cancer signatures.

PubMed

Li, Yongsheng; Sahni, Nidhi; Yi, Song

2016-11-29

Comprehensive understanding of human cancer mechanisms requires the identification of a thorough list of cancer-associated genes, which could serve as biomarkers for diagnoses and therapies in various types of cancer. Although substantial progress has been made in functional studies to uncover genes involved in cancer, these efforts are often time-consuming and costly. Therefore, it remains challenging to comprehensively identify cancer candidate genes. Network-based methods have accelerated this process through the analysis of complex molecular interactions in the cell. However, the extent to which various interactome networks can contribute to prediction of candidate genes responsible for cancer is still enigmatic. In this study, we evaluated different human protein-protein interactome networks and compared their application to cancer gene prioritization. Our results indicate that network analyses can increase the power to identify novel cancer genes. In particular, such predictive power can be enhanced with the use of unbiased systematic protein interaction maps for cancer gene prioritization. Functional analysis reveals that the top ranked genes from network predictions co-occur often with cancer-related terms in literature, and further, these candidate genes are indeed frequently mutated across cancers. Finally, our study suggests that integrating interactome networks with other omics datasets could provide novel insights into cancer-associated genes and underlying molecular mechanisms.

High-Confidence Interactome for RNF41 Built on Multiple Orthogonal Assays.

PubMed

Masschaele, Delphine; Wauman, Joris; Vandemoortele, Giel; De Sutter, Delphine; De Ceuninck, Leentje; Eyckerman, Sven; Tavernier, Jan

2018-04-06

Ring finger protein 41 (RNF41) is an E3 ubiquitin ligase involved in the ubiquitination and degradation of many proteins including ErbB3 receptors, BIRC6, and parkin. Next to this, RNF41 regulates the intracellular trafficking of certain JAK2-associated cytokine receptors by ubiquitinating and suppressing USP8, which, in turn, destabilizes the ESCRT-0 complex. To further elucidate the function of RNF41 we used different orthogonal approaches to reveal the RNF41 protein complex: affinity purification-mass spectrometry, BioID, and Virotrap. We combined these results with known data sets for RNF41 obtained with microarray MAPPIT and Y2H screens. This way, we establish a comprehensive high-resolution interactome network comprising 175 candidate protein partners. To remove potential methodological artifacts from this network, we distilled the data into a high-confidence interactome map by retaining a total of 19 protein hits identified in two or more of the orthogonal methods. AP2S1, a novel RNF41 interaction partner, was selected from this high-confidence interactome for further functional validation. We reveal a role for AP2S1 in leptin and LIF receptor signaling and show that RNF41 stabilizes and relocates AP2S1.

mRNA interactome capture in mammalian cells.

PubMed

Kastelic, Nicolai; Landthaler, Markus

2017-08-15

Throughout their entire life cycle, mRNAs are associated with RNA-binding proteins (RBPs), forming ribonucleoprotein (RNP) complexes with highly dynamic compositions. Their interplay is one key to control gene regulatory mechanisms from mRNA synthesis to decay. To assay the global scope of RNA-protein interactions, we and others have published a method combining crosslinking with highly stringent oligo(dT) affinity purification to enrich proteins associated with polyadenylated RNA (poly(A)+ RNA). Identification of the poly(A)+ RNA-bound proteome (also: mRNA interactome capture) has by now been applied to a diversity of cell lines and model organisms, uncovering comprehensive repertoires of RBPs and hundreds of novel RBP candidates. In addition to determining the RBP catalog in a given biological system, mRNA interactome capture allows the examination of changes in protein-mRNA interactions in response to internal and external stimuli, altered cellular programs and disease. Copyright © 2017. Published by Elsevier Inc.

An in vivo proteomic analysis of the Me31B interactome in Drosophila germ granules.

PubMed

DeHaan, Hunter; McCambridge, Aidan; Armstrong, Brittany; Cruse, Carlie; Solanki, Dhruv; Trinidad, Jonathan C; Arkov, Alexey L; Gao, Ming

2017-11-01

Drosophila Me31B is a conserved protein of germ granules, ribonucleoprotein complexes essential for germ cell development. Me31B post-transcriptionally regulates mRNAs by interacting with other germ granule proteins. However, a Me31B interactome is lacking. Here, we use an in vivo proteomics approach to show that the Me31B interactome contains polypeptides from four functional groups: RNA regulatory proteins, glycolytic enzymes, cytoskeleton/motor proteins, and germ plasm components. We further show that Me31B likely colocalizes with the germ plasm components Tudor (Tud), Vasa, and Aubergine in the nuage and germ plasm and provide evidence that Me31B may directly bind to Tud in a symmetrically dimethylated arginine-dependent manner. Our study supports the role of Me31B in RNA regulation and suggests its novel roles in germ granule assembly and function. © 2017 Federation of European Biochemical Societies.

Serial interactome capture of the human cell nucleus.

PubMed

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

2016-04-04

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

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

PubMed

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

2018-01-16

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

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

Cancer.gov

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

Schizophrenia interactome with 504 novel protein–protein interactions

PubMed Central

Ganapathiraju, Madhavi K; Thahir, Mohamed; Handen, Adam; Sarkar, Saumendra N; Sweet, Robert A; Nimgaonkar, Vishwajit L; Loscher, Christine E; Bauer, Eileen M; Chaparala, Srilakshmi

2016-01-01

Genome-wide association studies of schizophrenia (GWAS) have revealed the role of rare and common genetic variants, but the functional effects of the risk variants remain to be understood. Protein interactome-based studies can facilitate the study of molecular mechanisms by which the risk genes relate to schizophrenia (SZ) genesis, but protein–protein interactions (PPIs) are unknown for many of the liability genes. We developed a computational model to discover PPIs, which is found to be highly accurate according to computational evaluations and experimental validations of selected PPIs. We present here, 365 novel PPIs of liability genes identified by the SZ Working Group of the Psychiatric Genomics Consortium (PGC). Seventeen genes that had no previously known interactions have 57 novel interactions by our method. Among the new interactors are 19 drug targets that are targeted by 130 drugs. In addition, we computed 147 novel PPIs of 25 candidate genes investigated in the pre-GWAS era. While there is little overlap between the GWAS genes and the pre-GWAS genes, the interactomes reveal that they largely belong to the same pathways, thus reconciling the apparent disparities between the GWAS and prior gene association studies. The interactome including 504 novel PPIs overall, could motivate other systems biology studies and trials with repurposed drugs. The PPIs are made available on a webserver, called Schizo-Pi at http://severus.dbmi.pitt.edu/schizo-pi with advanced search capabilities. PMID:27336055

A combined database related and de novo MS-identification of yeast mannose-1-phosphate guanyltransferase PSA1 interaction partners at different phases of batch cultivation

NASA Astrophysics Data System (ADS)

Parviainen, Ville; Joenväärä, Sakari; Peltoniemi, Hannu; Mattila, Pirkko; Renkonen, Risto

2009-04-01

Mass spectrometry-based proteomic research has become one of the main methods in protein-protein interaction research. Several high throughput studies have established an interaction landscape of exponentially growing Baker's yeast culture. However, many of the protein-protein interactions are likely to change in different environmental conditions. In order to examine the dynamic nature of the protein interactions we isolated the protein complexes of mannose-1-phosphate guanyltransferase PSA1 from Saccharomyces cerevisiae at four different time points during batch cultivation. We used the tandem affinity purification (TAP)-method to purify the complexes and subjected the tryptic peptides to LC-MS/MS. The resulting peak lists were analyzed with two different methods: the database related protein identification program X!Tandem and the de novo sequencing program Lutefisk. We observed significant changes in the interactome of PSA1 during the batch cultivation and identified altogether 74 proteins interacting with PSA1 of which only six were found to interact during all time points. All the other proteins showed a more dynamic nature of binding activity. In this study we also demonstrate the benefit of using both database related and de novo methods in the protein interaction research to enhance both the quality and the quantity of observations.

DenHunt - A Comprehensive Database of the Intricate Network of Dengue-Human Interactions

PubMed Central

Arjunan, Selvam; Sastri, Narayan P.; Chandra, Nagasuma

2016-01-01

Dengue virus (DENV) is a human pathogen and its etiology has been widely established. There are many interactions between DENV and human proteins that have been reported in literature. However, no publicly accessible resource for efficiently retrieving the information is yet available. In this study, we mined all publicly available dengue–human interactions that have been reported in the literature into a database called DenHunt. We retrieved 682 direct interactions of human proteins with dengue viral components, 382 indirect interactions and 4120 differentially expressed human genes in dengue infected cell lines and patients. We have illustrated the importance of DenHunt by mapping the dengue–human interactions on to the host interactome and observed that the virus targets multiple host functional complexes of important cellular processes such as metabolism, immune system and signaling pathways suggesting a potential role of these interactions in viral pathogenesis. We also observed that 7 percent of the dengue virus interacting human proteins are also associated with other infectious and non-infectious diseases. Finally, the understanding that comes from such analyses could be used to design better strategies to counteract the diseases caused by dengue virus. The whole dataset has been catalogued in a searchable database, called DenHunt (http://proline.biochem.iisc.ernet.in/DenHunt/). PMID:27618709

DenHunt - A Comprehensive Database of the Intricate Network of Dengue-Human Interactions.

PubMed

Karyala, Prashanthi; Metri, Rahul; Bathula, Christopher; Yelamanchi, Syam K; Sahoo, Lipika; Arjunan, Selvam; Sastri, Narayan P; Chandra, Nagasuma

2016-09-01

Dengue virus (DENV) is a human pathogen and its etiology has been widely established. There are many interactions between DENV and human proteins that have been reported in literature. However, no publicly accessible resource for efficiently retrieving the information is yet available. In this study, we mined all publicly available dengue-human interactions that have been reported in the literature into a database called DenHunt. We retrieved 682 direct interactions of human proteins with dengue viral components, 382 indirect interactions and 4120 differentially expressed human genes in dengue infected cell lines and patients. We have illustrated the importance of DenHunt by mapping the dengue-human interactions on to the host interactome and observed that the virus targets multiple host functional complexes of important cellular processes such as metabolism, immune system and signaling pathways suggesting a potential role of these interactions in viral pathogenesis. We also observed that 7 percent of the dengue virus interacting human proteins are also associated with other infectious and non-infectious diseases. Finally, the understanding that comes from such analyses could be used to design better strategies to counteract the diseases caused by dengue virus. The whole dataset has been catalogued in a searchable database, called DenHunt (http://proline.biochem.iisc.ernet.in/DenHunt/).

APP is cleaved by Bace1 in pre-synaptic vesicles and establishes a pre-synaptic interactome, via its intracellular domain, with molecular complexes that regulate pre-synaptic vesicles functions.

PubMed

Del Prete, Dolores; Lombino, Franco; Liu, Xinran; D'Adamio, Luciano

2014-01-01

Amyloid Precursor Protein (APP) is a type I membrane protein that undergoes extensive processing by secretases, including BACE1. Although mutations in APP and genes that regulate processing of APP, such as PSENs and BRI2/ITM2B, cause dementias, the normal function of APP in synaptic transmission, synaptic plasticity and memory formation is poorly understood. To grasp the biochemical mechanisms underlying the function of APP in the central nervous system, it is important to first define the sub-cellular localization of APP in synapses and the synaptic interactome of APP. Using biochemical and electron microscopy approaches, we have found that APP is localized in pre-synaptic vesicles, where it is processed by Bace1. By means of a proteomic approach, we have characterized the synaptic interactome of the APP intracellular domain. We focused on this region of APP because in vivo data underline the central functional and pathological role of the intracellular domain of APP. Consistent with the expression of APP in pre-synaptic vesicles, the synaptic APP intracellular domain interactome is predominantly constituted by pre-synaptic, rather than post-synaptic, proteins. This pre-synaptic interactome of the APP intracellular domain includes proteins expressed on pre-synaptic vesicles such as the vesicular SNARE Vamp2/Vamp1 and the Ca2+ sensors Synaptotagmin-1/Synaptotagmin-2, and non-vesicular pre-synaptic proteins that regulate exocytosis, endocytosis and recycling of pre-synaptic vesicles, such as target-membrane-SNAREs (Syntaxin-1b, Syntaxin-1a, Snap25 and Snap47), Munc-18, Nsf, α/β/γ-Snaps and complexin. These data are consistent with a functional role for APP, via its carboxyl-terminal domain, in exocytosis, endocytosis and/or recycling of pre-synaptic vesicles.

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

PubMed

Xu, Yungang; Guo, Maozu; Zou, Quan; Liu, Xiaoyan; Wang, Chunyu; Liu, Yang

2014-01-01

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

System-Level Insights into the Cellular Interactome of a Non-Model Organism: Inferring, Modelling and Analysing Functional Gene Network of Soybean (Glycine max)

PubMed Central

Xu, Yungang; Guo, Maozu; Zou, Quan; Liu, Xiaoyan; Wang, Chunyu; Liu, Yang

2014-01-01

Cellular interactome, in which genes and/or their products interact on several levels, forming transcriptional regulatory-, protein interaction-, metabolic-, signal transduction networks, etc., has attracted decades of research focuses. However, such a specific type of network alone can hardly explain the various interactive activities among genes. These networks characterize different interaction relationships, implying their unique intrinsic properties and defects, and covering different slices of biological information. Functional gene network (FGN), a consolidated interaction network that models fuzzy and more generalized notion of gene-gene relations, have been proposed to combine heterogeneous networks with the goal of identifying functional modules supported by multiple interaction types. There are yet no successful precedents of FGNs on sparsely studied non-model organisms, such as soybean (Glycine max), due to the absence of sufficient heterogeneous interaction data. We present an alternative solution for inferring the FGNs of soybean (SoyFGNs), in a pioneering study on the soybean interactome, which is also applicable to other organisms. SoyFGNs exhibit the typical characteristics of biological networks: scale-free, small-world architecture and modularization. Verified by co-expression and KEGG pathways, SoyFGNs are more extensive and accurate than an orthology network derived from Arabidopsis. As a case study, network-guided disease-resistance gene discovery indicates that SoyFGNs can provide system-level studies on gene functions and interactions. This work suggests that inferring and modelling the interactome of a non-model plant are feasible. It will speed up the discovery and definition of the functions and interactions of other genes that control important functions, such as nitrogen fixation and protein or lipid synthesis. The efforts of the study are the basis of our further comprehensive studies on the soybean functional interactome at the genome and microRNome levels. Additionally, a web tool for information retrieval and analysis of SoyFGNs can be accessed at SoyFN: http://nclab.hit.edu.cn/SoyFN. PMID:25423109

Exploring the cellular basis of human disease through a large-scale mapping of deleterious genes to cell types.

PubMed

Cornish, Alex J; Filippis, Ioannis; David, Alessia; Sternberg, Michael J E

2015-09-01

Each cell type found within the human body performs a diverse and unique set of functions, the disruption of which can lead to disease. However, there currently exists no systematic mapping between cell types and the diseases they can cause. In this study, we integrate protein-protein interaction data with high-quality cell-type-specific gene expression data from the FANTOM5 project to build the largest collection of cell-type-specific interactomes created to date. We develop a novel method, called gene set compactness (GSC), that contrasts the relative positions of disease-associated genes across 73 cell-type-specific interactomes to map genes associated with 196 diseases to the cell types they affect. We conduct text-mining of the PubMed database to produce an independent resource of disease-associated cell types, which we use to validate our method. The GSC method successfully identifies known disease-cell-type associations, as well as highlighting associations that warrant further study. This includes mast cells and multiple sclerosis, a cell population currently being targeted in a multiple sclerosis phase 2 clinical trial. Furthermore, we build a cell-type-based diseasome using the cell types identified as manifesting each disease, offering insight into diseases linked through etiology. The data set produced in this study represents the first large-scale mapping of diseases to the cell types in which they are manifested and will therefore be useful in the study of disease systems. Overall, we demonstrate that our approach links disease-associated genes to the phenotypes they produce, a key goal within systems medicine.

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

PubMed

Li, Shuxian; Musungu, Bryan; Lightfoot, David; Ji, Pingsheng

2018-01-01

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

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

PubMed Central

Li, Shuxian; Musungu, Bryan; Lightfoot, David; Ji, Pingsheng

2018-01-01

Phomopsis longicolla T. W. Hobbs (syn. Diaporthe longicolla) is the primary cause of Phomopsis seed decay (PSD) in soybean, Glycine max (L.) Merrill. This disease results in poor seed quality and is one of the most economically important seed diseases in soybean. The objectives of this study were to infer protein–protein interactions (PPI) and to identify conserved global networks and pathogenicity subnetworks in P. longicolla including orthologous pathways for cell signaling and pathogenesis. The interlog method used in the study identified 215,255 unique PPIs among 3,868 proteins. There were 1,414 pathogenicity related genes in P. longicolla identified using the pathogen host interaction (PHI) database. Additionally, 149 plant cell wall degrading enzymes (PCWDE) were detected. The network captured five different classes of carbohydrate degrading enzymes, including the auxiliary activities, carbohydrate esterases, glycoside hydrolases, glycosyl transferases, and carbohydrate binding molecules. From the PPI analysis, novel interacting partners were determined for each of the PCWDE classes. The most predominant class of PCWDE was a group of 60 glycoside hydrolases proteins. The glycoside hydrolase subnetwork was found to be interacting with 1,442 proteins within the network and was among the largest clusters. The orthologous proteins FUS3, HOG, CYP1, SGE1, and the g5566t.1 gene identified in this study could play an important role in pathogenicity. Therefore, the P. longicolla protein interactome (PiPhom) generated in this study can lead to a better understanding of PPIs in soybean pathogens. Furthermore, the PPI may aid in targeting of genes and proteins for further studies of the pathogenicity mechanisms. PMID:29666630

A bioinformatic and mechanistic study elicits the antifibrotic effect of ursolic acid through the attenuation of oxidative stress with the involvement of ERK, PI3K/Akt, and p38 MAPK signaling pathways in human hepatic stellate cells and rat liver

PubMed Central

He, Wenhua; Shi, Feng; Zhou, Zhi-Wei; Li, Bimin; Zhang, Kunhe; Zhang, Xinhua; Ouyang, Canhui; Zhou, Shu-Feng; Zhu, Xuan

2015-01-01

NADPH oxidases (NOXs) are a predominant mediator of redox homeostasis in hepatic stellate cells (HSCs), and oxidative stress plays an important role in the pathogenesis of liver fibrosis. Ursolic acid (UA) is a pentacyclic triterpenoid with various pharmacological activities, but the molecular targets and underlying mechanisms for its antifibrotic effect in the liver remain elusive. This study aimed to computationally predict the molecular interactome and mechanistically investigate the antifibrotic effect of UA on oxidative stress, with a focus on NOX4 activity and cross-linked signaling pathways in human HSCs and rat liver. Drug–drug interaction via chemical–protein interactome tool, a server that can predict drug–drug interaction via chemical–protein interactome, was used to predict the molecular targets of UA, and Database for Annotation, Visualization, and Integrated Discovery was employed to analyze the signaling pathways of the predicted targets of UA. The bioinformatic data showed that there were 611 molecular proteins possibly interacting with UA and that there were over 49 functional clusters responding to UA. The subsequential benchmarking data showed that UA significantly reduced the accumulation of type I collagen in HSCs in rat liver, increased the expression level of MMP-1, but decreased the expression level of TIMP-1 in HSC-T6 cells. UA also remarkably reduced the gene expression level of type I collagen in HSC-T6 cells. Furthermore, UA remarkably attenuated oxidative stress via negative regulation of NOX4 activity and expression in HSC-T6 cells. The employment of specific chemical inhibitors, SB203580, LY294002, PD98059, and AG490, demonstrated the involvement of ERK, PI3K/Akt, and p38 MAPK signaling pathways in the regulatory effect of UA on NOX4 activity and expression. Collectively, the antifibrotic effect of UA is partially due to the oxidative stress attenuating effect through manipulating NOX4 activity and expression. The results suggest that UA may act as a promising antifibrotic agent. More studies are warranted to evaluate the safety and efficacy of UA in the treatment of liver fibrosis. PMID:26347199

The human cytoplasmic dynein interactome reveals novel activators of motility

PubMed Central

Redwine, William B; DeSantis, Morgan E; Hollyer, Ian; Htet, Zaw Min; Tran, Phuoc Tien; Swanson, Selene K; Florens, Laurence; Washburn, Michael P; Reck-Peterson, Samara L

2017-01-01

In human cells, cytoplasmic dynein-1 is essential for long-distance transport of many cargos, including organelles, RNAs, proteins, and viruses, towards microtubule minus ends. To understand how a single motor achieves cargo specificity, we identified the human dynein interactome by attaching a promiscuous biotin ligase (‘BioID’) to seven components of the dynein machinery, including a subunit of the essential cofactor dynactin. This method reported spatial information about the large cytosolic dynein/dynactin complex in living cells. To achieve maximal motile activity and to bind its cargos, human dynein/dynactin requires ‘activators’, of which only five have been described. We developed methods to identify new activators in our BioID data, and discovered that ninein and ninein-like are a new family of dynein activators. Analysis of the protein interactomes for six activators, including ninein and ninein-like, suggests that each dynein activator has multiple cargos. DOI: http://dx.doi.org/10.7554/eLife.28257.001 PMID:28718761

Identification of the Interactome of a Palmitoylated Membrane Protein, Phosphatidylinositol 4-Kinase Type II Alpha.

PubMed

Gokhale, Avanti; Ryder, Pearl V; Zlatic, Stephanie A; Faundez, Victor

2016-01-01

Phosphatidylinositol 4-kinases (PI4K) are enzymes responsible for the production of phosphatidylinositol 4-phosphates, important intermediates in several cell signaling pathways. PI4KIIα is the most abundant membrane-associated kinase in mammalian cells and is involved in a variety of essential cellular functions. However, the precise role(s) of PI4KIIα in the cell is not yet completely deciphered. Here we present an experimental protocol that uses a chemical cross-linker, DSP, combined with immunoprecipitation and immunoaffinity purification to identify novel PI4KIIα interactors. As predicted, PI4KIIα participates in transient, low-affinity interactions that are stabilized by the use of DSP. Using this optimized protocol we have successfully identified actin cytoskeleton regulators-the WASH complex and RhoGEF1, as major novel interactors of PI4KIIα. While this chapter focuses on the PI4KIIα interactome, this protocol can and has been used to generate other membrane interactome networks.

A Proteome-wide Fission Yeast Interactome Reveals Network Evolution Principles from Yeasts to Human.

PubMed

Vo, Tommy V; Das, Jishnu; Meyer, Michael J; Cordero, Nicolas A; Akturk, Nurten; Wei, Xiaomu; Fair, Benjamin J; Degatano, Andrew G; Fragoza, Robert; Liu, Lisa G; Matsuyama, Akihisa; Trickey, Michelle; Horibata, Sachi; Grimson, Andrew; Yamano, Hiroyuki; Yoshida, Minoru; Roth, Frederick P; Pleiss, Jeffrey A; Xia, Yu; Yu, Haiyuan

2016-01-14

Here, we present FissionNet, a proteome-wide binary protein interactome for S. pombe, comprising 2,278 high-quality interactions, of which ∼ 50% were previously not reported in any species. FissionNet unravels previously unreported interactions implicated in processes such as gene silencing and pre-mRNA splicing. We developed a rigorous network comparison framework that accounts for assay sensitivity and specificity, revealing extensive species-specific network rewiring between fission yeast, budding yeast, and human. Surprisingly, although genes are better conserved between the yeasts, S. pombe interactions are significantly better conserved in human than in S. cerevisiae. Our framework also reveals that different modes of gene duplication influence the extent to which paralogous proteins are functionally repurposed. Finally, cross-species interactome mapping demonstrates that coevolution of interacting proteins is remarkably prevalent, a result with important implications for studying human disease in model organisms. Overall, FissionNet is a valuable resource for understanding protein functions and their evolution. Copyright © 2016 Elsevier Inc. All rights reserved.

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

PubMed

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

2017-02-14

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

Using neighborhood cohesiveness to infer interactions between protein domains.

PubMed

Segura, Joan; Sorzano, C O S; Cuenca-Alba, Jesus; Aloy, Patrick; Carazo, J M

2015-08-01

In recent years, large-scale studies have been undertaken to describe, at least partially, protein-protein interaction maps, or interactomes, for a number of relevant organisms, including human. However, current interactomes provide a somehow limited picture of the molecular details involving protein interactions, mostly because essential experimental information, especially structural data, is lacking. Indeed, the gap between structural and interactomics information is enlarging and thus, for most interactions, key experimental information is missing. We elaborate on the observation that many interactions between proteins involve a pair of their constituent domains and, thus, the knowledge of how protein domains interact adds very significant information to any interactomic analysis. In this work, we describe a novel use of the neighborhood cohesiveness property to infer interactions between protein domains given a protein interaction network. We have shown that some clustering coefficients can be extended to measure a degree of cohesiveness between two sets of nodes within a network. Specifically, we used the meet/min coefficient to measure the proportion of interacting nodes between two sets of nodes and the fraction of common neighbors. This approach extends previous works where homolog coefficients were first defined around network nodes and later around edges. The proposed approach substantially increases both the number of predicted domain-domain interactions as well as its accuracy as compared with current methods. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

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

PubMed

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

2018-02-01

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

Comprehensive Identification of mRNA-Binding Proteins of Leishmania donovani by Interactome Capture.

PubMed

Nandan, Devki; Thomas, Sneha A; Nguyen, Anne; Moon, Kyung-Mee; Foster, Leonard J; Reiner, Neil E

2017-01-01

Leishmania are unicellular eukaryotes responsible for leishmaniasis in humans. Like other trypanosomatids, leishmania regulate protein coding gene expression almost exclusively at the post-transcriptional level with the help of RNA binding proteins (RBPs). Due to the presence of polycystronic transcription units, leishmania do not regulate RNA polymerase II-dependent transcription initiation. Recent evidence suggests that the main control points in gene expression are mRNA degradation and translation. Protein-RNA interactions are involved in every aspect of RNA biology, such as mRNA splicing, polyadenylation, localization, degradation, and translation. A detailed picture of these interactions would likely prove to be highly informative in understanding leishmania biology and virulence. We developed a strategy involving covalent UV cross-linking of RBPs to mRNA in vivo, followed by interactome capture using oligo(dT) magnetic beads to define comprehensively the mRNA interactome of growing L. donovani amastigotes. The protein mass spectrometry analysis of captured proteins identified 79 mRNA interacting proteins which withstood very stringent washing conditions. Strikingly, we found that 49 of these mRNA interacting proteins had no orthologs or homologs in the human genome. Consequently, these may represent high quality candidates for selective drug targeting leading to novel therapeutics. These results show that this unbiased, systematic strategy has the promise to be applicable to study the mRNA interactome during various biological settings such as metabolic changes, stress (low pH environment, oxidative stress and nutrient deprivation) or drug treatment.

A meta-analysis to evaluate the cellular processes regulated by the interactome of endogenous and over-expressed estrogen receptor alpha.

PubMed

Simões, Joana; Amado, Francisco M; Vitorino, Rui; Helguero, Luisa A

2015-01-01

The nature of the proteins complexes that regulate ERα subcellular localization and activity is still an open question in breast cancer biology. Identification of such complexes will help understand development of endocrine resistance in ER+ breast cancer. Mass spectrometry (MS) has allowed comprehensive analysis of the ERα interactome. We have compared six published works analyzing the ERα interactome of MCF-7 and HeLa cells in order to identify a shared or different pathway-related fingerprint. Overall, 806 ERα interacting proteins were identified. The cellular processes were differentially represented according to the ERα purification methodology, indicating that the methodologies used are complementary. While in MCF-7 cells, the interactome of endogenous and over-expressed ERα essentially represents the same biological processes and cellular components, the proteins identified were not over-lapping; thus, suggesting that the biological response may differ as the regulatory/participating proteins in these complexes are different. Interestingly, biological processes uniquely associated to ERα over-expressed in HeLa cell line included L-serine biosynthetic process, cellular amino acid biosynthetic process and cell redox homeostasis. In summary, all the approaches analyzed in this meta-analysis are valid and complementary; in particular, for those cases where the processes occur at low frequency with normal ERα levels, and can be identified when the receptor is over-expressed. However special effort should be put into validating these findings in cells expressing physiological ERα levels.

Characterization of the Cardiac Overexpression of HSPB2 Reveals Mitochondrial and Myogenic Roles Supported by a Cardiac HspB2 Interactome.

PubMed

Grose, Julianne H; Langston, Kelsey; Wang, Xiaohui; Squires, Shayne; Mustafi, Soumyajit Banerjee; Hayes, Whitney; Neubert, Jonathan; Fischer, Susan K; Fasano, Matthew; Saunders, Gina Moore; Dai, Qiang; Christians, Elisabeth; Lewandowski, E Douglas; Ping, Peipei; Benjamin, Ivor J

2015-01-01

Small Heat Shock Proteins (sHSPs) are molecular chaperones that transiently interact with other proteins, thereby assisting with quality control of proper protein folding and/or degradation. They are also recruited to protect cells from a variety of stresses in response to extreme heat, heavy metals, and oxidative-reductive stress. Although ten human sHSPs have been identified, their likely diverse biological functions remain an enigma in health and disease, and much less is known about non-redundant roles in selective cells and tissues. Herein, we set out to comprehensively characterize the cardiac-restricted Heat Shock Protein B-2 (HspB2), which exhibited ischemic cardioprotection in transgenic overexpressing mice including reduced infarct size and maintenance of ATP levels. Global yeast two-hybrid analysis using HspB2 (bait) and a human cardiac library (prey) coupled with co-immunoprecipitation studies for mitochondrial target validation revealed the first HspB2 "cardiac interactome" to contain many myofibril and mitochondrial-binding partners consistent with the overexpression phenotype. This interactome has been submitted to the Biological General Repository for Interaction Datasets (BioGRID). A related sHSP chaperone HspB5 had only partially overlapping binding partners, supporting specificity of the interactome as well as non-redundant roles reported for these sHSPs. Evidence that the cardiac yeast two-hybrid HspB2 interactome targets resident mitochondrial client proteins is consistent with the role of HspB2 in maintaining ATP levels and suggests new chaperone-dependent functions for metabolic homeostasis. One of the HspB2 targets, glyceraldehyde 3-phosphate dehydrogenase (GAPDH), has reported roles in HspB2 associated phenotypes including cardiac ATP production, mitochondrial function, and apoptosis, and was validated as a potential client protein of HspB2 through chaperone assays. From the clientele and phenotypes identified herein, it is tempting to speculate that small molecule activators of HspB2 might be deployed to mitigate mitochondrial related diseases such as cardiomyopathy and neurodegenerative disease.

The cell-cycle interactome: a source of growth regulators?

PubMed

Blomme, Jonas; Inzé, Dirk; Gonzalez, Nathalie

2014-06-01

When plants develop, cell proliferation and cell expansion are tightly controlled in order to generate organs with a determinate final size such as leaves. Several studies have demonstrated the importance of the cell proliferation phase for leaf growth, illustrating that cell-cycle regulation is crucial for correct leaf development. A large and complex set of interacting proteins that constitute the cell-cycle interactome controls the transition from one cell-cycle phase to another. Here, we review the current knowledge on cell-cycle regulators from this interactome affecting final leaf size when their expression is altered, mainly in Arabidopsis. In addition to the description of mutants of CYCLIN-DEPENDENT KINASES (CDKs), CYCLINS (CYCs), and their transcriptional and post-translational regulators, a phenotypic analysis of gain- and loss-of-function mutants for 27 genes encoding proteins that interact with cell-cycle proteins is presented. This compilation of information shows that when cell-cycle-related genes are mis-expressed, leaf growth is often altered and that, seemingly, three main trends appear to be crucial in the regulation of final organ size by cell-cycle-related genes: (i) cellular compensation; (ii) gene dosage; and (iii) correct transition through the G2/M phase by ANAPHASE PROMOTING COMPLEX/CYCLOSOME (APC/C) activation. In conclusion, this meta-analysis shows that the cell-cycle interactome is enriched in leaf growth regulators, and illustrates the potential to identify new leaf growth regulators among putative new cell-cycle regulators. © The Author 2013. Published by Oxford University Press on behalf of the Society for Experimental Biology. All rights reserved. For permissions, please email: journals.permissions@oup.com.

A “Candidate-Interactome” Aggregate Analysis of Genome-Wide Association Data in Multiple Sclerosis

PubMed Central

Policano, Claudia; Annibali, Viviana; Coarelli, Giulia; Ricigliano, Vito A. G.; Vittori, Danila; Fornasiero, Arianna; Buscarinu, Maria Chiara; Romano, Silvia; Salvetti, Marco; Ristori, Giovanni

2013-01-01

Though difficult, the study of gene-environment interactions in multifactorial diseases is crucial for interpreting the relevance of non-heritable factors and prevents from overlooking genetic associations with small but measurable effects. We propose a “candidate interactome” (i.e. a group of genes whose products are known to physically interact with environmental factors that may be relevant for disease pathogenesis) analysis of genome-wide association data in multiple sclerosis. We looked for statistical enrichment of associations among interactomes that, at the current state of knowledge, may be representative of gene-environment interactions of potential, uncertain or unlikely relevance for multiple sclerosis pathogenesis: Epstein-Barr virus, human immunodeficiency virus, hepatitis B virus, hepatitis C virus, cytomegalovirus, HHV8-Kaposi sarcoma, H1N1-influenza, JC virus, human innate immunity interactome for type I interferon, autoimmune regulator, vitamin D receptor, aryl hydrocarbon receptor and a panel of proteins targeted by 70 innate immune-modulating viral open reading frames from 30 viral species. Interactomes were either obtained from the literature or were manually curated. The P values of all single nucleotide polymorphism mapping to a given interactome were obtained from the last genome-wide association study of the International Multiple Sclerosis Genetics Consortium & the Wellcome Trust Case Control Consortium, 2. The interaction between genotype and Epstein Barr virus emerges as relevant for multiple sclerosis etiology. However, in line with recent data on the coexistence of common and unique strategies used by viruses to perturb the human molecular system, also other viruses have a similar potential, though probably less relevant in epidemiological terms. PMID:23696811

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

PubMed Central

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

2013-01-01

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

Mapping transcription factor interactome networks using HaloTag protein arrays.

PubMed

Yazaki, Junshi; Galli, Mary; Kim, Alice Y; Nito, Kazumasa; Aleman, Fernando; Chang, Katherine N; Carvunis, Anne-Ruxandra; Quan, Rosa; Nguyen, Hien; Song, Liang; Alvarez, José M; Huang, Shao-Shan Carol; Chen, Huaming; Ramachandran, Niroshan; Altmann, Stefan; Gutiérrez, Rodrigo A; Hill, David E; Schroeder, Julian I; Chory, Joanne; LaBaer, Joshua; Vidal, Marc; Braun, Pascal; Ecker, Joseph R

2016-07-19

Protein microarrays enable investigation of diverse biochemical properties for thousands of proteins in a single experiment, an unparalleled capacity. Using a high-density system called HaloTag nucleic acid programmable protein array (HaloTag-NAPPA), we created high-density protein arrays comprising 12,000 Arabidopsis ORFs. We used these arrays to query protein-protein interactions for a set of 38 transcription factors and transcriptional regulators (TFs) that function in diverse plant hormone regulatory pathways. The resulting transcription factor interactome network, TF-NAPPA, contains thousands of novel interactions. Validation in a benchmarked in vitro pull-down assay revealed that a random subset of TF-NAPPA validated at the same rate of 64% as a positive reference set of literature-curated interactions. Moreover, using a bimolecular fluorescence complementation (BiFC) assay, we confirmed in planta several interactions of biological interest and determined the interaction localizations for seven pairs. The application of HaloTag-NAPPA technology to plant hormone signaling pathways allowed the identification of many novel transcription factor-protein interactions and led to the development of a proteome-wide plant hormone TF interactome network.

Bacterial interactomes: Interacting protein partners share similar function and are validated in independent assays more frequently than previously reported.

DOE PAGES

Shatsky, Maxim; Allen, Simon; Gold, Barbara; ...

2016-05-01

Numerous affinity purification – mass-spectrometry (AP-MS) and yeast two hybrid (Y2H) screens have each defined thousands of pairwise protein-protein interactions (PPIs), most between functionally unrelated proteins. The accuracy of these networks, however, is under debate. Here we present an AP-MS survey of the bacterium Desulfovibrio vulgaris together with a critical reanalysis of nine published bacterial Y2H and AP-MS screens. We have identified 459 high confidence PPIs from D. vulgaris and 391 from Escherichia coli. Compared to the nine published interactomes, our two networks are smaller; are much less highly connected; have significantly lower false discovery rates; and are much moremore » enriched in protein pairs that are encoded in the same operon, have similar functions, and are reproducibly detected in other physical interaction assays. Lastly, our work establishes more stringent benchmarks for the properties of protein interactomes and suggests that bona fide PPIs much more frequently involve protein partners that are annotated with similar functions or that can be validated in independent assays than earlier studies suggested.« less

Arabidopsis G-protein interactome reveals connections to cell wall carbohydrates and morphogenesis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Klopffleisch, Karsten; Phan, Nguyen; Chen, Jay

2011-01-01

The heterotrimeric G-protein complex is minimally composed of G{alpha}, G{beta}, and G{gamma} subunits. In the classic scenario, the G-protein complex is the nexus in signaling from the plasma membrane, where the heterotrimeric G-protein associates with heptahelical G-protein-coupled receptors (GPCRs), to cytoplasmic target proteins called effectors. Although a number of effectors are known in metazoans and fungi, none of these are predicted to exist in their canonical forms in plants. To identify ab initio plant G-protein effectors and scaffold proteins, we screened a set of proteins from the G-protein complex using two-hybrid complementation in yeast. After deep and exhaustive interrogation, wemore » detected 544 interactions between 434 proteins, of which 68 highly interconnected proteins form the core G-protein interactome. Within this core, over half of the interactions comprising two-thirds of the nodes were retested and validated as genuine in planta. Co-expression analysis in combination with phenotyping of loss-of-function mutations in a set of core interactome genes revealed a novel role for G-proteins in regulating cell wall modification.« less

Native KCC2 interactome reveals PACSIN1 as a critical regulator of synaptic inhibition.

PubMed

Mahadevan, Vivek; Khademullah, C Sahara; Dargaei, Zahra; Chevrier, Jonah; Uvarov, Pavel; Kwan, Julian; Bagshaw, Richard D; Pawson, Tony; Emili, Andrew; De Koninck, Yves; Anggono, Victor; Airaksinen, Matti; Woodin, Melanie A

2017-10-13

KCC2 is a neuron-specific K + -Cl - cotransporter essential for establishing the Cl - gradient required for hyperpolarizing inhibition in the central nervous system (CNS). KCC2 is highly localized to excitatory synapses where it regulates spine morphogenesis and AMPA receptor confinement. Aberrant KCC2 function contributes to human neurological disorders including epilepsy and neuropathic pain. Using functional proteomics, we identified the KCC2-interactome in the mouse brain to determine KCC2-protein interactions that regulate KCC2 function. Our analysis revealed that KCC2 interacts with diverse proteins, and its most predominant interactors play important roles in postsynaptic receptor recycling. The most abundant KCC2 interactor is a neuronal endocytic regulatory protein termed PACSIN1 (SYNDAPIN1). We verified the PACSIN1-KCC2 interaction biochemically and demonstrated that shRNA knockdown of PACSIN1 in hippocampal neurons increases KCC2 expression and hyperpolarizes the reversal potential for Cl - . Overall, our global native-KCC2 interactome and subsequent characterization revealed PACSIN1 as a novel and potent negative regulator of KCC2.

Native KCC2 interactome reveals PACSIN1 as a critical regulator of synaptic inhibition

PubMed Central

Mahadevan, Vivek; Chevrier, Jonah; Uvarov, Pavel; Kwan, Julian; Bagshaw, Richard D; Pawson, Tony; Emili, Andrew; De Koninck, Yves; Anggono, Victor; Airaksinen, Matti

2017-01-01

KCC2 is a neuron-specific K+-Cl– cotransporter essential for establishing the Cl- gradient required for hyperpolarizing inhibition in the central nervous system (CNS). KCC2 is highly localized to excitatory synapses where it regulates spine morphogenesis and AMPA receptor confinement. Aberrant KCC2 function contributes to human neurological disorders including epilepsy and neuropathic pain. Using functional proteomics, we identified the KCC2-interactome in the mouse brain to determine KCC2-protein interactions that regulate KCC2 function. Our analysis revealed that KCC2 interacts with diverse proteins, and its most predominant interactors play important roles in postsynaptic receptor recycling. The most abundant KCC2 interactor is a neuronal endocytic regulatory protein termed PACSIN1 (SYNDAPIN1). We verified the PACSIN1-KCC2 interaction biochemically and demonstrated that shRNA knockdown of PACSIN1 in hippocampal neurons increases KCC2 expression and hyperpolarizes the reversal potential for Cl-. Overall, our global native-KCC2 interactome and subsequent characterization revealed PACSIN1 as a novel and potent negative regulator of KCC2. PMID:29028184

The MYO6 interactome reveals adaptor complexes coordinating early endosome and cytoskeletal dynamics.

PubMed

O'Loughlin, Thomas; Masters, Thomas A; Buss, Folma

2018-04-01

The intracellular functions of myosin motors requires a number of adaptor molecules, which control cargo attachment, but also fine-tune motor activity in time and space. These motor-adaptor-cargo interactions are often weak, transient or highly regulated. To overcome these problems, we use a proximity labelling-based proteomics strategy to map the interactome of the unique minus end-directed actin motor MYO6. Detailed biochemical and functional analysis identified several distinct MYO6-adaptor modules including two complexes containing RhoGEFs: the LIFT (LARG-Induced F-actin for Tethering) complex that controls endosome positioning and motility through RHO-driven actin polymerisation; and the DISP (DOCK7-Induced Septin disPlacement) complex, a novel regulator of the septin cytoskeleton. These complexes emphasise the role of MYO6 in coordinating endosome dynamics and cytoskeletal architecture. This study provides the first in vivo interactome of a myosin motor protein and highlights the power of this approach in uncovering dynamic and functionally diverse myosin motor complexes. © 2018 The Authors. Published under the terms of the CC BY 4.0 license.

Dawn of the in vivo RNA structurome and interactome.

PubMed

Kwok, Chun Kit

2016-10-15

RNA is one of the most fascinating biomolecules in living systems given its structural versatility to fold into elaborate architectures for important biological functions such as gene regulation, catalysis, and information storage. Knowledge of RNA structures and interactions can provide deep insights into their functional roles in vivo For decades, RNA structural studies have been conducted on a transcript-by-transcript basis. The advent of next-generation sequencing (NGS) has enabled the development of transcriptome-wide structural probing methods to profile the global landscape of RNA structures and interactions, also known as the RNA structurome and interactome, which transformed our understanding of the RNA structure-function relationship on a transcriptomic scale. In this review, molecular tools and NGS methods used for RNA structure probing are presented, novel insights uncovered by RNA structurome and interactome studies are highlighted, and perspectives on current challenges and potential future directions are discussed. A more complete understanding of the RNA structures and interactions in vivo will help illuminate the novel roles of RNA in gene regulation, development, and diseases. © 2016 The Author(s); published by Portland Press Limited on behalf of the Biochemical Society.

Arabidopsis G-protein interactome reveals connections to cell wall carbohydrates and morphogenesis.

PubMed

Klopffleisch, Karsten; Phan, Nguyen; Augustin, Kelsey; Bayne, Robert S; Booker, Katherine S; Botella, Jose R; Carpita, Nicholas C; Carr, Tyrell; Chen, Jin-Gui; Cooke, Thomas Ryan; Frick-Cheng, Arwen; Friedman, Erin J; Fulk, Brandon; Hahn, Michael G; Jiang, Kun; Jorda, Lucia; Kruppe, Lydia; Liu, Chenggang; Lorek, Justine; McCann, Maureen C; Molina, Antonio; Moriyama, Etsuko N; Mukhtar, M Shahid; Mudgil, Yashwanti; Pattathil, Sivakumar; Schwarz, John; Seta, Steven; Tan, Matthew; Temp, Ulrike; Trusov, Yuri; Urano, Daisuke; Welter, Bastian; Yang, Jing; Panstruga, Ralph; Uhrig, Joachim F; Jones, Alan M

2011-09-27

The heterotrimeric G-protein complex is minimally composed of Gα, Gβ, and Gγ subunits. In the classic scenario, the G-protein complex is the nexus in signaling from the plasma membrane, where the heterotrimeric G-protein associates with heptahelical G-protein-coupled receptors (GPCRs), to cytoplasmic target proteins called effectors. Although a number of effectors are known in metazoans and fungi, none of these are predicted to exist in their canonical forms in plants. To identify ab initio plant G-protein effectors and scaffold proteins, we screened a set of proteins from the G-protein complex using two-hybrid complementation in yeast. After deep and exhaustive interrogation, we detected 544 interactions between 434 proteins, of which 68 highly interconnected proteins form the core G-protein interactome. Within this core, over half of the interactions comprising two-thirds of the nodes were retested and validated as genuine in planta. Co-expression analysis in combination with phenotyping of loss-of-function mutations in a set of core interactome genes revealed a novel role for G-proteins in regulating cell wall modification.

Arabidopsis G-protein interactome reveals connections to cell wall carbohydrates and morphogenesis

PubMed Central

Klopffleisch, Karsten; Phan, Nguyen; Augustin, Kelsey; Bayne, Robert S; Booker, Katherine S; Botella, Jose R; Carpita, Nicholas C; Carr, Tyrell; Chen, Jin-Gui; Cooke, Thomas Ryan; Frick-Cheng, Arwen; Friedman, Erin J; Fulk, Brandon; Hahn, Michael G; Jiang, Kun; Jorda, Lucia; Kruppe, Lydia; Liu, Chenggang; Lorek, Justine; McCann, Maureen C; Molina, Antonio; Moriyama, Etsuko N; Mukhtar, M Shahid; Mudgil, Yashwanti; Pattathil, Sivakumar; Schwarz, John; Seta, Steven; Tan, Matthew; Temp, Ulrike; Trusov, Yuri; Urano, Daisuke; Welter, Bastian; Yang, Jing; Panstruga, Ralph; Uhrig, Joachim F; Jones, Alan M

2011-01-01

The heterotrimeric G-protein complex is minimally composed of Gα, Gβ, and Gγ subunits. In the classic scenario, the G-protein complex is the nexus in signaling from the plasma membrane, where the heterotrimeric G-protein associates with heptahelical G-protein-coupled receptors (GPCRs), to cytoplasmic target proteins called effectors. Although a number of effectors are known in metazoans and fungi, none of these are predicted to exist in their canonical forms in plants. To identify ab initio plant G-protein effectors and scaffold proteins, we screened a set of proteins from the G-protein complex using two-hybrid complementation in yeast. After deep and exhaustive interrogation, we detected 544 interactions between 434 proteins, of which 68 highly interconnected proteins form the core G-protein interactome. Within this core, over half of the interactions comprising two-thirds of the nodes were retested and validated as genuine in planta. Co-expression analysis in combination with phenotyping of loss-of-function mutations in a set of core interactome genes revealed a novel role for G-proteins in regulating cell wall modification. PMID:21952135

Shifted Transversal Design smart-pooling for high coverage interactome mapping

PubMed Central

Xin, Xiaofeng; Rual, Jean-François; Hirozane-Kishikawa, Tomoko; Hill, David E.; Vidal, Marc; Boone, Charles; Thierry-Mieg, Nicolas

2009-01-01

“Smart-pooling,” in which test reagents are multiplexed in a highly redundant manner, is a promising strategy for achieving high efficiency, sensitivity, and specificity in systems-level projects. However, previous applications relied on low redundancy designs that do not leverage the full potential of smart-pooling, and more powerful theoretical constructions, such as the Shifted Transversal Design (STD), lack experimental validation. Here we evaluate STD smart-pooling in yeast two-hybrid (Y2H) interactome mapping. We employed two STD designs and two established methods to perform ORFeome-wide Y2H screens with 12 baits. We found that STD pooling achieves similar levels of sensitivity and specificity as one-on-one array-based Y2H, while the costs and workloads are divided by three. The screening-sequencing approach is the most cost- and labor-efficient, yet STD identifies about twofold more interactions. Screening-sequencing remains an appropriate method for quickly producing low-coverage interactomes, while STD pooling appears as the method of choice for obtaining maps with higher coverage. PMID:19447967

Exploring the interactome: microfluidic isolation of proteins and interacting partners for quantitative analysis by electron microscopy.

PubMed

Giss, Dominic; Kemmerling, Simon; Dandey, Venkata; Stahlberg, Henning; Braun, Thomas

2014-05-20

Multimolecular protein complexes are important for many cellular processes. However, the stochastic nature of the cellular interactome makes the experimental detection of complex protein assemblies difficult and quantitative analysis at the single molecule level essential. Here, we present a fast and simple microfluidic method for (i) the quantitative isolation of endogenous levels of untagged protein complexes from minute volumes of cell lysates under close to physiological conditions and (ii) the labeling of specific components constituting these complexes. The method presented uses specific antibodies that are conjugated via a photocleavable linker to magnetic beads that are trapped in microcapillaries to immobilize the target proteins. Proteins are released by photocleavage, eluted, and subsequently analyzed by quantitative transmission electron microscopy at the single molecule level. Additionally, before photocleavage, immunogold can be employed to label proteins that interact with the primary target protein. Thus, the presented method provides a new way to study the interactome and, in combination with single molecule transmission electron microscopy, to structurally characterize the large, dynamic, heterogeneous multimolecular protein complexes formed.

Proteomic characterization of hempseed (Cannabis sativa L.).

PubMed

Aiello, Gilda; Fasoli, Elisa; Boschin, Giovanna; Lammi, Carmen; Zanoni, Chiara; Citterio, Attilio; Arnoldi, Anna

2016-09-16

This paper presents an investigation on hempseed proteome. The experimental approach, based on combinatorial peptide ligand libraries (CPLLs), SDS-PAGE separation, nLC-ESI-MS/MS identification, and database search, permitted identifying in total 181 expressed proteins. This very large number of identifications was achieved by searching in two databases: Cannabis sativa L. (56 gene products identified) and Arabidopsis thaliana (125 gene products identified). By performing a protein-protein association network analysis using the STRING software, it was possible to build the first interactomic map of all detected proteins, characterized by 137 nodes and 410 interactions. Finally, a Gene Ontology analysis of the identified species permitted to classify their molecular functions: the great majority is involved in the seed metabolic processes (41%), responses to stimulus (8%), and biological process (7%). Hempseed is an underexploited non-legume protein-rich seed. Although its protein is well known for its digestibility, essential amino acid composition, and useful techno-functional properties, a comprehensive proteome characterization is still lacking. The objective of this work was to fill this knowledge gap and provide information useful for a better exploitation of this seed in different food products. Copyright © 2016 Elsevier B.V. All rights reserved.

Proteomics profiling of interactome dynamics by colocalisation analysis (COLA).

PubMed

Mardakheh, Faraz K; Sailem, Heba Z; Kümper, Sandra; Tape, Christopher J; McCully, Ryan R; Paul, Angela; Anjomani-Virmouni, Sara; Jørgensen, Claus; Poulogiannis, George; Marshall, Christopher J; Bakal, Chris

2016-12-20

Localisation and protein function are intimately linked in eukaryotes, as proteins are localised to specific compartments where they come into proximity of other functionally relevant proteins. Significant co-localisation of two proteins can therefore be indicative of their functional association. We here present COLA, a proteomics based strategy coupled with a bioinformatics framework to detect protein-protein co-localisations on a global scale. COLA reveals functional interactions by matching proteins with significant similarity in their subcellular localisation signatures. The rapid nature of COLA allows mapping of interactome dynamics across different conditions or treatments with high precision.

Approaches for Defining the Hsp90-dependent Proteome

PubMed Central

Hartson, Steven D.; Matts, Robert L.

2011-01-01

Hsp90 is the target of ongoing drug discovery studies seeking new compounds to treat cancer, neurodegenerative diseases, and protein folding disorders. To better understand Hsp90’s roles in cellular pathologies and in normal cells, numerous studies have utilized proteomics assays and related high-throughput tools to characterize its physical and functional protein partnerships. This review surveys these studies, and summarizes the strengths and limitations of the individual attacks. We also include downloadable spreadsheets compiling all of the Hsp90-interacting proteins identified in more than 23 studies. These tools include cross-references among gene aliases, human homologues of yeast Hsp90-interacting proteins, hyperlinks to database entries, summaries of canonical pathways that are enriched in the Hsp90 interactome, and additional bioinformatic annotations. In addition to summarizing Hsp90 proteomics studies performed to date and the insights they have provided, we identify gaps in our current understanding of Hsp90-mediated proteostasis. PMID:21906632

Global Membrane Protein Interactome Analysis using In vivo Crosslinking and Mass Spectrometry-based Protein Correlation Profiling*

PubMed Central

Larance, Mark; Kirkwood, Kathryn J.; Tinti, Michele; Brenes Murillo, Alejandro; Ferguson, Michael A. J.; Lamond, Angus I.

2016-01-01

We present a methodology using in vivo crosslinking combined with HPLC-MS for the global analysis of endogenous protein complexes by protein correlation profiling. Formaldehyde crosslinked protein complexes were extracted with high yield using denaturing buffers that maintained complex solubility during chromatographic separation. We show this efficiently detects both integral membrane and membrane-associated protein complexes,in addition to soluble complexes, allowing identification and analysis of complexes not accessible in native extracts. We compare the protein complexes detected by HPLC-MS protein correlation profiling in both native and formaldehyde crosslinked U2OS cell extracts. These proteome-wide data sets of both in vivo crosslinked and native protein complexes from U2OS cells are freely available via a searchable online database (www.peptracker.com/epd). Raw data are also available via ProteomeXchange (identifier PXD003754). PMID:27114452

Small Molecule Interactome Mapping by Photoaffinity Labeling Reveals Binding Site Hotspots for the NSAIDs.

PubMed

Gao, Jinxu; Mfuh, Adelphe; Amako, Yuka; Woo, Christina M

2018-03-28

Many therapeutics elicit cell-type specific polypharmacology that is executed by a network of molecular recognition events between a small molecule and the whole proteome. However, measurement of the structures that underpin the molecular associations between the proteome and even common therapeutics, such as the nonsteroidal anti-inflammatory drugs (NSAIDs), is limited by the inability to map the small molecule interactome. To address this gap, we developed a platform termed small molecule interactome mapping by photoaffinity labeling (SIM-PAL) and applied it to the in cellulo direct characterization of specific NSAID binding sites. SIM-PAL uses (1) photochemical conjugation of NSAID derivatives in the whole proteome and (2) enrichment and isotope-recoding of the conjugated peptides for (3) targeted mass spectrometry-based assignment. Using SIM-PAL, we identified the NSAID interactome consisting of over 1000 significantly enriched proteins and directly characterized nearly 200 conjugated peptides representing direct binding sites of the photo-NSAIDs with proteins from Jurkat and K562 cells. The enriched proteins were often identified as parts of complexes, including known targets of NSAID activity (e.g., NF-κB) and novel interactions (e.g., AP-2, proteasome). The conjugated peptides revealed direct NSAID binding sites from the cell surface to the nucleus and a specific binding site hotspot for the three photo-NSAIDs on histones H2A and H2B. NSAID binding stabilized COX-2 and histone H2A by cellular thermal shift assay. Since small molecule stabilization of protein complexes is a gain of function regulatory mechanism, it is conceivable that NSAIDs affect biological processes through these broader proteomic interactions. SIM-PAL enabled characterization of NSAID binding site hotspots and is amenable to map global binding sites for virtually any molecule of interest.

Lubricin: A Principal Modulator of the Psychoneuroendocrine - Osteoimmune Interactome - Implications for Novel Treatments of Osteoarthritic Pathologies.

PubMed

Khakshooy, Allen; Balenton, Nicole; Chiappelli, Francesco

2017-01-01

Lubricin is a synovial glycoprotein that contributes to joint lubrication. We propose the hypothesis that lubricin is a key modulator of the psychoneuroendocrine-osteoimmune interactome, with important clinical relevance for osteoarthritic pathologies. We consider a variety of neuroendocrine-immune factors, including inflammatory cytokines and chemokines that may contribute to the modulation of lubricin in rheumatic complications. Based on our preliminary immunocytochemistry and fractal analysis data, and in the context of translational research of modern healthcare, we propose that molecular lubricin gene expression modification by means of the novel CRISPR/Cas system be considered for osteoarthritic therapies.

A human XPC protein interactome--a resource.

PubMed

Lubin, Abigail; Zhang, Ling; Chen, Hua; White, Victoria M; Gong, Feng

2013-12-23

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

Interactomic approach for evaluating nucleophosmin-binding proteins as biomarkers for Ewing's sarcoma.

PubMed

Haga, Ayako; Ogawara, Yoko; Kubota, Daisuke; Kitabayashi, Issay; Murakami, Yasufumi; Kondo, Tadashi

2013-06-01

Nucleophosmin (NPM) is a novel prognostic biomarker for Ewing's sarcoma. To evaluate the prognostic utility of NPM, we conducted an interactomic approach to characterize the NPM protein complex in Ewing's sarcoma cells. A gene suppression assay revealed that NPM promoted cell proliferation and the invasive properties of Ewing's sarcoma cells. FLAG-tag-based affinity purification coupled with liquid chromatography-tandem mass spectrometry identified 106 proteins in the NPM protein complex. The functional classification suggested that the NPM complex participates in critical biological events, including ribosome biogenesis, regulation of transcription and translation, and protein folding, that are mediated by these proteins. In addition to JAK1, a candidate prognostic biomarker for Ewing's sarcoma, the NPM complex, includes 11 proteins known as prognostic biomarkers for other malignancies. Meta-analysis of gene expression profiles of 32 patients with Ewing's sarcoma revealed that 6 of 106 were significantly and independently associated with survival period. These observations suggest a functional role as well as prognostic value of these NPM complex proteins in Ewing's sarcoma. Further, our study suggests the potential applications of interactomics in conjunction with meta-analysis for biomarker discovery. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Functional Proteomics Identifies Acinus L as a Direct Insulin- and Amino Acid-Dependent Mammalian Target of Rapamycin Complex 1 (mTORC1) Substrate*

PubMed Central

Schwarz, Jennifer Jasmin; Wiese, Heike; Tölle, Regine Charlotte; Zarei, Mostafa; Dengjel, Jörn; Warscheid, Bettina; Thedieck, Kathrin

2015-01-01

The serine/threonine kinase mammalian target of rapamycin (mTOR) governs growth, metabolism, and aging in response to insulin and amino acids (aa), and is often activated in metabolic disorders and cancer. Much is known about the regulatory signaling network that encompasses mTOR, but surprisingly few direct mTOR substrates have been established to date. To tackle this gap in our knowledge, we took advantage of a combined quantitative phosphoproteomic and interactomic strategy. We analyzed the insulin- and aa-responsive phosphoproteome upon inhibition of the mTOR complex 1 (mTORC1) component raptor, and investigated in parallel the interactome of endogenous mTOR. By overlaying these two datasets, we identified acinus L as a potential novel mTORC1 target. We confirmed acinus L as a direct mTORC1 substrate by co-immunoprecipitation and MS-enhanced kinase assays. Our study delineates a triple proteomics strategy of combined phosphoproteomics, interactomics, and MS-enhanced kinase assays for the de novo-identification of mTOR network components, and provides a rich source of potential novel mTOR interactors and targets for future investigation. PMID:25907765

Epigenetic Drug Repositioning for Alzheimer's Disease Based on Epigenetic Targets in Human Interactome.

PubMed

Chatterjee, Paulami; Roy, Debjani; Rathi, Nitin

2018-01-01

Epigenetics has emerged as an important field in drug discovery. Alzheimer's disease (AD), the leading neurodegenerative disorder throughout the world, is shown to have an epigenetic basis. Currently, there are very few effective epigenetic drugs available for AD. In this work, for the first time we have proposed 14 AD repositioning epigenetic drugs and identified their targets from extensive human interactome. Interacting partners of the AD epigenetic proteins were identified from the extensive human interactome to construct Epigenetic Protein-Protein Interaction Network (EP-PPIN). Epigenetic Drug-Target Network (EP-DTN) was constructed with the drugs associated with the proteins of EP-PPIN. Regulation of non-coding RNAs associated with the target proteins of these drugs was also studied. AD related target proteins, epigenetic targets, enriched pathways, and functional categories of the proposed repositioning drugs were also studied. The proposed 14 AD epigenetic repositioning drugs have overlapping targets and miRs with known AD epigenetic targets and miRs. Furthermore, several shared functional categories and enriched pathways were obtained for these drugs with FDA approved epigenetic drugs and known AD drugs. The findings of our work might provide insight into future AD epigenetic-therapeutics.

Mass Spectrometry-Based Screening Platform Reveals Orco Interactome in Drosophila melanogaster.

PubMed

Yu, Kate E; Kim, Do-Hyoung; Kim, Yong-In; Jones, Walton D; Lee, J Eugene

2018-02-28

Animals use their odorant receptors to receive chemical information from the environment. Insect odorant receptors differ from the G protein-coupled odorant receptors in vertebrates and nematodes, and very little is known about their protein-protein interactions. Here, we introduce a mass spectrometric platform designed for the large-scale analysis of insect odorant receptor protein-protein interactions. Using this platform, we obtained the first Orco interactome from Drosophila melanogaster . From a total of 1,186 identified proteins, we narrowed the interaction candidates to 226, of which only two-thirds have been named. These candidates include the known olfactory proteins Or92a and Obp51a. Around 90% of the proteins having published names likely function inside the cell, and nearly half of these intracellular proteins are associated with the endomembrane system. In a basic loss-of-function electrophysiological screen, we found that the disruption of eight (i.e., Rab5, CG32795, Mpcp, Tom70, Vir-1, CG30427, Eaat1, and CG2781) of 28 randomly selected candidates affects olfactory responses in vivo . Thus, because this Orco interactome includes physiologically meaningful candidates, we anticipate that our platform will help guide further research on the molecular mechanisms of the insect odorant receptor family.

High-throughput proteomics : optical approaches.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Davidson, George S.

2008-09-01

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

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

PubMed Central

2011-01-01

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

How perfect can protein interactomes be?

PubMed

Levy, Emmanuel D; Landry, Christian R; Michnick, Stephen W

2009-03-03

Any engineered device should certainly not contain nonfunctional components, for this would be a waste of energy and money. In contrast, evolutionary theory tells us that biological systems need not be optimized and may very well accumulate nonfunctional elements. Mutational and demographic processes contribute to the cluttering of eukaryotic genomes and transcriptional networks with "junk" DNA and spurious DNA binding sites. Here, we question whether such a notion should be applied to protein interactomes-that is, whether these protein interactomes are expected to contain a fraction of nonselected, nonfunctional protein-protein interactions (PPIs), which we term "noisy." We propose a simple relationship between the fraction of noisy interactions expected in a given organism and three parameters: (i) the number of mutations needed to create and destroy interactions, (ii) the size of the proteome, and (iii) the fitness cost of noisy interactions. All three parameters suggest that noisy PPIs are expected to exist. Their existence could help to explain why PPIs determined from large-scale studies often lack functional relationships between interacting proteins, why PPIs are poorly conserved across organisms, and why the PPI space appears to be immensely large. Finally, we propose experimental strategies to estimate the fraction of evolutionary noise in PPI networks.

Interactome Mapping Guided by Tissue-Specific Phosphorylation in Age-Related Macular Degeneration

PubMed Central

Sripathi, Srinivas R.; He, Weilue; Prigge, Cameron L.; Sylvester, O’Donnell; Um, Ji-Yeon; Powell, Folami L.; Neksumi, Musa; Bernstein, Paul S.; Choo, Dong-Won; Bartoli, Manuela; Gutsaeva, Diana R.; Jahng, Wan Jin

2017-01-01

The current study aims to determine the molecular mechanisms of age-related macular degeneration (AMD) using the phosphorylation network. Specifically, we examined novel biomarkers for oxidative stress by protein interaction mapping using in vitro and in vivo models that mimic the complex and progressive characteristics of AMD. We hypothesized that the early apoptotic reactions could be initiated by protein phosphorylation in region-dependent (peripheral retina vs. macular) and tissue-dependent (retinal pigment epithelium vs. retina) manner under chronic oxidative stress. The analysis of protein interactome and oxidative biomarkers showed the presence of tissue- and region-specific post-translational mechanisms that contribute to AMD progression and suggested new therapeutic targets that include ubiquitin, erythropoietin, vitronectin, MMP2, crystalline, nitric oxide, and prohibitin. Phosphorylation of specific target proteins in RPE cells is a central regulatory mechanism as a survival tool under chronic oxidative imbalance. The current interactome map demonstrates a positive correlation between oxidative stress-mediated phosphorylation and AMD progression and provides a basis for understanding oxidative stress-induced cytoskeletal changes and the mechanism of aggregate formation induced by protein phosphorylation. This information could provide an effective therapeutic approach to treat age-related neurodegeneration. PMID:28580316

Interactome Mapping Guided by Tissue-Specific Phosphorylation in Age-Related Macular Degeneration.

PubMed

Sripathi, Srinivas R; He, Weilue; Prigge, Cameron L; Sylvester, O'Donnell; Um, Ji-Yeon; Powell, Folami L; Neksumi, Musa; Bernstein, Paul S; Choo, Dong-Won; Bartoli, Manuela; Gutsaeva, Diana R; Jahng, Wan Jin

2017-02-01

The current study aims to determine the molecular mechanisms of age-related macular degeneration (AMD) using the phosphorylation network. Specifically, we examined novel biomarkers for oxidative stress by protein interaction mapping using in vitro and in vivo models that mimic the complex and progressive characteristics of AMD. We hypothesized that the early apoptotic reactions could be initiated by protein phosphorylation in region-dependent (peripheral retina vs. macular) and tissue-dependent (retinal pigment epithelium vs. retina) manner under chronic oxidative stress. The analysis of protein interactome and oxidative biomarkers showed the presence of tissue- and region-specific post-translational mechanisms that contribute to AMD progression and suggested new therapeutic targets that include ubiquitin, erythropoietin, vitronectin, MMP2, crystalline, nitric oxide, and prohibitin. Phosphorylation of specific target proteins in RPE cells is a central regulatory mechanism as a survival tool under chronic oxidative imbalance. The current interactome map demonstrates a positive correlation between oxidative stress-mediated phosphorylation and AMD progression and provides a basis for understanding oxidative stress-induced cytoskeletal changes and the mechanism of aggregate formation induced by protein phosphorylation. This information could provide an effective therapeutic approach to treat age-related neurodegeneration.

DIANA-LncBase v2: indexing microRNA targets on non-coding transcripts

PubMed Central

Paraskevopoulou, Maria D.; Vlachos, Ioannis S.; Karagkouni, Dimitra; Georgakilas, Georgios; Kanellos, Ilias; Vergoulis, Thanasis; Zagganas, Konstantinos; Tsanakas, Panayiotis; Floros, Evangelos; Dalamagas, Theodore; Hatzigeorgiou, Artemis G.

2016-01-01

microRNAs (miRNAs) are short non-coding RNAs (ncRNAs) that act as post-transcriptional regulators of coding gene expression. Long non-coding RNAs (lncRNAs) have been recently reported to interact with miRNAs. The sponge-like function of lncRNAs introduces an extra layer of complexity in the miRNA interactome. DIANA-LncBase v1 provided a database of experimentally supported and in silico predicted miRNA Recognition Elements (MREs) on lncRNAs. The second version of LncBase (www.microrna.gr/LncBase) presents an extensive collection of miRNA:lncRNA interactions. The significantly enhanced database includes more than 70 000 low and high-throughput, (in)direct miRNA:lncRNA experimentally supported interactions, derived from manually curated publications and the analysis of 153 AGO CLIP-Seq libraries. The new experimental module presents a 14-fold increase compared to the previous release. LncBase v2 hosts in silico predicted miRNA targets on lncRNAs, identified with the DIANA-microT algorithm. The relevant module provides millions of predicted miRNA binding sites, accompanied with detailed metadata and MRE conservation metrics. LncBase v2 caters information regarding cell type specific miRNA:lncRNA regulation and enables users to easily identify interactions in 66 different cell types, spanning 36 tissues for human and mouse. Database entries are also supported by accurate lncRNA expression information, derived from the analysis of more than 6 billion RNA-Seq reads. PMID:26612864

Comparison of Online Agricultural Information Services.

ERIC Educational Resources Information Center

Reneau, Fred; Patterson, Richard

1984-01-01

Outlines major online agricultural information services--agricultural databases, databases with agricultural services, educational databases in agriculture--noting services provided, access to the database, and costs. Benefits of online agricultural database sources (availability of agricultural marketing, weather, commodity prices, management…

Recent Progress in CFTR Interactome Mapping and Its Importance for Cystic Fibrosis.

PubMed

Lim, Sang Hyun; Legere, Elizabeth-Ann; Snider, Jamie; Stagljar, Igor

2017-01-01

Cystic Fibrosis Transmembrane Conductance Regulator (CFTR) is a chloride channel found in secretory epithelia with a plethora of known interacting proteins. Mutations in the CFTR gene cause cystic fibrosis (CF), a disease that leads to progressive respiratory illness and other complications of phenotypic variance resulting from perturbations of this protein interaction network. Studying the collection of CFTR interacting proteins and the differences between the interactomes of mutant and wild type CFTR provides insight into the molecular machinery of the disease and highlights possible therapeutic targets. This mini review focuses on functional genomics and proteomics approaches used for systematic, high-throughput identification of CFTR-interacting proteins to provide comprehensive insight into CFTR regulation and function.

RNA interactome capture in yeast.

PubMed

Beckmann, Benedikt M

2017-04-15

RNA-binding proteins (RBPs) are key players in post-transcriptional regulation of gene expression in eukaryotic cells. To be able to unbiasedly identify RBPs in Saccharomyces cerevisiae, we developed a yeast RNA interactome capture protocol which employs RNA labeling, covalent UV crosslinking of RNA and proteins at 365nm wavelength (photoactivatable-ribonucleoside-enhanced crosslinking, PAR-CL) and finally purification of the protein-bound mRNA. The method can be easily implemented in common workflows and takes about 3days to complete. Next to a comprehensive explanation of the method, we focus on our findings about the choice of crosslinking in yeast and discuss the rationale of individual steps in the protocol. Copyright © 2016. Published by Elsevier Inc.

Interactome Analyses of Mature γ-Secretase Complexes Reveal Distinct Molecular Environments of Presenilin (PS) Paralogs and Preferential Binding of Signal Peptide Peptidase to PS2*

PubMed Central

Jeon, Amy Hye Won; Böhm, Christopher; Chen, Fusheng; Huo, Hairu; Ruan, Xueying; Ren, Carl He; Ho, Keith; Qamar, Seema; Mathews, Paul M.; Fraser, Paul E.; Mount, Howard T. J.; St George-Hyslop, Peter; Schmitt-Ulms, Gerold

2013-01-01

γ-Secretase plays a pivotal role in the production of neurotoxic amyloid β-peptides (Aβ) in Alzheimer disease (AD) and consists of a heterotetrameric core complex that includes the aspartyl intramembrane protease presenilin (PS). The human genome codes for two presenilin paralogs. To understand the causes for distinct phenotypes of PS paralog-deficient mice and elucidate whether PS mutations associated with early-onset AD affect the molecular environment of mature γ-secretase complexes, quantitative interactome comparisons were undertaken. Brains of mice engineered to express wild-type or mutant PS1, or HEK293 cells stably expressing PS paralogs with N-terminal tandem-affinity purification tags served as biological source materials. The analyses revealed novel interactions of the γ-secretase core complex with a molecular machinery that targets and fuses synaptic vesicles to cellular membranes and with the H+-transporting lysosomal ATPase macrocomplex but uncovered no differences in the interactomes of wild-type and mutant PS1. The catenin/cadherin network was almost exclusively found associated with PS1. Another intramembrane protease, signal peptide peptidase, predominantly co-purified with PS2-containing γ-secretase complexes and was observed to influence Aβ production. PMID:23589300

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

PubMed

Carter, C J

2013-01-01

Toxoplasma gondii is not only implicated in schizophrenia and related disorders, but also in Alzheimer's or Parkinson's disease, cancer, cardiac myopathies, and autoimmune disorders. During its life cycle, the pathogen interacts with ~3000 host genes or proteins. Susceptibility genes for multiple sclerosis, Alzheimer's disease, schizophrenia, bipolar disorder, depression, childhood obesity, Parkinson's disease, attention deficit hyperactivity disorder (P  from  8.01E - 05  (ADHD)  to  1.22E - 71) (multiple sclerosis), and autism (P = 0.013), but not anorexia or chronic fatigue are highly enriched in the human arm of this interactome and 18 (ADHD) to 33% (MS) of the susceptibility genes relate to it. The signalling pathways involved in the susceptibility gene/interactome overlaps are relatively specific and relevant to each disease suggesting a means whereby susceptibility genes could orient the attentions of a single pathogen towards disruption of the specific pathways that together contribute (positively or negatively) to the endophenotypes of different diseases. Conditional protein knockdown, orchestrated by T. gondii proteins or antibodies binding to those of the host (pathogen derived autoimmunity) and metabolite exchange, may contribute to this disruption. Susceptibility genes may thus be related to the causes and influencers of disease, rather than (and as well as) to the disease itself.

Large-scale De Novo Prediction of Physical Protein-Protein Association*

PubMed Central

Elefsinioti, Antigoni; Saraç, Ömer Sinan; Hegele, Anna; Plake, Conrad; Hubner, Nina C.; Poser, Ina; Sarov, Mihail; Hyman, Anthony; Mann, Matthias; Schroeder, Michael; Stelzl, Ulrich; Beyer, Andreas

2011-01-01

Information about the physical association of proteins is extensively used for studying cellular processes and disease mechanisms. However, complete experimental mapping of the human interactome will remain prohibitively difficult in the near future. Here we present a map of predicted human protein interactions that distinguishes functional association from physical binding. Our network classifies more than 5 million protein pairs predicting 94,009 new interactions with high confidence. We experimentally tested a subset of these predictions using yeast two-hybrid analysis and affinity purification followed by quantitative mass spectrometry. Thus we identified 462 new protein-protein interactions and confirmed the predictive power of the network. These independent experiments address potential issues of circular reasoning and are a distinctive feature of this work. Analysis of the physical interactome unravels subnetworks mediating between different functional and physical subunits of the cell. Finally, we demonstrate the utility of the network for the analysis of molecular mechanisms of complex diseases by applying it to genome-wide association studies of neurodegenerative diseases. This analysis provides new evidence implying TOMM40 as a factor involved in Alzheimer's disease. The network provides a high-quality resource for the analysis of genomic data sets and genetic association studies in particular. Our interactome is available via the hPRINT web server at: www.print-db.org. PMID:21836163

The Sharpin interactome reveals a role for Sharpin in lamellipodium formation via the Arp2/3 complex.

PubMed

Khan, Meraj H; Salomaa, Siiri I; Jacquemet, Guillaume; Butt, Umar; Miihkinen, Mitro; Deguchi, Takahiro; Kremneva, Elena; Lappalainen, Pekka; Humphries, Martin J; Pouwels, Jeroen

2017-09-15

Sharpin, a multifunctional adaptor protein, regulates several signalling pathways. For example, Sharpin enhances signal-induced NF-κB signalling as part of the linear ubiquitin assembly complex (LUBAC) and inhibits integrins, the T cell receptor, caspase 1 and PTEN. However, despite recent insights into Sharpin and LUBAC function, a systematic approach to identify the signalling pathways regulated by Sharpin has not been reported. Here, we present the first 'Sharpin interactome', which identifies a large number of novel potential Sharpin interactors in addition to several known ones. These data suggest that Sharpin and LUBAC might regulate a larger number of biological processes than previously identified, such as endosomal trafficking, RNA processing, metabolism and cytoskeleton regulation. Importantly, using the Sharpin interactome, we have identified a novel role for Sharpin in lamellipodium formation. We demonstrate that Sharpin interacts with Arp2/3, a protein complex that catalyses actin filament branching. We have identified the Arp2/3-binding site in Sharpin and demonstrate using a specific Arp2/3-binding deficient mutant that the Sharpin-Arp2/3 interaction promotes lamellipodium formation in a LUBAC-independent fashion.This article has an associated First Person interview with the first author of the paper. © 2017. Published by The Company of Biologists Ltd.

Brain-inspired cheminformatics of drug-target brain interactome, synthesis, and assay of TVP1022 derivatives.

PubMed

Romero-Durán, Francisco J; Alonso, Nerea; Yañez, Matilde; Caamaño, Olga; García-Mera, Xerardo; González-Díaz, Humberto

2016-04-01

The use of Cheminformatics tools is gaining importance in the field of translational research from Medicinal Chemistry to Neuropharmacology. In particular, we need it for the analysis of chemical information on large datasets of bioactive compounds. These compounds form large multi-target complex networks (drug-target interactome network) resulting in a very challenging data analysis problem. Artificial Neural Network (ANN) algorithms may help us predict the interactions of drugs and targets in CNS interactome. In this work, we trained different ANN models able to predict a large number of drug-target interactions. These models predict a dataset of thousands of interactions of central nervous system (CNS) drugs characterized by > 30 different experimental measures in >400 different experimental protocols for >150 molecular and cellular targets present in 11 different organisms (including human). The model was able to classify cases of non-interacting vs. interacting drug-target pairs with satisfactory performance. A second aim focus on two main directions: the synthesis and assay of new derivatives of TVP1022 (S-analogues of rasagiline) and the comparison with other rasagiline derivatives recently reported. Finally, we used the best of our models to predict drug-target interactions for the best new synthesized compound against a large number of CNS protein targets. Copyright © 2015 Elsevier Ltd. All rights reserved.

Characterization of the zinc-induced Shank3 interactome of mouse synaptosome.

PubMed

Lee, Yeunkum; Ryu, Jae Ryun; Kang, Hyojin; Kim, Yoonhee; Kim, Shinhyun; Zhang, Yinhua; Jin, Chunmei; Cho, Hyo Min; Kim, Won-Ki; Sun, Woong; Han, Kihoon

2017-12-16

Variants of the SHANK3 gene, which encodes a core scaffold protein of the postsynaptic density of excitatory synapses, have been causally associated with numerous brain disorders. Shank3 proteins directly bind zinc ions through their C-terminal sterile α motif domain, which enhances the multimerization and synaptic localization of Shank3, to regulate excitatory synaptic strength. However, no studies have explored whether zinc affects the protein interactions of Shank3, which might contribute to the synaptic changes observed after zinc application. To examine this, we first purified Shank3 protein complexes from mouse brain synaptosomal lysates that were incubated with different concentrations of ZnCl 2 , and analyzed them with mass spectrometry. We used strict criteria to identify 71 proteins that specifically interacted with Shank3 when extra ZnCl 2 was added to the lysate. To characterize the zinc-induced Shank3 interactome, we performed various bioinformatic analyses that revealed significant associations of the interactome with subcellular compartments, including mitochondria, and brain disorders, such as bipolar disorder and schizophrenia. Together, our results showing that zinc affected the Shank3 protein interactions of in vitro mouse synaptosomes provided an additional link between zinc and core synaptic proteins that have been implicated in multiple brain disorders. Copyright © 2017 Elsevier Inc. All rights reserved.

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

PubMed Central

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

2012-01-01

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

HIV–host interactome revealed directly from infected cells

PubMed Central

Luo, Yang; Jacobs, Erica Y.; Greco, Todd M.; Mohammed, Kevin D.; Tong, Tommy; Keegan, Sarah; Binley, James M.; Cristea, Ileana M.; Fenyö, David; Rout, Michael P.; Chait, Brian T.; Muesing, Mark A.

2016-01-01

Although genetically compact, HIV-1 commandeers vast arrays of cellular machinery to sustain and protect it during cycles of viral outgrowth. Transposon-mediated saturation linker scanning mutagenesis was used to isolate fully replication-competent viruses harbouring a potent foreign epitope tag. Using these viral isolates, we performed differential isotopic labelling and affinity-capture mass spectrometric analyses on samples obtained from cultures of human lymphocytes to classify the vicinal interactomes of the viral Env and Vif proteins as they occur during natural infection. Importantly, interacting proteins were recovered without bias, regardless of their potential for positive, negative or neutral impact on viral replication. We identified specific host associations made with trimerized Env during its biosynthesis, at virological synapses, with innate immune effectors (such as HLA-E) and with certain cellular signalling pathways (for example, Notch1). We also defined Vif associations with host proteins involved in the control of nuclear transcription and nucleoside biosynthesis as well as those interacting stably or transiently with the cytoplasmic protein degradation apparatus. Our approach is broadly applicable to elucidating pathogen–host interactomes, providing high-certainty identification of interactors by their direct access during cycling infection. Understanding the pathophysiological consequences of these associations is likely to provide strategic targets for antiviral intervention. PMID:27375898

SteinerNet: a web server for integrating ‘omic’ data to discover hidden components of response pathways

PubMed Central

Tuncbag, Nurcan; McCallum, Scott; Huang, Shao-shan Carol; Fraenkel, Ernest

2012-01-01

High-throughput technologies including transcriptional profiling, proteomics and reverse genetics screens provide detailed molecular descriptions of cellular responses to perturbations. However, it is difficult to integrate these diverse data to reconstruct biologically meaningful signaling networks. Previously, we have established a framework for integrating transcriptional, proteomic and interactome data by searching for the solution to the prize-collecting Steiner tree problem. Here, we present a web server, SteinerNet, to make this method available in a user-friendly format for a broad range of users with data from any species. At a minimum, a user only needs to provide a set of experimentally detected proteins and/or genes and the server will search for connections among these data from the provided interactomes for yeast, human, mouse, Drosophila melanogaster and Caenorhabditis elegans. More advanced users can upload their own interactome data as well. The server provides interactive visualization of the resulting optimal network and downloadable files detailing the analysis and results. We believe that SteinerNet will be useful for researchers who would like to integrate their high-throughput data for a specific condition or cellular response and to find biologically meaningful pathways. SteinerNet is accessible at http://fraenkel.mit.edu/steinernet. PMID:22638579

Developing and applying a gene functional association network for anti-angiogenic kinase inhibitor activity assessment in an angiogenesis co-culture model

PubMed Central

Chen, Yuefeng; Wei, Tao; Yan, Lei; Lawrence, Frank; Qian, Hui-Rong; Burkholder, Timothy P; Starling, James J; Yingling, Jonathan M; Shou, Jianyong

2008-01-01

Background Tumor angiogenesis is a highly regulated process involving intercellular communication as well as the interactions of multiple downstream signal transduction pathways. Disrupting one or even a few angiogenesis pathways is often insufficient to achieve sustained therapeutic benefits due to the complexity of angiogenesis. Targeting multiple angiogenic pathways has been increasingly recognized as a viable strategy. However, translation of the polypharmacology of a given compound to its antiangiogenic efficacy remains a major technical challenge. Developing a global functional association network among angiogenesis-related genes is much needed to facilitate holistic understanding of angiogenesis and to aid the development of more effective anti-angiogenesis therapeutics. Results We constructed a comprehensive gene functional association network or interactome by transcript profiling an in vitro angiogenesis model, in which human umbilical vein endothelial cells (HUVECs) formed capillary structures when co-cultured with normal human dermal fibroblasts (NHDFs). HUVEC competence and NHDF supportiveness of cord formation were found to be highly cell-passage dependent. An enrichment test of Biological Processes (BP) of differentially expressed genes (DEG) revealed that angiogenesis related BP categories significantly changed with cell passages. Built upon 2012 DEGs identified from two microarray studies, the resulting interactome captured 17226 functional gene associations and displayed characteristics of a scale-free network. The interactome includes the involvement of oncogenes and tumor suppressor genes in angiogenesis. We developed a network walking algorithm to extract connectivity information from the interactome and applied it to simulate the level of network perturbation by three multi-targeted anti-angiogenic kinase inhibitors. Simulated network perturbation correlated with observed anti-angiogenesis activity in a cord formation bioassay. Conclusion We established a comprehensive gene functional association network to model in vitro angiogenesis regulation. The present study provided a proof-of-concept pilot of applying network perturbation analysis to drug phenotypic activity assessment. PMID:18518970

Analysis of the interactome of the Ser/Thr Protein Phosphatase type 1 in Plasmodium falciparum.

PubMed

Hollin, Thomas; De Witte, Caroline; Lenne, Astrid; Pierrot, Christine; Khalife, Jamal

2016-03-17

Protein Phosphatase 1 (PP1) is an enzyme essential to cell viability in the malaria parasite Plasmodium falciparum (Pf). The activity of PP1 is regulated by the binding of regulatory subunits, of which there are up to 200 in humans, but only 3 have been so far reported for the parasite. To better understand the P. falciparum PP1 (PfPP1) regulatory network, we here report the use of three strategies to characterize the PfPP1 interactome: co-affinity purified proteins identified by mass spectrometry, yeast two-hybrid (Y2H) screening and in silico analysis of the P. falciparum predicted proteome. Co-affinity purification followed by MS analysis identified 6 PfPP1 interacting proteins (Pips) of which 3 contained the RVxF consensus binding, 2 with a Fxx[RK]x[RK] motif, also shown to be a PP1 binding motif and one with both binding motifs. The Y2H screens identified 134 proteins of which 30 present the RVxF binding motif and 20 have the Fxx[RK]x[RK] binding motif. The in silico screen of the Pf predicted proteome using a consensus RVxF motif as template revealed the presence of 55 potential Pips. As further demonstration, 35 candidate proteins were validated as PfPP1 interacting proteins in an ELISA-based assay. To the best of our knowledge, this is the first study on PfPP1 interactome. The data reports several conserved PP1 interacting proteins as well as a high number of specific interactors to PfPP1. Their analysis indicates a high diversity of biological functions for PP1 in Plasmodium. Based on the present data and on an earlier study of the Pf interactome, a potential implication of Pips in protein folding/proteolysis, transcription and pathogenicity networks is proposed. The present work provides a starting point for further studies on the structural basis of these interactions and their functions in P. falciparum.

Prediction of GCRV virus-host protein interactome based on structural motif-domain interactions.

PubMed

Zhang, Aidi; He, Libo; Wang, Yaping

2017-03-02

Grass carp hemorrhagic disease, caused by grass carp reovirus (GCRV), is the most fatal causative agent in grass carp aquaculture. Protein-protein interactions between virus and host are one avenue through which GCRV can trigger infection and induce disease. Experimental approaches for the detection of host-virus interactome have many inherent limitations, and studies on protein-protein interactions between GCRV and its host remain rare. In this study, based on known motif-domain interaction information, we systematically predicted the GCRV virus-host protein interactome by using motif-domain interaction pair searching strategy. These proteins derived from different domain families and were predicted to interact with different motif patterns in GCRV. JAM-A protein was successfully predicted to interact with motifs of GCRV Sigma1-like protein, and shared the similar binding mode compared with orthoreovirus. Differentially expressed genes during GCRV infection process were extracted and mapped to our predicted interactome, the overlapped genes displayed different tissue expression distributions on the whole, the overall expression level in intestinal is higher than that of other three tissues, which may suggest that the functions of these genes are more active in intestinal. Function annotation and pathway enrichment analysis revealed that the host targets were largely involved in signaling pathway and immune pathway, such as interferon-gamma signaling pathway, VEGF signaling pathway, EGF receptor signaling pathway, B cell activation, and T cell activation. Although the predicted PPIs may contain some false positives due to limited data resource and poor research background in non-model species, the computational method still provide reasonable amount of interactions, which can be further validated by high throughput experiments. The findings of this work will contribute to the development of system biology for GCRV infectious diseases, and help guide the identification of novel receptors of GCRV in its host.

Protein interactome analysis of 12 mitogen-activated protein kinase kinase kinase in rice using a yeast two-hybrid system.

PubMed

Singh, Raksha; Lee, Jae-Eun; Dangol, Sarmina; Choi, Jihyun; Yoo, Ran Hee; Moon, Jae Sun; Shim, Jae-Kyung; Rakwal, Randeep; Agrawal, Ganesh Kumar; Jwa, Nam-Soo

2014-01-01

The mitogen-activated protein kinase (MAPK) cascade is composed at least of MAP3K (for MAPK kinase kinase), MAP2K, and MAPK family modules. These components together play a central role in mediating extracellular signals to the cell and vice versa by interacting with their partner proteins. However, the MAP3K-interacting proteins remain poorly investigated in plants. Here, we utilized a yeast two-hybrid system and bimolecular fluorescence complementation in the model crop rice (Oryza sativa) to map MAP3K-interacting proteins. We identified 12 novel nonredundant interacting protein pairs (IPPs) representing 11 nonredundant interactors using 12 rice MAP3Ks (available as full-length cDNA in the rice KOME (http://cdna01.dna.affrc.go.jp/cDNA/) at the time of experimental design and execution) as bait and a rice seedling cDNA library as prey. Of the 12 MAP3Ks, only six had interacting protein partners. The established MAP3K interactome consisted of two kinases, three proteases, two forkhead-associated domain-containing proteins, two expressed proteins, one E3 ligase, one regulatory protein, and one retrotransposon protein. Notably, no MAP3K showed physical interaction with either MAP2K or MAPK. Seven IPPs (58.3%) were confirmed in vivo by bimolecular fluorescence complementation. Subcellular localization of 14 interactors, together involved in nine IPPs (75%) further provide prerequisite for biological significance of the IPPs. Furthermore, GO of identified interactors predicted their involvement in diverse physiological responses, which were supported by a literature survey. These findings increase our knowledge of the MAP3K-interacting proteins, help in proposing a model of MAPK modules, provide a valuable resource for developing a complete map of the rice MAPK interactome, and allow discussion for translating the interactome knowledge to rice crop improvement against environmental factors. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

PubMed

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

2017-01-01

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

Visualisation and graph-theoretic analysis of a large-scale protein structural interactome

PubMed Central

Bolser, Dan; Dafas, Panos; Harrington, Richard; Park, Jong; Schroeder, Michael

2003-01-01

Background Large-scale protein interaction maps provide a new, global perspective with which to analyse protein function. PSIMAP, the Protein Structural Interactome Map, is a database of all the structurally observed interactions between superfamilies of protein domains with known three-dimensional structure in the PDB. PSIMAP incorporates both functional and evolutionary information into a single network. Results We present a global analysis of PSIMAP using several distinct network measures relating to centrality, interactivity, fault-tolerance, and taxonomic diversity. We found the following results: Centrality: we show that the center and barycenter of PSIMAP do not coincide, and that the superfamilies forming the barycenter relate to very general functions, while those constituting the center relate to enzymatic activity. Interactivity: we identify the P-loop and immunoglobulin superfamilies as the most highly interactive. We successfully use connectivity and cluster index, which characterise the connectivity of a superfamily's neighbourhood, to discover superfamilies of complex I and II. This is particularly significant as the structure of complex I is not yet solved. Taxonomic diversity: we found that highly interactive superfamilies are in general taxonomically very diverse and are thus amongst the oldest. Fault-tolerance: we found that the network is very robust as for the majority of superfamilies removal from the network will not break up the network. Conclusions Overall, we can single out the P-loop containing nucleotide triphosphate hydrolases superfamily as it is the most highly connected and has the highest taxonomic diversity. In addition, this superfamily has the highest interaction rank, is the barycenter of the network (it has the shortest average path to every other superfamily in the network), and is an articulation vertex, whose removal will disconnect the network. More generally, we conclude that the graph-theoretic and taxonomic analysis of PSIMAP is an important step towards the understanding of protein function and could be an important tool for tracing the evolution of life at the molecular level. PMID:14531933

Graphical user interfaces for symbol-oriented database visualization and interaction

NASA Astrophysics Data System (ADS)

Brinkschulte, Uwe; Siormanolakis, Marios; Vogelsang, Holger

1997-04-01

In this approach, two basic services designed for the engineering of computer based systems are combined: a symbol-oriented man-machine-service and a high speed database-service. The man-machine service is used to build graphical user interfaces (GUIs) for the database service; these interfaces are stored using the database service. The idea is to create a GUI-builder and a GUI-manager for the database service based upon the man-machine service using the concept of symbols. With user-definable and predefined symbols, database contents can be visualized and manipulated in a very flexible and intuitive way. Using the GUI-builder and GUI-manager, a user can build and operate its own graphical user interface for a given database according to its needs without writing a single line of code.

Global analysis of host-pathogen interactions that regulate early stage HIV-1 replication

PubMed Central

König, Renate; Zhou, Yingyao; Elleder, Daniel; Diamond, Tracy L.; Bonamy, Ghislain M.C.; Irelan, Jeffrey T.; Chiang, Chih-yuan; Tu, Buu P.; De Jesus, Paul D.; Lilley, Caroline E.; Seidel, Shannon; Opaluch, Amanda M.; Caldwell, Jeremy S.; Weitzman, Matthew D.; Kuhen, Kelli L.; Bandyopadhyay, Sourav; Ideker, Trey; Orth, Anthony P.; Miraglia, Loren J.; Bushman, Frederic D.; Young, John A.; Chanda, Sumit K.

2008-01-01

Human Immunodeficiency Viruses (HIV-1 and HIV-2) rely upon host-encoded proteins to facilitate their replication. Here we combined genome-wide siRNA analyses with interrogation of human interactome databases to assemble a host-pathogen biochemical network containing 213 confirmed host cellular factors and 11 HIV-1-encoded proteins. Protein complexes that regulate ubiquitin conjugation, proteolysis, DNA damage response and RNA splicing were identified as important modulators of early stage HIV-1 infection. Additionally, over 40 new factors were shown to specifically influence initiation and/or kinetics of HIV-1 DNA synthesis, including cytoskeletal regulatory proteins, modulators of post-translational modification, and nucleic acid binding proteins. Finally, fifteen proteins with diverse functional roles, including nuclear transport, prostaglandin synthesis, ubiquitination, and transcription, were found to influence nuclear import or viral DNA integration. Taken together, the multi-scale approach described here has uncovered multiprotein virus-host interactions that likely act in concert to facilitate early steps of HIV-1 infection. PMID:18854154

Proteomics profiling of interactome dynamics by colocalisation analysis (COLA)† †Electronic supplementary information (ESI) available. See DOI: 10.1039/c6mb00701e Click here for additional data file. Click here for additional data file.

PubMed Central

Sailem, Heba Z.; Kümper, Sandra; Tape, Christopher J.; McCully, Ryan R.; Paul, Angela; Anjomani-Virmouni, Sara; Jørgensen, Claus; Poulogiannis, George; Marshall, Christopher J.

2017-01-01

Localisation and protein function are intimately linked in eukaryotes, as proteins are localised to specific compartments where they come into proximity of other functionally relevant proteins. Significant co-localisation of two proteins can therefore be indicative of their functional association. We here present COLA, a proteomics based strategy coupled with a bioinformatics framework to detect protein–protein co-localisations on a global scale. COLA reveals functional interactions by matching proteins with significant similarity in their subcellular localisation signatures. The rapid nature of COLA allows mapping of interactome dynamics across different conditions or treatments with high precision. PMID:27824369

Ocean plankton. Determinants of community structure in the global plankton interactome.

PubMed

Lima-Mendez, Gipsi; Faust, Karoline; Henry, Nicolas; Decelle, Johan; Colin, Sébastien; Carcillo, Fabrizio; Chaffron, Samuel; Ignacio-Espinosa, J Cesar; Roux, Simon; Vincent, Flora; Bittner, Lucie; Darzi, Youssef; Wang, Jun; Audic, Stéphane; Berline, Léo; Bontempi, Gianluca; Cabello, Ana M; Coppola, Laurent; Cornejo-Castillo, Francisco M; d'Ovidio, Francesco; De Meester, Luc; Ferrera, Isabel; Garet-Delmas, Marie-José; Guidi, Lionel; Lara, Elena; Pesant, Stéphane; Royo-Llonch, Marta; Salazar, Guillem; Sánchez, Pablo; Sebastian, Marta; Souffreau, Caroline; Dimier, Céline; Picheral, Marc; Searson, Sarah; Kandels-Lewis, Stefanie; Gorsky, Gabriel; Not, Fabrice; Ogata, Hiroyuki; Speich, Sabrina; Stemmann, Lars; Weissenbach, Jean; Wincker, Patrick; Acinas, Silvia G; Sunagawa, Shinichi; Bork, Peer; Sullivan, Matthew B; Karsenti, Eric; Bowler, Chris; de Vargas, Colomban; Raes, Jeroen

2015-05-22

Species interaction networks are shaped by abiotic and biotic factors. Here, as part of the Tara Oceans project, we studied the photic zone interactome using environmental factors and organismal abundance profiles and found that environmental factors are incomplete predictors of community structure. We found associations across plankton functional types and phylogenetic groups to be nonrandomly distributed on the network and driven by both local and global patterns. We identified interactions among grazers, primary producers, viruses, and (mainly parasitic) symbionts and validated network-generated hypotheses using microscopy to confirm symbiotic relationships. We have thus provided a resource to support further research on ocean food webs and integrating biological components into ocean models. Copyright © 2015, American Association for the Advancement of Science.

A Systems Biology Methodology Combining Transcriptome and Interactome Datasets to Assess the Implications of Cytokinin Signaling for Plant Immune Networks.

PubMed

Kunz, Meik; Dandekar, Thomas; Naseem, Muhammad

2017-01-01

Cytokinins (CKs) play an important role in plant growth and development. Also, several studies highlight the modulatory implications of CKs for plant-pathogen interaction. However, the underlying mechanisms of CK mediating immune networks in plants are still not fully understood. A detailed analysis of high-throughput transcriptome (RNA-Seq and microarrays) datasets under modulated conditions of plant CKs and its mergence with cellular interactome (large-scale protein-protein interaction data) has the potential to unlock the contribution of CKs to plant defense. Here, we specifically describe a detailed systems biology methodology pertinent to the acquisition and analysis of various omics datasets that delineate the role of plant CKs in impacting immune pathways in Arabidopsis.

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Davidson, George S.; Brown, William Michael

2007-09-01

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

NAViGaTing the Micronome – Using Multiple MicroRNA Prediction Databases to Identify Signalling Pathway-Associated MicroRNAs

PubMed Central

Shirdel, Elize A.; Xie, Wing; Mak, Tak W.; Jurisica, Igor

2011-01-01

Background MicroRNAs are a class of small RNAs known to regulate gene expression at the transcript level, the protein level, or both. Since microRNA binding is sequence-based but possibly structure-specific, work in this area has resulted in multiple databases storing predicted microRNA:target relationships computed using diverse algorithms. We integrate prediction databases, compare predictions to in vitro data, and use cross-database predictions to model the microRNA:transcript interactome – referred to as the micronome – to study microRNA involvement in well-known signalling pathways as well as associations with disease. We make this data freely available with a flexible user interface as our microRNA Data Integration Portal — mirDIP (http://ophid.utoronto.ca/mirDIP). Results mirDIP integrates prediction databases to elucidate accurate microRNA:target relationships. Using NAViGaTOR to produce interaction networks implicating microRNAs in literature-based, KEGG-based and Reactome-based pathways, we find these signalling pathway networks have significantly more microRNA involvement compared to chance (p<0.05), suggesting microRNAs co-target many genes in a given pathway. Further examination of the micronome shows two distinct classes of microRNAs; universe microRNAs, which are involved in many signalling pathways; and intra-pathway microRNAs, which target multiple genes within one signalling pathway. We find universe microRNAs to have more targets (p<0.0001), to be more studied (p<0.0002), and to have higher degree in the KEGG cancer pathway (p<0.0001), compared to intra-pathway microRNAs. Conclusions Our pathway-based analysis of mirDIP data suggests microRNAs are involved in intra-pathway signalling. We identify two distinct classes of microRNAs, suggesting a hierarchical organization of microRNAs co-targeting genes both within and between pathways, and implying differential involvement of universe and intra-pathway microRNAs at the disease level. PMID:21364759

DIANA-LncBase v2: indexing microRNA targets on non-coding transcripts.

PubMed

Paraskevopoulou, Maria D; Vlachos, Ioannis S; Karagkouni, Dimitra; Georgakilas, Georgios; Kanellos, Ilias; Vergoulis, Thanasis; Zagganas, Konstantinos; Tsanakas, Panayiotis; Floros, Evangelos; Dalamagas, Theodore; Hatzigeorgiou, Artemis G

2016-01-04

microRNAs (miRNAs) are short non-coding RNAs (ncRNAs) that act as post-transcriptional regulators of coding gene expression. Long non-coding RNAs (lncRNAs) have been recently reported to interact with miRNAs. The sponge-like function of lncRNAs introduces an extra layer of complexity in the miRNA interactome. DIANA-LncBase v1 provided a database of experimentally supported and in silico predicted miRNA Recognition Elements (MREs) on lncRNAs. The second version of LncBase (www.microrna.gr/LncBase) presents an extensive collection of miRNA:lncRNA interactions. The significantly enhanced database includes more than 70 000 low and high-throughput, (in)direct miRNA:lncRNA experimentally supported interactions, derived from manually curated publications and the analysis of 153 AGO CLIP-Seq libraries. The new experimental module presents a 14-fold increase compared to the previous release. LncBase v2 hosts in silico predicted miRNA targets on lncRNAs, identified with the DIANA-microT algorithm. The relevant module provides millions of predicted miRNA binding sites, accompanied with detailed metadata and MRE conservation metrics. LncBase v2 caters information regarding cell type specific miRNA:lncRNA regulation and enables users to easily identify interactions in 66 different cell types, spanning 36 tissues for human and mouse. Database entries are also supported by accurate lncRNA expression information, derived from the analysis of more than 6 billion RNA-Seq reads. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

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

PubMed

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

2016-03-16

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

Struct2Net: a web service to predict protein–protein interactions using a structure-based approach

PubMed Central

Singh, Rohit; Park, Daniel; Xu, Jinbo; Hosur, Raghavendra; Berger, Bonnie

2010-01-01

Struct2Net is a web server for predicting interactions between arbitrary protein pairs using a structure-based approach. Prediction of protein–protein interactions (PPIs) is a central area of interest and successful prediction would provide leads for experiments and drug design; however, the experimental coverage of the PPI interactome remains inadequate. We believe that Struct2Net is the first community-wide resource to provide structure-based PPI predictions that go beyond homology modeling. Also, most web-resources for predicting PPIs currently rely on functional genomic data (e.g. GO annotation, gene expression, cellular localization, etc.). Our structure-based approach is independent of such methods and only requires the sequence information of the proteins being queried. The web service allows multiple querying options, aimed at maximizing flexibility. For the most commonly studied organisms (fly, human and yeast), predictions have been pre-computed and can be retrieved almost instantaneously. For proteins from other species, users have the option of getting a quick-but-approximate result (using orthology over pre-computed results) or having a full-blown computation performed. The web service is freely available at http://struct2net.csail.mit.edu. PMID:20513650

SCOWLP classification: Structural comparison and analysis of protein binding regions

PubMed Central

Teyra, Joan; Paszkowski-Rogacz, Maciej; Anders, Gerd; Pisabarro, M Teresa

2008-01-01

Background Detailed information about protein interactions is critical for our understanding of the principles governing protein recognition mechanisms. The structures of many proteins have been experimentally determined in complex with different ligands bound either in the same or different binding regions. Thus, the structural interactome requires the development of tools to classify protein binding regions. A proper classification may provide a general view of the regions that a protein uses to bind others and also facilitate a detailed comparative analysis of the interacting information for specific protein binding regions at atomic level. Such classification might be of potential use for deciphering protein interaction networks, understanding protein function, rational engineering and design. Description Protein binding regions (PBRs) might be ideally described as well-defined separated regions that share no interacting residues one another. However, PBRs are often irregular, discontinuous and can share a wide range of interacting residues among them. The criteria to define an individual binding region can be often arbitrary and may differ from other binding regions within a protein family. Therefore, the rational behind protein interface classification should aim to fulfil the requirements of the analysis to be performed. We extract detailed interaction information of protein domains, peptides and interfacial solvent from the SCOWLP database and we classify the PBRs of each domain family. For this purpose, we define a similarity index based on the overlapping of interacting residues mapped in pair-wise structural alignments. We perform our classification with agglomerative hierarchical clustering using the complete-linkage method. Our classification is calculated at different similarity cut-offs to allow flexibility in the analysis of PBRs, feature especially interesting for those protein families with conflictive binding regions. The hierarchical classification of PBRs is implemented into the SCOWLP database and extends the SCOP classification with three additional family sub-levels: Binding Region, Interface and Contacting Domains. SCOWLP contains 9,334 binding regions distributed within 2,561 families. In 65% of the cases we observe families containing more than one binding region. Besides, 22% of the regions are forming complex with more than one different protein family. Conclusion The current SCOWLP classification and its web application represent a framework for the study of protein interfaces and comparative analysis of protein family binding regions. This comparison can be performed at atomic level and allows the user to study interactome conservation and variability. The new SCOWLP classification may be of great utility for reconstruction of protein complexes, understanding protein networks and ligand design. SCOWLP will be updated with every SCOP release. The web application is available at . PMID:18182098

Comparative Metabolite Fingerprinting of the Rumen System during Colonisation of Three Forage Grass (Lolium perenne L.) Varieties

PubMed Central

Kingston-Smith, Alison H.; Davies, Teri E.; Rees Stevens, Pauline; Mur, Luis A. J.

2013-01-01

The rumen microbiota enable ruminants to degrade complex ligno-cellulosic compounds to produce high quality protein for human consumption. However, enteric fermentation by domestic ruminants generates negative by-products: greenhouse gases (methane) and environmental nitrogen pollution. The current lack of cultured isolates representative of the totality of rumen microbial species creates an information gap about the in vivo function of the rumen microbiota and limits our ability to apply predictive biology for improvement of feed for ruminants. In this work we took a whole ecosystem approach to understanding how the metabolism of the microbial population responds to introduction of its substrate. Fourier Transform Infra Red (FTIR) spectroscopy-based metabolite fingerprinting was used to discriminate differences in the plant-microbial interactome of the rumen when using three forage grass varieties (Lolium perenne L. cv AberDart, AberMagic and Premium) as substrates for microbial colonisation and fermentation. Specific examination of spectral regions associated with fatty acids, amides, sugars and alkanes indicated that although the three forages were apparently similar by traditional nutritional analysis, patterns of metabolite flux within the plant-microbial interactome were distinct and plant genotype dependent. Thus, the utilisation pattern of forage nutrients by the rumen microbiota can be influenced by subtleties determined by forage genotypes. These data suggest that our interactomic approach represents an important means to improve forages and ultimately the livestock environment. PMID:24312434

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

PubMed Central

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

2016-01-01

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

The cyclin D1-CDK4 oncogenic interactome enables identification of potential novel oncogenes and clinical prognosis

PubMed Central

Jirawatnotai, Siwanon; Sharma, Samanta; Michowski, Wojciech; Suktitipat, Bhoom; Geng, Yan; Quackenbush, John; Elias, Joshua E; Gygi, Steven P; Wang, Yaoyu E; Sicinski, Piotr

2014-01-01

Overexpression of cyclin D1 and its catalytic partner, CDK4, is frequently seen in human cancers. We constructed cyclin D1 and CDK4 protein interaction network in a human breast cancer cell line MCF7, and identified novel CDK4 protein partners. Among CDK4 interactors we observed several proteins functioning in protein folding and in complex assembly. One of the novel partners of CDK4 is FKBP5, which we found to be required to maintain CDK4 levels in cancer cells. An integrative analysis of the extended cyclin D1 cancer interactome and somatic copy number alterations in human cancers identified BAIAPL21 as a potential novel human oncogene. We observed that in several human tumor types BAIAPL21 is expressed at higher levels as compared to normal tissue. Forced overexpression of BAIAPL21 augmented anchorage independent growth, increased colony formation by cancer cells and strongly enhanced the ability of cells to form tumors in vivo. Lastly, we derived an Aggregate Expression Score (AES), which quantifies the expression of all cyclin D1 interactors in a given tumor. We observed that AES has a prognostic value among patients with ER-positive breast cancers. These studies illustrate the utility of analyzing the interactomes of proteins involved in cancer to uncover potential oncogenes, or to allow better cancer prognosis. PMID:25486477

Interactome-transcriptome analysis discovers signatures complementary to GWAS Loci of Type 2 Diabetes

PubMed Central

Li, Jing-Woei; Lee, Heung-Man; Wang, Ying; Tong, Amy Hin-Yan; Yip, Kevin Y.; Tsui, Stephen Kwok-Wing; Lok, Si; Ozaki, Risa; Luk, Andrea O; Kong, Alice P. S.; So, Wing-Yee; Ma, Ronald C. W.; Chan, Juliana C. N.; Chan, Ting-Fung

2016-01-01

Protein interactions play significant roles in complex diseases. We analyzed peripheral blood mononuclear cells (PBMC) transcriptome using a multi-method strategy. We constructed a tissue-specific interactome (T2Di) and identified 420 molecular signatures associated with T2D-related comorbidity and symptoms, mainly implicated in inflammation, adipogenesis, protein phosphorylation and hormonal secretion. Apart from explaining the residual associations within the DIAbetes Genetics Replication And Meta-analysis (DIAGRAM) study, the T2Di signatures were enriched in pathogenic cell type-specific regulatory elements related to fetal development, immunity and expression quantitative trait loci (eQTL). The T2Di revealed a novel locus near a well-established GWAS loci AChE, in which SRRT interacts with JAZF1, a T2D-GWAS gene implicated in pancreatic function. The T2Di also included known anti-diabetic drug targets (e.g. PPARD, MAOB) and identified possible druggable targets (e.g. NCOR2, PDGFR). These T2Di signatures were validated by an independent computational method, and by expression data of pancreatic islet, muscle and liver with some of the signatures (CEBPB, SREBF1, MLST8, SRF, SRRT and SLC12A9) confirmed in PBMC from an independent cohort of 66 T2D and 66 control subjects. By combining prior knowledge and transcriptome analysis, we have constructed an interactome to explain the multi-layered regulatory pathways in T2D. PMID:27752041

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

PubMed Central

Carter, C. J.

2013-01-01

Toxoplasma gondii is not only implicated in schizophrenia and related disorders, but also in Alzheimer's or Parkinson's disease, cancer, cardiac myopathies, and autoimmune disorders. During its life cycle, the pathogen interacts with ~3000 host genes or proteins. Susceptibility genes for multiple sclerosis, Alzheimer's disease, schizophrenia, bipolar disorder, depression, childhood obesity, Parkinson's disease, attention deficit hyperactivity disorder (P  from  8.01E − 05  (ADHD)  to  1.22E − 71) (multiple sclerosis), and autism (P = 0.013), but not anorexia or chronic fatigue are highly enriched in the human arm of this interactome and 18 (ADHD) to 33% (MS) of the susceptibility genes relate to it. The signalling pathways involved in the susceptibility gene/interactome overlaps are relatively specific and relevant to each disease suggesting a means whereby susceptibility genes could orient the attentions of a single pathogen towards disruption of the specific pathways that together contribute (positively or negatively) to the endophenotypes of different diseases. Conditional protein knockdown, orchestrated by T. gondii proteins or antibodies binding to those of the host (pathogen derived autoimmunity) and metabolite exchange, may contribute to this disruption. Susceptibility genes may thus be related to the causes and influencers of disease, rather than (and as well as) to the disease itself. PMID:23533776

Caspofungin exposure alters the core septin AspB interactome of Aspergillus fumigatus.

PubMed

Vargas-Muñiz, José M; Renshaw, Hilary; Waitt, Greg; Soderblom, Erik J; Moseley, M Arthur; Palmer, Jonathan M; Juvvadi, Praveen R; Keller, Nancy P; Steinbach, William J

2017-04-01

Aspergillus fumigatus, the main etiological agent of invasive aspergillosis, is a leading cause of death in immunocompromised patients. Septins, a conserved family of GTP-binding proteins, serve as scaffolding proteins to recruit enzymes and key regulators to different cellular compartments. Deletion of the A. fumigatus septin aspB increases susceptibility to the echinocandin antifungal caspofungin. However, how AspB mediates this response to caspofungin is unknown. Here, we characterized the AspB interactome under basal conditions and after exposure to a clinically relevant concentration of caspofungin. While A. fumigatus AspB interacted with 334 proteins, including kinases, cell cycle regulators, and cell wall synthesis-related proteins under basal growth conditions, caspofungin exposure altered AspB interactions. A total of 69 of the basal interactants did not interact with AspB after exposure to caspofungin, and 54 new interactants were identified following caspofungin exposure. We generated A. fumigatus deletion strains for 3 proteins (ArpB, Cyp4, and PpoA) that only interacted with AspB following exposure to caspofungin that were previously annotated as induced after exposure to antifungal agents, yet only PpoA was implicated in the response to caspofungin. Taken together, we defined how the septin AspB interactome is altered in the presence of a clinically relevant antifungal. Copyright © 2017 Elsevier Inc. All rights reserved.

Privacy-Aware Location Database Service for Granular Queries

NASA Astrophysics Data System (ADS)

Kiyomoto, Shinsaku; Martin, Keith M.; Fukushima, Kazuhide

Future mobile markets are expected to increasingly embrace location-based services. This paper presents a new system architecture for location-based services, which consists of a location database and distributed location anonymizers. The service is privacy-aware in the sense that the location database always maintains a degree of anonymity. The location database service permits three different levels of query and can thus be used to implement a wide range of location-based services. Furthermore, the architecture is scalable and employs simple functions that are similar to those found in general database systems.

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

PubMed

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

2012-01-01

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

DataBase on Demand

NASA Astrophysics Data System (ADS)

Gaspar Aparicio, R.; Gomez, D.; Coterillo Coz, I.; Wojcik, D.

2012-12-01

At CERN a number of key database applications are running on user-managed MySQL database services. The database on demand project was born out of an idea to provide the CERN user community with an environment to develop and run database services outside of the actual centralised Oracle based database services. The Database on Demand (DBoD) empowers the user to perform certain actions that had been traditionally done by database administrators, DBA's, providing an enterprise platform for database applications. It also allows the CERN user community to run different database engines, e.g. presently open community version of MySQL and single instance Oracle database server. This article describes a technology approach to face this challenge, a service level agreement, the SLA that the project provides, and an evolution of possible scenarios.

Database on Demand: insight how to build your own DBaaS

NASA Astrophysics Data System (ADS)

Gaspar Aparicio, Ruben; Coterillo Coz, Ignacio

2015-12-01

At CERN, a number of key database applications are running on user-managed MySQL, PostgreSQL and Oracle database services. The Database on Demand (DBoD) project was born out of an idea to provide CERN user community with an environment to develop and run database services as a complement to the central Oracle based database service. The Database on Demand empowers the user to perform certain actions that had been traditionally done by database administrators, providing an enterprise platform for database applications. It also allows the CERN user community to run different database engines, e.g. presently three major RDBMS (relational database management system) vendors are offered. In this article we show the actual status of the service after almost three years of operations, some insight of our new redesign software engineering and near future evolution.

Field Validation of Food Service Listings: A Comparison of Commercial and Online Geographic Information System Databases

PubMed Central

Seliske, Laura; Pickett, William; Bates, Rebecca; Janssen, Ian

2012-01-01

Many studies examining the food retail environment rely on geographic information system (GIS) databases for location information. The purpose of this study was to validate information provided by two GIS databases, comparing the positional accuracy of food service places within a 1 km circular buffer surrounding 34 schools in Ontario, Canada. A commercial database (InfoCanada) and an online database (Yellow Pages) provided the addresses of food service places. Actual locations were measured using a global positioning system (GPS) device. The InfoCanada and Yellow Pages GIS databases provided the locations for 973 and 675 food service places, respectively. Overall, 749 (77.1%) and 595 (88.2%) of these were located in the field. The online database had a higher proportion of food service places found in the field. The GIS locations of 25% of the food service places were located within approximately 15 m of their actual location, 50% were within 25 m, and 75% were within 50 m. This validation study provided a detailed assessment of errors in the measurement of the location of food service places in the two databases. The location information was more accurate for the online database, however, when matching criteria were more conservative, there were no observed differences in error between the databases. PMID:23066385

Field validation of food service listings: a comparison of commercial and online geographic information system databases.

PubMed

Seliske, Laura; Pickett, William; Bates, Rebecca; Janssen, Ian

2012-08-01

Many studies examining the food retail environment rely on geographic information system (GIS) databases for location information. The purpose of this study was to validate information provided by two GIS databases, comparing the positional accuracy of food service places within a 1 km circular buffer surrounding 34 schools in Ontario, Canada. A commercial database (InfoCanada) and an online database (Yellow Pages) provided the addresses of food service places. Actual locations were measured using a global positioning system (GPS) device. The InfoCanada and Yellow Pages GIS databases provided the locations for 973 and 675 food service places, respectively. Overall, 749 (77.1%) and 595 (88.2%) of these were located in the field. The online database had a higher proportion of food service places found in the field. The GIS locations of 25% of the food service places were located within approximately 15 m of their actual location, 50% were within 25 m, and 75% were within 50 m. This validation study provided a detailed assessment of errors in the measurement of the location of food service places in the two databases. The location information was more accurate for the online database, however, when matching criteria were more conservative, there were no observed differences in error between the databases.

Predicted Arabidopsis Interactome Resource and Gene Set Linkage Analysis: A Transcriptomic Analysis Resource.

PubMed

Yao, Heng; Wang, Xiaoxuan; Chen, Pengcheng; Hai, Ling; Jin, Kang; Yao, Lixia; Mao, Chuanzao; Chen, Xin

2018-05-01

An advanced functional understanding of omics data is important for elucidating the design logic of physiological processes in plants and effectively controlling desired traits in plants. We present the latest versions of the Predicted Arabidopsis Interactome Resource (PAIR) and of the gene set linkage analysis (GSLA) tool, which enable the interpretation of an observed transcriptomic change (differentially expressed genes [DEGs]) in Arabidopsis ( Arabidopsis thaliana ) with respect to its functional impact for biological processes. PAIR version 5.0 integrates functional association data between genes in multiple forms and infers 335,301 putative functional interactions. GSLA relies on this high-confidence inferred functional association network to expand our perception of the functional impacts of an observed transcriptomic change. GSLA then interprets the biological significance of the observed DEGs using established biological concepts (annotation terms), describing not only the DEGs themselves but also their potential functional impacts. This unique analytical capability can help researchers gain deeper insights into their experimental results and highlight prospective directions for further investigation. We demonstrate the utility of GSLA with two case studies in which GSLA uncovered how molecular events may have caused physiological changes through their collective functional influence on biological processes. Furthermore, we showed that typical annotation-enrichment tools were unable to produce similar insights to PAIR/GSLA. The PAIR version 5.0-inferred interactome and GSLA Web tool both can be accessed at http://public.synergylab.cn/pair/. © 2018 American Society of Plant Biologists. All Rights Reserved.

Transcriptomic Analysis of the Claudin Interactome in Malignant Pleural Mesothelioma: Evaluation of the Effect of Disease Phenotype, Asbestos Exposure, and CDKN2A Deletion Status

PubMed Central

Rouka, Erasmia; Vavougios, Georgios D.; Solenov, Evgeniy I.; Gourgoulianis, Konstantinos I.; Hatzoglou, Chrissi; Zarogiannis, Sotirios G.

2017-01-01

Malignant pleural mesothelioma (MPM) is a highly aggressive tumor primarily associated with asbestos exposure. Early detection of MPM is restricted by the long latency period until clinical presentation, the ineffectiveness of imaging techniques in early stage detection and the lack of non-invasive biomarkers with high sensitivity and specificity. In this study we used transcriptome data mining in order to determine which CLAUDIN (CLDN) genes are differentially expressed in MPM as compared to controls. Using the same approach we identified the interactome of the differentially expressed CLDN genes and assessed their expression profile. Subsequently, we evaluated the effect of tumor histology, asbestos exposure, CDKN2A deletion status, and gender on the gene expression level of the claudin interactome. We found that 5 out of 15 studied CLDNs (4, 5, 8, 10, 15) and 4 out of 27 available interactors (S100B, SHBG, CDH5, CXCL8) were differentially expressed in MPM specimens vs. healthy tissues. The genes encoding the CLDN-15 and S100B proteins present differences in their expression profile between the three histological subtypes of MPM. Moreover, CLDN-15 is significantly under-expressed in the cohort of patients with previous history of asbestos exposure. CLDN-15 was also found significantly underexpressed in patients lacking the CDKN2A gene. These results warrant the detailed in vitro investigation of the role of CDLN-15 in the pathobiology of MPM. PMID:28377727

Transcriptomic Analysis of the Claudin Interactome in Malignant Pleural Mesothelioma: Evaluation of the Effect of Disease Phenotype, Asbestos Exposure, and CDKN2A Deletion Status.

PubMed

Rouka, Erasmia; Vavougios, Georgios D; Solenov, Evgeniy I; Gourgoulianis, Konstantinos I; Hatzoglou, Chrissi; Zarogiannis, Sotirios G

2017-01-01

Malignant pleural mesothelioma (MPM) is a highly aggressive tumor primarily associated with asbestos exposure. Early detection of MPM is restricted by the long latency period until clinical presentation, the ineffectiveness of imaging techniques in early stage detection and the lack of non-invasive biomarkers with high sensitivity and specificity. In this study we used transcriptome data mining in order to determine which CLAUDIN (CLDN) genes are differentially expressed in MPM as compared to controls. Using the same approach we identified the interactome of the differentially expressed CLDN genes and assessed their expression profile. Subsequently, we evaluated the effect of tumor histology, asbestos exposure, CDKN2A deletion status, and gender on the gene expression level of the claudin interactome. We found that 5 out of 15 studied CLDNs ( 4, 5, 8, 10, 15 ) and 4 out of 27 available interactors ( S100B, SHBG, CDH5, CXCL8 ) were differentially expressed in MPM specimens vs. healthy tissues. The genes encoding the CLDN-15 and S100B proteins present differences in their expression profile between the three histological subtypes of MPM. Moreover, CLDN-15 is significantly under-expressed in the cohort of patients with previous history of asbestos exposure. CLDN-15 was also found significantly underexpressed in patients lacking the CDKN2A gene. These results warrant the detailed in vitro investigation of the role of CDLN-15 in the pathobiology of MPM.

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

PubMed Central

Khatri, Nisha; Mudgil, Yashwanti

2015-01-01

N-MYC DOWNREGULATED-LIKE proteins (NDL), members of the alpha/beta hydrolase superfamily were recently rediscovered as interactors of G-protein signaling in Arabidopsis thaliana. Although the precise molecular function of NDL proteins is still elusive, in animals these proteins play protective role in hypoxia and expression is induced by hypoxia and nickel, indicating role in stress. Homology of NDL1 with animal counterpart N-MYC DOWNREGULATED GENE (NDRG) suggests similar functions in animals and plants. It is well established that stress responses leads to the microtubule depolymerization and reorganization which is crucial for stress tolerance. NDRG is a microtubule-associated protein which mediates the microtubule organization in animals by causing acetylation and increases the stability of α-tubulin. As NDL1 is highly homologous to NDRG, involvement of NDL1 in the microtubule organization during plant stress can also be expected. Discovery of interaction of NDL with protein kinesin light chain- related 1, enodomembrane family protein 70, syntaxin-23, tubulin alpha-2 chain, as a part of G protein interactome initiative encourages us to postulate microtubule stabilizing functions for NDL family in plants. Our search for NDL interactors in G protein interactome also predicts the role of NDL proteins in abiotic stress tolerance management. Based on published report in animals and predicted interacting partners for NDL in G protein interactome lead us to hypothesize involvement of NDL in the microtubule organization during abiotic stress management in plants. PMID:26583023

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

PubMed

Khatri, Nisha; Mudgil, Yashwanti

2015-01-01

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

NR4A nuclear receptors are orphans but not lonesome.

PubMed

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

2014-11-01

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

47 CFR 52.101 - General definitions.

Code of Federal Regulations, 2013 CFR

2013-10-01

... Center (“NASC”). The entity that provides user support for the Service Management System database and administers the Service Management System database on a day-to-day basis. (b) Responsible Organization (“Resp... regional databases in the toll free network. (d) Service Management System Database (“SMS Database”). The...

47 CFR 52.101 - General definitions.

Code of Federal Regulations, 2011 CFR

2011-10-01

... Center (“NASC”). The entity that provides user support for the Service Management System database and administers the Service Management System database on a day-to-day basis. (b) Responsible Organization (“Resp... regional databases in the toll free network. (d) Service Management System Database (“SMS Database”). The...

47 CFR 52.101 - General definitions.

Code of Federal Regulations, 2014 CFR

2014-10-01

... Center (“NASC”). The entity that provides user support for the Service Management System database and administers the Service Management System database on a day-to-day basis. (b) Responsible Organization (“Resp... regional databases in the toll free network. (d) Service Management System Database (“SMS Database”). The...

76 FR 59170 - Hartford Financial Services, Inc., Corporate/EIT/CTO Database Management Division, Hartford, CT...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-09-23

... Services, Inc., Corporate/EIT/CTO Database Management Division, Hartford, CT; Notice of Negative... Services, Inc., Corporate/EIT/CTO Database Management Division, Hartford, Connecticut (The Hartford, Corporate/EIT/CTO Database Management Division). The negative determination was issued on August 19, 2011...

47 CFR 52.101 - General definitions.

Code of Federal Regulations, 2010 CFR

2010-10-01

... Center (“NASC”). The entity that provides user support for the Service Management System database and administers the Service Management System database on a day-to-day basis. (b) Responsible Organization (“Resp... regional databases in the toll free network. (d) Service Management System Database (“SMS Database”). The...

47 CFR 52.101 - General definitions.

Code of Federal Regulations, 2012 CFR

2012-10-01

... Center (“NASC”). The entity that provides user support for the Service Management System database and administers the Service Management System database on a day-to-day basis. (b) Responsible Organization (“Resp... regional databases in the toll free network. (d) Service Management System Database (“SMS Database”). The...

Inferring Higher Functional Information for RIKEN Mouse Full-Length cDNA Clones With FACTS

PubMed Central

Nagashima, Takeshi; Silva, Diego G.; Petrovsky, Nikolai; Socha, Luis A.; Suzuki, Harukazu; Saito, Rintaro; Kasukawa, Takeya; Kurochkin, Igor V.; Konagaya, Akihiko; Schönbach, Christian

2003-01-01

FACTS (Functional Association/Annotation of cDNA Clones from Text/Sequence Sources) is a semiautomated knowledge discovery and annotation system that integrates molecular function information derived from sequence analysis results (sequence inferred) with functional information extracted from text. Text-inferred information was extracted from keyword-based retrievals of MEDLINE abstracts and by matching of gene or protein names to OMIM, BIND, and DIP database entries. Using FACTS, we found that 47.5% of the 60,770 RIKEN mouse cDNA FANTOM2 clone annotations were informative for text searches. MEDLINE queries yielded molecular interaction-containing sentences for 23.1% of the clones. When disease MeSH and GO terms were matched with retrieved abstracts, 22.7% of clones were associated with potential diseases, and 32.5% with GO identifiers. A significant number (23.5%) of disease MeSH-associated clones were also found to have a hereditary disease association (OMIM Morbidmap). Inferred neoplastic and nervous system disease represented 49.6% and 36.0% of disease MeSH-associated clones, respectively. A comparison of sequence-based GO assignments with informative text-based GO assignments revealed that for 78.2% of clones, identical GO assignments were provided for that clone by either method, whereas for 21.8% of clones, the assignments differed. In contrast, for OMIM assignments, only 28.5% of clones had identical sequence-based and text-based OMIM assignments. Sequence, sentence, and term-based functional associations are included in the FACTS database (http://facts.gsc.riken.go.jp/), which permits results to be annotated and explored through web-accessible keyword and sequence search interfaces. The FACTS database will be a critical tool for investigating the functional complexity of the mouse transcriptome, cDNA-inferred interactome (molecular interactions), and pathome (pathologies). PMID:12819151

New Directions in Library and Information Science Education. Final Report. Volume 2.6: Database Distributor/Service Professional Competencies.

ERIC Educational Resources Information Center

Griffiths, Jose-Marie; And Others

This document contains validated activities and competencies needed by librarians working in a database distributor/service organization. The activities of professionals working in database distributor/service organizations are listed by function: Database Processing; Customer Support; System Administration; and Planning. The competencies are…

A survey of the interactome of Kaposi's sarcoma-associated herpesvirus ORF45 revealed its binding to viral ORF33 and cellular USP7, resulting in stabilization of ORF33 that is required for production of progeny viruses.

PubMed

Gillen, Joseph; Li, Wenwei; Liang, Qiming; Avey, Denis; Wu, Jianjun; Wu, Fayi; Myoung, JinJong; Zhu, Fanxiu

2015-05-01

The ORF45 protein of Kaposi's sarcoma-associated herpesvirus (KSHV) is a gammaherpesvirus-specific immediate-early tegument protein. Our previous studies have revealed its crucial roles in both early and late stages of KSHV infection. In this study, we surveyed the interactome of ORF45 using a panel of monoclonal antibodies. In addition to the previously identified extracellular regulated kinase (ERK) and p90 ribosomal S6 kinase (RSK) proteins, we found several other copurified proteins, including prominent ones of ∼38 kDa and ∼130 kDa. Mass spectrometry revealed that the 38-kDa protein is viral ORF33 and the 130-kDa protein is cellular USP7 (ubiquitin-specific protease 7). We mapped the ORF33-binding domain to the highly conserved carboxyl-terminal 19 amino acids (aa) of ORF45 and the USP7-binding domain to the reported consensus motif in the central region of ORF45. Using immunofluorescence staining, we observed colocalization of ORF45 with ORF33 or USP7 both under transfected conditions and in KSHV-infected cells. Moreover, we noticed ORF45-dependent relocalization of a portion of ORF33/USP7 from the nucleus to the cytoplasm. We found that ORF45 caused an increase in ORF33 protein accumulation that was abolished if either the ORF33- or USP7-binding domain in ORF45 was deleted. Furthermore, deletion of the conserved carboxyl terminus of ORF45 in the KSHV genome drastically reduced the level of ORF33 protein in KSHV-infected cells and abolished production of progeny virions. Collectively, our results not only reveal new components of the ORF45 interactome, but also demonstrate that the interactions among these proteins are crucial for KSHV lytic replication. Kaposi's sarcoma-associated herpesvirus (KSHV) is the causative agent of several human cancers. KSHV ORF45 is a multifunctional protein that is required for KSHV lytic replication, but the exact mechanisms by which ORF45 performs its critical functions are unclear. Our previous studies revealed that all ORF45 protein in cells exists in high-molecular-weight complexes. We therefore sought to characterize the interactome of ORF45 to provide insights into its roles during lytic replication. Using a panel of monoclonal antibodies, we surveyed the ORF45 interactome in KSHV-infected cells. We identified two new binding partners of ORF45: the viral protein ORF33 and cellular ubiquitin-specific protease 7 (USP7). We further demonstrate that the interaction between ORF45 and ORF33 is crucial for the efficient production of KSHV viral particles, suggesting that the targeted interference with this interaction may represent a novel strategy to inhibit KSHV lytic replication. Copyright © 2015, American Society for Microbiology. All Rights Reserved.

Modeling microbial communities: current, developing, and future technologies for predicting microbial community interaction.

PubMed

Larsen, Peter; Hamada, Yuki; Gilbert, Jack

2012-07-31

Never has there been a greater opportunity for investigating microbial communities. Not only are the profound effects of microbial ecology on every aspect of Earth's geochemical cycles beginning to be understood, but also the analytical and computational tools for investigating microbial Earth are undergoing a rapid revolution. This environmental microbial interactome, the system of interactions between the microbiome and the environment, has shaped the planet's past and will undoubtedly continue to do so in the future. We review recent approaches for modeling microbial community structures and the interactions of microbial populations with their environments. Different modeling approaches consider the environmental microbial interactome from different aspects, and each provides insights to different facets of microbial ecology. We discuss the challenges and opportunities for the future of microbial modeling and describe recent advances in microbial community modeling that are extending current descriptive technologies into a predictive science. Copyright © 2012 Elsevier B.V. All rights reserved.

Prediction of missing common genes for disease pairs using network based module separation on incomplete human interactome.

PubMed

Akram, Pakeeza; Liao, Li

2017-12-06

Identification of common genes associated with comorbid diseases can be critical in understanding their pathobiological mechanism. This work presents a novel method to predict missing common genes associated with a disease pair. Searching for missing common genes is formulated as an optimization problem to minimize network based module separation from two subgraphs produced by mapping genes associated with disease onto the interactome. Using cross validation on more than 600 disease pairs, our method achieves significantly higher average receiver operating characteristic ROC Score of 0.95 compared to a baseline ROC score 0.60 using randomized data. Missing common genes prediction is aimed to complete gene set associated with comorbid disease for better understanding of biological intervention. It will also be useful for gene targeted therapeutics related to comorbid diseases. This method can be further considered for prediction of missing edges to complete the subgraph associated with disease pair.

The NRF2-related interactome and regulome contain multifunctional proteins and fine-tuned autoregulatory loops.

PubMed

Papp, Diána; Lenti, Katalin; Módos, Dezső; Fazekas, Dávid; Dúl, Zoltán; Türei, Dénes; Földvári-Nagy, László; Nussinov, Ruth; Csermely, Péter; Korcsmáros, Tamás

2012-06-21

NRF2 is a well-known, master transcription factor (TF) of oxidative and xenobiotic stress responses. Recent studies uncovered an even wider regulatory role of NRF2 influencing carcinogenesis, inflammation and neurodegeneration. Prompted by these advances here we present a systems-level resource for NRF2 interactome and regulome that includes 289 protein-protein, 7469 TF-DNA and 85 miRNA interactions. As systems-level examples of NRF2-related signaling we identified regulatory loops of NRF2 interacting proteins (e.g., JNK1 and CBP) and a fine-tuned regulatory system, where 35 TFs regulated by NRF2 influence 63 miRNAs that down-regulate NRF2. The presented network and the uncovered regulatory loops may facilitate the development of efficient, NRF2-based therapeutic agents. Copyright © 2012 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

Mapping the local protein interactome of the NuA3 histone acetyltransferase

PubMed Central

Smart, Sherri K; Mackintosh, Samuel G; Edmondson, Ricky D; Taverna, Sean D; Tackett, Alan J

2009-01-01

Protein–protein interactions modulate cellular functions ranging from the activity of enzymes to signal transduction cascades. A technology termed transient isotopic differentiation of interactions as random or targeted (transient I-DIRT) is described for the identification of stable and transient protein–protein interactions in vivo. The procedure combines mild in vivo chemical cross-linking and non-stringent affinity purification to isolate low abundance chromatin-associated protein complexes. Using isotopic labeling and mass spectrometric readout, purified proteins are categorized with respect to the protein ‘bait’ as stable, transient, or contaminant. Here we characterize the local interactome of the chromatin-associated NuA3 histone lysine-acetyltransferase protein complex. We describe transient associations with the yFACT nucleosome assembly complex, RSC chromatin remodeling complex and a nucleosome assembly protein. These novel, physical associations with yFACT, RSC, and Nap1 provide insight into the mechanism of NuA3-associated transcription and chromatin regulation. PMID:19621382

A comparative study of disease genes and drug targets in the human protein interactome

PubMed Central

2015-01-01

Background Disease genes cause or contribute genetically to the development of the most complex diseases. Drugs are the major approaches to treat the complex disease through interacting with their targets. Thus, drug targets are critical for treatment efficacy. However, the interrelationship between the disease genes and drug targets is not clear. Results In this study, we comprehensively compared the network properties of disease genes and drug targets for five major disease categories (cancer, cardiovascular disease, immune system disease, metabolic disease, and nervous system disease). We first collected disease genes from genome-wide association studies (GWAS) for five disease categories and collected their corresponding drugs based on drugs' Anatomical Therapeutic Chemical (ATC) classification. Then, we obtained the drug targets for these five different disease categories. We found that, though the intersections between disease genes and drug targets were small, disease genes were significantly enriched in targets compared to their enrichment in human protein-coding genes. We further compared network properties of the proteins encoded by disease genes and drug targets in human protein-protein interaction networks (interactome). The results showed that the drug targets tended to have higher degree, higher betweenness, and lower clustering coefficient in cancer Furthermore, we observed a clear fraction increase of disease proteins or drug targets in the near neighborhood compared with the randomized genes. Conclusions The study presents the first comprehensive comparison of the disease genes and drug targets in the context of interactome. The results provide some foundational network characteristics for further designing computational strategies to predict novel drug targets and drug repurposing. PMID:25861037

A network biology-based approach to evaluating the effect of environmental contaminants on human interactome and diseases.

PubMed

Iida, M; Takemoto, K

2018-09-30

Environmental contaminant exposure can pose significant risks to human health. Therefore, evaluating the impact of this exposure is of great importance; however, it is often difficult because both the molecular mechanism of disease and the mode of action of the contaminants are complex. We used network biology techniques to quantitatively assess the impact of environmental contaminants on the human interactome and diseases with a particular focus on seven major contaminant categories: persistent organic pollutants (POPs), dioxins, polycyclic aromatic hydrocarbons (PAHs), pesticides, perfluorochemicals (PFCs), metals, and pharmaceutical and personal care products (PPCPs). We integrated publicly available data on toxicogenomics, the diseasome, protein-protein interactions (PPIs), and gene essentiality and found that a few contaminants were targeted to many genes, and a few genes were targeted by many contaminants. The contaminant targets were hub proteins in the human PPI network, whereas the target proteins in most categories did not contain abundant essential proteins. Generally, contaminant targets and disease-associated proteins were closely associated with the PPI network, and the closeness of the associations depended on the disease type and chemical category. Network biology techniques were used to identify environmental contaminants with broad effects on the human interactome and contaminant-sensitive biomarkers. Moreover, this method enabled us to quantify the relationship between environmental contaminants and human diseases, which was supported by epidemiological and experimental evidence. These methods and findings have facilitated the elucidation of the complex relationship between environmental exposure and adverse health outcomes. Copyright © 2018 Elsevier Inc. All rights reserved.

Identification of the interactome between fish plasma proteins and Edwardsiella tarda reveals tissue-specific strategies against bacterial infection.

PubMed

Li, Hui; Huang, Xiaoyan; Zeng, Zaohai; Peng, Xuan-Xian; Peng, Bo

2016-09-01

Elucidating the complex pathogen-host interaction is essential for a comprehensive understanding of how these remarkable agents invade their hosts and how the hosts defend against these invaders. During the infection, pathogens interact intensively with host to enable their survival, which can be revealed through their interactome. Edwardsiella tarda is a Gram-negative bacterial pathogen causing huge economic loss in aquaculture and a spectrum of intestinal and extraintestinal diseases in humans. E. tarda is an ideal model for host-pathogen investigation as it infects fish in three distinct steps: entering the host, circulating through the blood and establishing infection. We adopted a previous established proteomic approach that inactivated E. tarda cells and covalent crosslink fish plasma proteins were used to capture plasma proteins and bacterial outer membrane proteins, respectively. By the combinatorial use of proteomic and biochemical approaches, six plasma proteins and seven outer membrane proteins (OMPs) were identified. Interactions among these proteins were validated with protein-array, far-Western blotting and co-immunoprecipitation. At last, seventeen plasma protein-bacteria protein-protein interaction were confirmed to be involved in the interaction network, forming a complex interactome. Compared to our previous results, different host proteins were detected, whereas some of the bacterial proteins were similar, which indicates that hosts adopt tissue-specific strategies to cope with the same pathogen during infection. Thus, our results provide a robust demonstration of both bacterial initiators and host receptors or interacting proteins to further explore infection and anti-infective mechanisms between hosts and microbes. Copyright © 2016 Elsevier Ltd. All rights reserved.

Novel candidate genes of the PARK7 interactome as mediators of apoptosis and acetylation in multiple sclerosis: An in silico analysis.

PubMed

Vavougios, George D; Zarogiannis, Sotirios G; Krogfelt, Karen Angeliki; Gourgoulianis, Konstantinos; Mitsikostas, Dimos Dimitrios; Hadjigeorgiou, Georgios

2018-01-01

currently only 4 studies have explored the potential role of PARK7's dysregulation in MS pathophysiology Currently, no study has evaluated the potential role of the PARK7 interactome in MS. The aim of our study was to assess the differential expression of PARK7 mRNA in peripheral blood mononuclears (PBMCs) donated from MS versus healthy patients using data mining techniques. The PARK7 interactome data from the GDS3920 profile were scrutinized for differentially expressed genes (DEGs); Gene Enrichment Analysis (GEA) was used to detect significantly enriched biological functions. 27 differentially expressed genes in the MS dataset were detected; 12 of these (NDUFA4, UBA2, TDP2, NPM1, NDUFS3, SUMO1, PIAS2, KIAA0101, RBBP4, NONO, RBBP7 AND HSPA4) are reported for the first time in MS. Stepwise Linear Discriminant Function Analysis constructed a predictive model (Wilk's λ = 0.176, χ 2 = 45.204, p = 1.5275e -10 ) with 2 variables (TIDP2, RBBP4) that achieved 96.6% accuracy when discriminating between patients and controls. Gene Enrichment Analysis revealed that induction and regulation of programmed / intrinsic cell death represented the most salient Gene Ontology annotations. Cross-validation on systemic lupus erythematosus and ischemic stroke datasets revealed that these functions are unique to the MS dataset. Based on our results, novel potential target genes are revealed; these differentially expressed genes regulate epigenetic and apoptotic pathways that may further elucidate underlying mechanisms of autorreactivity in MS. Copyright © 2017 Elsevier B.V. All rights reserved.

Ovarian Cancer Differential Interactome and Network Entropy Analysis Reveal New Candidate Biomarkers.

PubMed

Ayyildiz, Dilara; Gov, Esra; Sinha, Raghu; Arga, Kazim Yalcin

2017-05-01

Ovarian cancer is one of the most common cancers and has a high mortality rate due to insidious symptoms and lack of robust diagnostics. A hitherto understudied concept in cancer pathogenesis may offer new avenues for innovation in ovarian cancer biomarker development. Cancer cells are characterized by an increase in network entropy, and several studies have exploited this concept to identify disease-associated gene and protein modules. We report in this study the changes in protein-protein interactions (PPIs) in ovarian cancer within a differential network (interactome) analysis framework utilizing the entropy concept and gene expression data. A compendium of six transcriptome datasets that included 140 samples from laser microdissected epithelial cells of ovarian cancer patients and 51 samples from healthy population was obtained from Gene Expression Omnibus, and the high confidence human protein interactome (31,465 interactions among 10,681 proteins) was used. The uncertainties of the up- or downregulation of PPIs in ovarian cancer were estimated through an entropy formulation utilizing combined expression levels of genes, and the interacting protein pairs with minimum uncertainty were identified. We identified 105 proteins with differential PPI patterns scattered in 11 modules, each indicating significantly affected biological pathways in ovarian cancer such as DNA repair, cell proliferation-related mechanisms, nucleoplasmic translocation of estrogen receptor, extracellular matrix degradation, and inflammation response. In conclusion, we suggest several PPIs as biomarker candidates for ovarian cancer and discuss their future biological implications as potential molecular targets for pharmaceutical development as well. In addition, network entropy analysis is a concept that deserves greater research attention for diagnostic innovation in oncology and tumor pathogenesis.

Identification of Human Disease Genes from Interactome Network Using Graphlet Interaction

PubMed Central

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

2014-01-01

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

The Orphan Disease Networks

PubMed Central

Zhang, Minlu; Zhu, Cheng; Jacomy, Alexis; Lu, Long J.; Jegga, Anil G.

2011-01-01

The low prevalence rate of orphan diseases (OD) requires special combined efforts to improve diagnosis, prevention, and discovery of novel therapeutic strategies. To identify and investigate relationships based on shared genes or shared functional features, we have conducted a bioinformatic-based global analysis of all orphan diseases with known disease-causing mutant genes. Starting with a bipartite network of known OD and OD-causing mutant genes and using the human protein interactome, we first construct and topologically analyze three networks: the orphan disease network, the orphan disease-causing mutant gene network, and the orphan disease-causing mutant gene interactome. Our results demonstrate that in contrast to the common disease-causing mutant genes that are predominantly nonessential, a majority of orphan disease-causing mutant genes are essential. In confirmation of this finding, we found that OD-causing mutant genes are topologically important in the protein interactome and are ubiquitously expressed. Additionally, functional enrichment analysis of those genes in which mutations cause ODs shows that a majority result in premature death or are lethal in the orthologous mouse gene knockout models. To address the limitations of traditional gene-based disease networks, we also construct and analyze OD networks on the basis of shared enriched features (biological processes, cellular components, pathways, phenotypes, and literature citations). Analyzing these functionally-linked OD networks, we identified several additional OD-OD relations that are both phenotypically similar and phenotypically diverse. Surprisingly, we observed that the wiring of the gene-based and other feature-based OD networks are largely different; this suggests that the relationship between ODs cannot be fully captured by the gene-based network alone. PMID:21664998

Interactome analysis of longitudinal pharyngeal infection of cynomolgus macaques by group A Streptococcus.

PubMed

Shea, Patrick R; Virtaneva, Kimmo; Kupko, John J; Porcella, Stephen F; Barry, William T; Wright, Fred A; Kobayashi, Scott D; Carmody, Aaron; Ireland, Robin M; Sturdevant, Daniel E; Ricklefs, Stacy M; Babar, Imran; Johnson, Claire A; Graham, Morag R; Gardner, Donald J; Bailey, John R; Parnell, Michael J; Deleo, Frank R; Musser, James M

2010-03-09

Relatively little is understood about the dynamics of global host-pathogen transcriptome changes that occur during bacterial infection of mucosal surfaces. To test the hypothesis that group A Streptococcus (GAS) infection of the oropharynx provokes a distinct host transcriptome response, we performed genome-wide transcriptome analysis using a nonhuman primate model of experimental pharyngitis. We also identified host and pathogen biological processes and individual host and pathogen gene pairs with correlated patterns of expression, suggesting interaction. For this study, 509 host genes and seven biological pathways were differentially expressed throughout the entire 32-day infection cycle. GAS infection produced an initial widespread significant decrease in expression of many host genes, including those involved in cytokine production, vesicle formation, metabolism, and signal transduction. This repression lasted until day 4, at which time a large increase in expression of host genes was observed, including those involved in protein translation, antigen presentation, and GTP-mediated signaling. The interactome analysis identified 73 host and pathogen gene pairs with correlated expression levels. We discovered significant correlations between transcripts of GAS genes involved in hyaluronic capsule production and host endocytic vesicle formation, GAS GTPases and host fibrinolytic genes, and GAS response to interaction with neutrophils. We also identified a strong signal, suggesting interaction between host gammadelta T cells and genes in the GAS mevalonic acid synthesis pathway responsible for production of isopentenyl-pyrophosphate, a short-chain phospholipid that stimulates these T cells. Taken together, our results are unique in providing a comprehensive understanding of the host-pathogen interactome during mucosal infection by a bacterial pathogen.

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

PubMed Central

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

2016-01-01

People with autism spectrum disorder (ASD) and other neurodevelopmental disorders (NDDs) are behaviorally and medically heterogeneous. The combination of polygenicity and gene pleiotropy - the influence of one gene on distinct phenotypes - raises questions of how specific genes and their protein products interact to contribute to NDDs. A preponderance of evidence supports developmental and pathophysiological roles for the MET receptor tyrosine kinase, a multi-functional receptor that mediates distinct biological responses depending upon cell context. MET influences neuron architecture and synapse maturation in the forebrain, and regulates homeostasis in gastrointestinal and immune systems, both commonly disrupted in NDDs. Peak expression of synapse-enriched MET is conserved across rodent and primate forebrain, yet regional differences in primate neocortex are pronounced, with enrichment in circuits that participate in social information processing. A functional risk allele in the MET promoter, enriched in subgroups of children with ASD, reduces transcription and disrupts socially-relevant neural circuits structurally and functionally. In mice, circuit-specific deletion of Met causes distinct atypical behaviors. MET activation increases dendritic complexity and nascent synapse number, but synapse maturation requires reductions in MET. MET mediates its specific biological effects through different intracellular signaling pathways, and has a complex protein interactome that is enriched in ASD and other NDD candidates. The interactome is co-regulated in developing human neocortex. We suggest that a gene as pleiotropic and highly regulated as MET, together with its interactome, is biologically relevant in normal and pathophysiological contexts, impacting central and peripheral phenotypes that contribute to NDD risk and clinical symptoms. PMID:27837921

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

NASA Astrophysics Data System (ADS)

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

2014-10-01

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

A comparative study of disease genes and drug targets in the human protein interactome.

PubMed

Sun, Jingchun; Zhu, Kevin; Zheng, W; Xu, Hua

2015-01-01

Disease genes cause or contribute genetically to the development of the most complex diseases. Drugs are the major approaches to treat the complex disease through interacting with their targets. Thus, drug targets are critical for treatment efficacy. However, the interrelationship between the disease genes and drug targets is not clear. In this study, we comprehensively compared the network properties of disease genes and drug targets for five major disease categories (cancer, cardiovascular disease, immune system disease, metabolic disease, and nervous system disease). We first collected disease genes from genome-wide association studies (GWAS) for five disease categories and collected their corresponding drugs based on drugs' Anatomical Therapeutic Chemical (ATC) classification. Then, we obtained the drug targets for these five different disease categories. We found that, though the intersections between disease genes and drug targets were small, disease genes were significantly enriched in targets compared to their enrichment in human protein-coding genes. We further compared network properties of the proteins encoded by disease genes and drug targets in human protein-protein interaction networks (interactome). The results showed that the drug targets tended to have higher degree, higher betweenness, and lower clustering coefficient in cancer Furthermore, we observed a clear fraction increase of disease proteins or drug targets in the near neighborhood compared with the randomized genes. The study presents the first comprehensive comparison of the disease genes and drug targets in the context of interactome. The results provide some foundational network characteristics for further designing computational strategies to predict novel drug targets and drug repurposing.

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

PubMed

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

2014-07-15

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

Functional Analysis of OMICs Data and Small Molecule Compounds in an Integrated "Knowledge-Based" Platform.

PubMed

Dubovenko, Alexey; Nikolsky, Yuri; Rakhmatulin, Eugene; Nikolskaya, Tatiana

2017-01-01

Analysis of NGS and other sequencing data, gene variants, gene expression, proteomics, and other high-throughput (OMICs) data is challenging because of its biological complexity and high level of technical and biological noise. One way to deal with both problems is to perform analysis with a high fidelity annotated knowledgebase of protein interactions, pathways, and functional ontologies. This knowledgebase has to be structured in a computer-readable format and must include software tools for managing experimental data, analysis, and reporting. Here, we present MetaCore™ and Key Pathway Advisor (KPA), an integrated platform for functional data analysis. On the content side, MetaCore and KPA encompass a comprehensive database of molecular interactions of different types, pathways, network models, and ten functional ontologies covering human, mouse, and rat genes. The analytical toolkit includes tools for gene/protein list enrichment analysis, statistical "interactome" tool for the identification of over- and under-connected proteins in the dataset, and a biological network analysis module made up of network generation algorithms and filters. The suite also features Advanced Search, an application for combinatorial search of the database content, as well as a Java-based tool called Pathway Map Creator for drawing and editing custom pathway maps. Applications of MetaCore and KPA include molecular mode of action of disease research, identification of potential biomarkers and drug targets, pathway hypothesis generation, analysis of biological effects for novel small molecule compounds and clinical applications (analysis of large cohorts of patients, and translational and personalized medicine).

Utilising the EGFR interactome to identify mechanisms of drug resistance in non-small cell lung cancer - Proof of concept towards a systems pharmacology approach.

PubMed

Saafan, Hisham; Foerster, Sarah; Parra-Guillen, Zinnia P; Hammer, Elke; Michaelis, Martin; Cinatl, Jindrich; Völker, Uwe; Fröhlich, Holger; Kloft, Charlotte; Ritter, Christoph A

2016-10-30

Drug treatment of epidermal growth factor receptor (EGFR) positive non-small cell lung cancer has improved substantially by targeting activating mutations within the receptor tyrosine kinase domain. However, the development of drug resistance still limits this approach. As root causes, large heterogeneity between tumour entities but also within tumour cells have been suggested. Therefore, approaches to identify these multitude and complex mechanisms are urgently required. Affinity purification coupled with high resolution mass spectrometry was applied to isolate and characterise the EGFR interactome from HCC4006 non-small cell lung cancer cells and their variant HCC4006 r ERLO 0.5 adapted to grow in the presence of therapeutically relevant concentrations of erlotinib. Bioinformatics analyses were carried out to identify proteins and their related molecular functions that interact differentially with EGFR in the untreated state or when incubated with erlotinib prior to EGFR activation. Across all experimental conditions 375 proteins were detected to participate in the EGFR interactome, 90% of which constituted a complex protein interaction network that was bioinformatically reconstructed from literature data. Treatment of HCC4006 r ERLO 0.5 cells carrying a resistance phenotype to erlotinib was associated with an increase of protein levels of members of the clathrin-associated adaptor protein family AP2 (AP2A1, AP2A2, AP2B1), structural proteins of cytoskeleton rearrangement as well as signalling molecules such as Shc. Validation experiments confirmed activation of the Ras-Raf-Mek-Erk (MAPK)-pathway, of which Shc is an initiating adaptor molecule, in HCC4006 r ERLO 0.5 cells. Taken together, differential proteins in the EGFR interactome of HCC4006 r ERLO 0.5 cells were identified that could be related to multiple resistance mechanisms including alterations in growth factor receptor expression, cellular remodelling processes suggesting epithelial-to-mesenchymal transition as well as alterations in downstream signalling. Knowledge of these mechanisms is a pivotal step to build an integrative model of drug resistance in a systems pharmacology manner and to be able to investigate the interplay of these mechanisms and ultimately recommend combinatorial treatment strategies to overcome drug resistance. Copyright © 2016 Elsevier B.V. All rights reserved.

47 CFR 15.713 - TV bands database.

Code of Federal Regulations, 2011 CFR

2011-10-01

... authorized services operating in the TV bands. In addition, a TV bands database must also verify that the FCC identifier (FCC ID) of a device seeking access to its services is valid; under this requirement the TV bands... information will come from the official Commission database. These services include: (i) Digital television...

47 CFR 51.217 - Nondiscriminatory access: Telephone numbers, operator services, directory assistance services...

Code of Federal Regulations, 2011 CFR

2011-10-01

... to have access to its directory assistance services, including directory assistance databases, so... provider, including transfer of the LECs' directory assistance databases in readily accessible magnetic.... Updates to the directory assistance database shall be made in the same format as the initial transfer...

The Impact of Online Bibliographic Databases on Teaching and Research in Political Science.

ERIC Educational Resources Information Center

Reichel, Mary

The availability of online bibliographic databases greatly facilitates literature searching in political science. The advantages to searching databases online include combination of concepts, comprehensiveness, multiple database searching, free-text searching, currency, current awareness services, document delivery service, and convenience.…

47 CFR 69.118 - Traffic sensitive switched services.

Code of Federal Regulations, 2013 CFR

2013-10-01

... Docket 86-10, FCC 93-53 (1993). Moreover, all customers that use basic 800 database service shall be... account revenues from the relevant Basic Service Element or Elements and 800 Database Service Elements in...

47 CFR 69.118 - Traffic sensitive switched services.

Code of Federal Regulations, 2011 CFR

2011-10-01

... Docket 86-10, FCC 93-53 (1993). Moreover, all customers that use basic 800 database service shall be... account revenues from the relevant Basic Service Element or Elements and 800 Database Service Elements in...

47 CFR 69.118 - Traffic sensitive switched services.

Code of Federal Regulations, 2014 CFR

2014-10-01

... Docket 86-10, FCC 93-53 (1993). Moreover, all customers that use basic 800 database service shall be... account revenues from the relevant Basic Service Element or Elements and 800 Database Service Elements in...

47 CFR 69.118 - Traffic sensitive switched services.

Code of Federal Regulations, 2010 CFR

2010-10-01

... Docket 86-10, FCC 93-53 (1993). Moreover, all customers that use basic 800 database service shall be... account revenues from the relevant Basic Service Element or Elements and 800 Database Service Elements in...

47 CFR 69.118 - Traffic sensitive switched services.

Code of Federal Regulations, 2012 CFR

2012-10-01

... Docket 86-10, FCC 93-53 (1993). Moreover, all customers that use basic 800 database service shall be... account revenues from the relevant Basic Service Element or Elements and 800 Database Service Elements in...

Systems Biology-Based Investigation of Cellular Antiviral Drug Targets Identified by Gene-Trap Insertional Mutagenesis.

PubMed

Cheng, Feixiong; Murray, James L; Zhao, Junfei; Sheng, Jinsong; Zhao, Zhongming; Rubin, Donald H

2016-09-01

Viruses require host cellular factors for successful replication. A comprehensive systems-level investigation of the virus-host interactome is critical for understanding the roles of host factors with the end goal of discovering new druggable antiviral targets. Gene-trap insertional mutagenesis is a high-throughput forward genetics approach to randomly disrupt (trap) host genes and discover host genes that are essential for viral replication, but not for host cell survival. In this study, we used libraries of randomly mutagenized cells to discover cellular genes that are essential for the replication of 10 distinct cytotoxic mammalian viruses, 1 gram-negative bacterium, and 5 toxins. We herein reported 712 candidate cellular genes, characterizing distinct topological network and evolutionary signatures, and occupying central hubs in the human interactome. Cell cycle phase-specific network analysis showed that host cell cycle programs played critical roles during viral replication (e.g. MYC and TAF4 regulating G0/1 phase). Moreover, the viral perturbation of host cellular networks reflected disease etiology in that host genes (e.g. CTCF, RHOA, and CDKN1B) identified were frequently essential and significantly associated with Mendelian and orphan diseases, or somatic mutations in cancer. Computational drug repositioning framework via incorporating drug-gene signatures from the Connectivity Map into the virus-host interactome identified 110 putative druggable antiviral targets and prioritized several existing drugs (e.g. ajmaline) that may be potential for antiviral indication (e.g. anti-Ebola). In summary, this work provides a powerful methodology with a tight integration of gene-trap insertional mutagenesis testing and systems biology to identify new antiviral targets and drugs for the development of broadly acting and targeted clinical antiviral therapeutics.

Host cell interactome of PA protein of H5N1 influenza A virus in chicken cells.

PubMed

Wang, Qiao; Li, Qinghe; Liu, Ranran; Zheng, Maiqing; Wen, Jie; Zhao, Guiping

2016-03-16

Influenza A virus (IAV) heavily depends on viral-host protein interactions in order to replicate and spread. Identification of host factors that interact with viral proteins plays crucial roles in understanding the mechanism of IAV infection. Here we report the interaction landscape of H5N1 IAV PA protein in chicken cells through the use of affinity purification and mass spectrometry. PA protein was expressed in chicken cells and PA interacting complexes were captured by co-immunoprecipitation and analyzed by mass spectrometry. A total of 134 proteins were identified as PA-host interacting factors. Protein complexes including the minichromosome maintenance complex (MCM), 26S proteasome and the coat protein I (COPI) complex associated with PA in chicken cells, indicating the essential roles of these functional protein complexes during the course of IAV infection. Gene Ontology and pathway enrichment analysis both showed strong enrichment of PA interacting proteins in the category of DNA replication, covering genes such as PCNA, MCM2, MCM3, MCM4, MCM5 and MCM7. This study has uncovered the comprehensive interactome of H5N1 IAV PA protein in its chicken host and helps to establish the foundation for further investigation into the newly identified viral-host interactions. Influenza A virus (IAV) is a great threat to public health and avian production. However, the manner in which avian IAV recruits the host cellular machinery for replication and how the host antagonizes the IAV infection was previously poorly understood. Here we present the viral-host interactome of the H5N1 IAV PA protein and reveal the comprehensive association of host factors with PA. Copyright © 2016 Elsevier B.V. All rights reserved.

Oncoprotein AEG-1 is an endoplasmic reticulum RNA-binding protein whose interactome is enriched in organelle resident protein-encoding mRNAs.

PubMed

Hsu, Jack C-C; Reid, David W; Hoffman, Alyson M; Sarkar, Devanand; Nicchitta, Christopher V

2018-05-01

Astrocyte elevated gene-1 (AEG-1), an oncogene whose overexpression promotes tumor cell proliferation, angiogenesis, invasion, and enhanced chemoresistance, is thought to function primarily as a scaffolding protein, regulating PI3K/Akt and Wnt/β-catenin signaling pathways. Here we report that AEG-1 is an endoplasmic reticulum (ER) resident integral membrane RNA-binding protein (RBP). Examination of the AEG-1 RNA interactome by HITS-CLIP and PAR-CLIP methodologies revealed a high enrichment for endomembrane organelle-encoding transcripts, most prominently those encoding ER resident proteins, and within this cohort, for integral membrane protein-encoding RNAs. Cluster mapping of the AEG-1/RNA interaction sites demonstrated a normalized rank order interaction of coding sequence >5' untranslated region, with 3' untranslated region interactions only weakly represented. Intriguingly, AEG-1/membrane protein mRNA interaction sites clustered downstream from encoded transmembrane domains, suggestive of a role in membrane protein biogenesis. Secretory and cytosolic protein-encoding mRNAs were also represented in the AEG-1 RNA interactome, with the latter category notably enriched in genes functioning in mRNA localization, translational regulation, and RNA quality control. Bioinformatic analyses of RNA-binding motifs and predicted secondary structure characteristics indicate that AEG-1 lacks established RNA-binding sites though shares the property of high intrinsic disorder commonly seen in RBPs. These data implicate AEG-1 in the localization and regulation of secretory and membrane protein-encoding mRNAs and provide a framework for understanding AEG-1 function in health and disease. © 2018 Hsu et al.; Published by Cold Spring Harbor Laboratory Press for the RNA Society.

A predicted protein interactome identifies conserved global networks and disease resistance subnetworks in maize

PubMed Central

Musungu, Bryan; Bhatnagar, Deepak; Brown, Robert L.; Fakhoury, Ahmad M.; Geisler, Matt

2015-01-01

Interactomes are genome-wide roadmaps of protein-protein interactions. They have been produced for humans, yeast, the fruit fly, and Arabidopsis thaliana and have become invaluable tools for generating and testing hypotheses. A predicted interactome for Zea mays (PiZeaM) is presented here as an aid to the research community for this valuable crop species. PiZeaM was built using a proven method of interologs (interacting orthologs) that were identified using both one-to-one and many-to-many orthology between genomes of maize and reference species. Where both maize orthologs occurred for an experimentally determined interaction in the reference species, we predicted a likely interaction in maize. A total of 49,026 unique interactions for 6004 maize proteins were predicted. These interactions are enriched for processes that are evolutionarily conserved, but include many otherwise poorly annotated proteins in maize. The predicted maize interactions were further analyzed by comparing annotation of interacting proteins, including different layers of ontology. A map of pairwise gene co-expression was also generated and compared to predicted interactions. Two global subnetworks were constructed for highly conserved interactions. These subnetworks showed clear clustering of proteins by function. Another subnetwork was created for disease response using a bait and prey strategy to capture interacting partners for proteins that respond to other organisms. Closer examination of this subnetwork revealed the connectivity between biotic and abiotic hormone stress pathways. We believe PiZeaM will provide a useful tool for the prediction of protein function and analysis of pathways for Z. mays researchers and is presented in this paper as a reference tool for the exploration of protein interactions in maize. PMID:26089837

Interactome analysis reveals ZNF804A, a schizophrenia risk gene, as a novel component of protein translational machinery critical for embryonic neurodevelopment

PubMed Central

Zhou, Y; Dong, F; Lanz, T A; Reinhart, V; Li, M; Liu, L; Zou, J; Xi, H S; Mao, Y

2018-01-01

Recent genome-wide association studies identified over 100 genetic loci that significantly associate with schizophrenia (SZ). A top candidate gene, ZNF804A, was robustly replicated in different populations. However, its neural functions are largely unknown. Here we show in mouse that ZFP804A, the homolog of ZNF804A, is required for normal progenitor proliferation and neuronal migration. Using a yeast two-hybrid genome-wide screen, we identified novel interacting proteins of ZNF804A. Rather than transcriptional factors, genes involved in mRNA translation are highly represented in our interactome result. ZNF804A co-fractionates with translational machinery and modulates the translational efficiency as well as the mTOR pathway. The ribosomal protein RPSA interacts with ZNF804A and rescues the migration and translational defects caused by ZNF804A knockdown. RNA immunoprecipitation–RNAseq (RIP-Seq) identified transcripts bound to ZFP804A. Consistently, ZFP804A associates with many short transcripts involved in translational and mitochondrial regulation. Moreover, among the transcripts associated with ZFP804A, a SZ risk gene, neurogranin (NRGN), is one of ZFP804A targets. Interestingly, downregulation of ZFP804A decreases NRGN expression and overexpression of NRGN can ameliorate ZFP804A-mediated migration defect. To verify the downstream targets of ZNF804A, a Duolink in situ interaction assay confirmed genes from our RIP-Seq data as the ZNF804A targets. Thus, our work uncovered a novel mechanistic link of a SZ risk gene to neurodevelopment and translational control. The interactome-driven approach here is an effective way for translating genome-wide association findings into novel biological insights of human diseases. PMID:28924186

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

PubMed

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

2017-03-01

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

Characterization of the Human NEK7 Interactome Suggests Catalytic and Regulatory Properties Distinct from Those of NEK6

PubMed Central

2015-01-01

Human NEK7 is a regulator of cell division and plays an important role in growth and survival of mammalian cells. Human NEK6 and NEK7 are closely related, consisting of a conserved C-terminal catalytic domain and a nonconserved and disordered N-terminal regulatory domain, crucial to mediate the interactions with their respective proteins. Here, in order to better understand NEK7 cellular functions, we characterize the NEK7 interactome by two screening approaches: one using a yeast two-hybrid system and the other based on immunoprecipitation followed by mass spectrometry analysis. These approaches led to the identification of 61 NEK7 interactors that contribute to a variety of biological processes, including cell division. Combining additional interaction and phosphorylation assays from yeast two-hybrid screens, we validated CC2D1A, TUBB2B, MNAT1, and NEK9 proteins as potential NEK7 interactors and substrates. Notably, endogenous RGS2, TUBB, MNAT1, NEK9, and PLEKHA8 localized with NEK7 at key sites throughout the cell cycle, especially during mitosis and cytokinesis. Furthermore, we obtained evidence that the closely related kinases NEK6 and NEK7 do not share common interactors, with the exception of NEK9, and display different modes of protein interaction, depending on their N- and C-terminal regions, in distinct fashions. In summary, our work shows for the first time a comprehensive NEK7 interactome that, combined with functional in vitro and in vivo assays, suggests that NEK7 is a multifunctional kinase acting in different cellular processes in concert with cell division signaling and independently of NEK6. PMID:25093993

Altered Protein Interactions of the Endogenous Interactome of PTPIP51 towards MAPK Signaling

PubMed Central

Brobeil, Alexander; Chehab, Rajaa; Dietel, Eric; Gattenlöhner, Stefan; Wimmer, Monika

2017-01-01

Protein–protein interactions play a pivotal role in normal cellular functions as well as in carcinogenesis. The protein–protein interactions form functional clusters during signal transduction. To elucidate the fine calibration of the protein–protein interactions of protein tyrosine phosphatase interacting protein 51 (PTPIP51) a small molecule drug, namely LDC-3, directly targeting PTPIP51 is now available. Therefore, LDC-3 allows for the studying of the regulation of the endogenous interactome by modulating PTPIP51 binding capacity. Small interfering ribonucleic acid (siRNA) experiments show that the modification in PTPIP51 binding capacity is induced by LDC-3. Application of LDC-3 annuls the known regulatory phosphorylation mechanisms for PTPIP51 and consequently, significantly alters the assembly of the PTPIP51 associated protein complexes. The treatment of human keratinocytes (HaCaT cells) with LDC-3 induces an altered protein–protein interaction profile of the endogenous interactome of PTPIP51. In addition, LDC-3 stabilizes PTPIP51 within a mitogen activated protein kinase (MAPK) complex composed of Raf-1 and the scaffold protein 14-3-3, independent of the phosphorylation status of PTPIP51. Of note, under LDC-3 treatment the regulatory function of the PTP1B on PTPIP51 fails to impact the PTPIP51 interaction characteristics, as reported for the HaCaT cell line. In summary, LDC-3 gives the unique opportunity to directly modulate PTPIP51 in malignant cells, thus targeting potential dysregulated signal transduction pathways such as the MAPK cascade. The provided data give critical insights in the therapeutic potential of PTPIP51 protein interactions and thus are basic for possible targeted therapy regimens. PMID:28754031

Development of Online Database Services in Japan and Perspectives on Asia.

ERIC Educational Resources Information Center

Miyakawa, Takayasu

This paper outlines the market developments, governmental promotion policies, and efforts by private industries for online database services in Japan since the late 1970s. The combination of these efforts over the years has resulted in an online database service market of US$20 billion annually, of which approximately one third is Western online…

Network-based study reveals potential infection pathways of hepatitis-C leading to various diseases.

PubMed

Mukhopadhyay, Anirban; Maulik, Ujjwal

2014-01-01

Protein-protein interaction network-based study of viral pathogenesis has been gaining popularity among computational biologists in recent days. In the present study we attempt to investigate the possible pathways of hepatitis-C virus (HCV) infection by integrating the HCV-human interaction network, human protein interactome and human genetic disease association network. We have proposed quasi-biclique and quasi-clique mining algorithms to integrate these three networks to identify infection gateway host proteins and possible pathways of HCV pathogenesis leading to various diseases. Integrated study of three networks, namely HCV-human interaction network, human protein interaction network, and human proteins-disease association network reveals potential pathways of infection by the HCV that lead to various diseases including cancers. The gateway proteins have been found to be biologically coherent and have high degrees in human interactome compared to the other virus-targeted proteins. The analyses done in this study provide possible targets for more effective anti-hepatitis-C therapeutic involvement.

Network-Based Study Reveals Potential Infection Pathways of Hepatitis-C Leading to Various Diseases

PubMed Central

Mukhopadhyay, Anirban; Maulik, Ujjwal

2014-01-01

Protein-protein interaction network-based study of viral pathogenesis has been gaining popularity among computational biologists in recent days. In the present study we attempt to investigate the possible pathways of hepatitis-C virus (HCV) infection by integrating the HCV-human interaction network, human protein interactome and human genetic disease association network. We have proposed quasi-biclique and quasi-clique mining algorithms to integrate these three networks to identify infection gateway host proteins and possible pathways of HCV pathogenesis leading to various diseases. Integrated study of three networks, namely HCV-human interaction network, human protein interaction network, and human proteins-disease association network reveals potential pathways of infection by the HCV that lead to various diseases including cancers. The gateway proteins have been found to be biologically coherent and have high degrees in human interactome compared to the other virus-targeted proteins. The analyses done in this study provide possible targets for more effective anti-hepatitis-C therapeutic involvement. PMID:24743187

Characterization of clinical signs in the human interactome.

PubMed

Chagoyen, Monica; Pazos, Florencio

2016-06-15

Many diseases are related by shared associated molecules and pathways, exhibiting comorbidities and common phenotypes, an indication of the continuous nature of the human pathological landscape. Although it is continuous, this landscape is always partitioned into discrete diseases when studied at the molecular level. Clinical signs are also important phenotypic descriptors that can reveal the molecular mechanisms that underlie pathological states, but have seldom been the subject of systemic research. Here, we quantify the modular nature of the clinical signs associated with genetic diseases in the human interactome. We found that clinical signs are reflected as modules at the molecular network level, to at least to the same extent as diseases. They can thus serve as a valid complementary partition of the human pathological landscape, with implications for etiology research, diagnosis and treatment. monica.chagoyen@cnb.csic.es Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

The RNA-binding protein repertoire of embryonic stem cells.

PubMed

Kwon, S Chul; Yi, Hyerim; Eichelbaum, Katrin; Föhr, Sophia; Fischer, Bernd; You, Kwon Tae; Castello, Alfredo; Krijgsveld, Jeroen; Hentze, Matthias W; Kim, V Narry

2013-09-01

RNA-binding proteins (RBPs) have essential roles in RNA-mediated gene regulation, and yet annotation of RBPs is limited mainly to those with known RNA-binding domains. To systematically identify the RBPs of embryonic stem cells (ESCs), we here employ interactome capture, which combines UV cross-linking of RBP to RNA in living cells, oligo(dT) capture and MS. From mouse ESCs (mESCs), we have defined 555 proteins constituting the mESC mRNA interactome, including 283 proteins not previously annotated as RBPs. Of these, 68 new RBP candidates are highly expressed in ESCs compared to differentiated cells, implicating a role in stem-cell physiology. Two well-known E3 ubiquitin ligases, Trim25 (also called Efp) and Trim71 (also called Lin41), are validated as RBPs, revealing a potential link between RNA biology and protein-modification pathways. Our study confirms and expands the atlas of RBPs, providing a useful resource for the study of the RNA-RBP network in stem cells.

SONAR Discovers RNA-Binding Proteins from Analysis of Large-Scale Protein-Protein Interactomes.

PubMed

Brannan, Kristopher W; Jin, Wenhao; Huelga, Stephanie C; Banks, Charles A S; Gilmore, Joshua M; Florens, Laurence; Washburn, Michael P; Van Nostrand, Eric L; Pratt, Gabriel A; Schwinn, Marie K; Daniels, Danette L; Yeo, Gene W

2016-10-20

RNA metabolism is controlled by an expanding, yet incomplete, catalog of RNA-binding proteins (RBPs), many of which lack characterized RNA binding domains. Approaches to expand the RBP repertoire to discover non-canonical RBPs are currently needed. Here, HaloTag fusion pull down of 12 nuclear and cytoplasmic RBPs followed by quantitative mass spectrometry (MS) demonstrates that proteins interacting with multiple RBPs in an RNA-dependent manner are enriched for RBPs. This motivated SONAR, a computational approach that predicts RNA binding activity by analyzing large-scale affinity precipitation-MS protein-protein interactomes. Without relying on sequence or structure information, SONAR identifies 1,923 human, 489 fly, and 745 yeast RBPs, including over 100 human candidate RBPs that contain zinc finger domains. Enhanced CLIP confirms RNA binding activity and identifies transcriptome-wide RNA binding sites for SONAR-predicted RBPs, revealing unexpected RNA binding activity for disease-relevant proteins and DNA binding proteins. Copyright © 2016 Elsevier Inc. All rights reserved.

Lineage-Specific Genome Architecture Links Enhancers and Non-coding Disease Variants to Target Gene Promoters.

PubMed

Javierre, Biola M; Burren, Oliver S; Wilder, Steven P; Kreuzhuber, Roman; Hill, Steven M; Sewitz, Sven; Cairns, Jonathan; Wingett, Steven W; Várnai, Csilla; Thiecke, Michiel J; Burden, Frances; Farrow, Samantha; Cutler, Antony J; Rehnström, Karola; Downes, Kate; Grassi, Luigi; Kostadima, Myrto; Freire-Pritchett, Paula; Wang, Fan; Stunnenberg, Hendrik G; Todd, John A; Zerbino, Daniel R; Stegle, Oliver; Ouwehand, Willem H; Frontini, Mattia; Wallace, Chris; Spivakov, Mikhail; Fraser, Peter

2016-11-17

Long-range interactions between regulatory elements and gene promoters play key roles in transcriptional regulation. The vast majority of interactions are uncharted, constituting a major missing link in understanding genome control. Here, we use promoter capture Hi-C to identify interacting regions of 31,253 promoters in 17 human primary hematopoietic cell types. We show that promoter interactions are highly cell type specific and enriched for links between active promoters and epigenetically marked enhancers. Promoter interactomes reflect lineage relationships of the hematopoietic tree, consistent with dynamic remodeling of nuclear architecture during differentiation. Interacting regions are enriched in genetic variants linked with altered expression of genes they contact, highlighting their functional role. We exploit this rich resource to connect non-coding disease variants to putative target promoters, prioritizing thousands of disease-candidate genes and implicating disease pathways. Our results demonstrate the power of primary cell promoter interactomes to reveal insights into genomic regulatory mechanisms underlying common diseases. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shatsky, Maxim; Allen, Simon; Gold, Barbara

Numerous affinity purification – mass-spectrometry (AP-MS) and yeast two hybrid (Y2H) screens have each defined thousands of pairwise protein-protein interactions (PPIs), most between functionally unrelated proteins. The accuracy of these networks, however, is under debate. Here we present an AP-MS survey of the bacterium Desulfovibrio vulgaris together with a critical reanalysis of nine published bacterial Y2H and AP-MS screens. We have identified 459 high confidence PPIs from D. vulgaris and 391 from Escherichia coli. Compared to the nine published interactomes, our two networks are smaller; are much less highly connected; have significantly lower false discovery rates; and are much moremore » enriched in protein pairs that are encoded in the same operon, have similar functions, and are reproducibly detected in other physical interaction assays. Lastly, our work establishes more stringent benchmarks for the properties of protein interactomes and suggests that bona fide PPIs much more frequently involve protein partners that are annotated with similar functions or that can be validated in independent assays than earlier studies suggested.« less

Deconstruction of the beaten Path-Sidestep interaction network provides insights into neuromuscular system development

PubMed Central

Li, Hanqing; Watson, Ash; Olechwier, Agnieszka; Anaya, Michael; Sorooshyari, Siamak K; Harnett, Dermott P; Lee, Hyung-Kook (Peter); Vielmetter, Jost; Fares, Mario A; Garcia, K Christopher; Özkan, Engin

2017-01-01

An ‘interactome’ screen of all Drosophila cell-surface and secreted proteins containing immunoglobulin superfamily (IgSF) domains discovered a network formed by paralogs of Beaten Path (Beat) and Sidestep (Side), a ligand-receptor pair that is central to motor axon guidance. Here we describe a new method for interactome screening, the Bio-Plex Interactome Assay (BPIA), which allows identification of many interactions in a single sample. Using the BPIA, we ‘deorphanized’ four more members of the Beat-Side network. We confirmed interactions using surface plasmon resonance. The expression patterns of beat and side genes suggest that Beats are neuronal receptors for Sides expressed on peripheral tissues. side-VI is expressed in muscle fibers targeted by the ISNb nerve, as well as at growth cone choice points and synaptic targets for the ISN and TN nerves. beat-V genes, encoding Side-VI receptors, are expressed in ISNb and ISN motor neurons. PMID:28829740

The cardiac TBX5 interactome reveals a chromatin remodeling network essential for cardiac septation

PubMed Central

Waldron, Lauren; Steimle, Jeffrey D.; Greco, Todd M.; Gomez, Nicholas C.; Dorr, Kerry M.; Kweon, Junghun; Temple, Brenda; Yang, Xinan Holly; Wilczewski, Caralynn M.; Davis, Ian J.; Cristea, Ileana M.; Moskowitz, Ivan P.; Conlon, Frank L.

2016-01-01

SUMMARY Human mutations in the cardiac transcription factor gene TBX5 cause Congenital Heart Disease (CHD), however the underlying mechanism is unknown. We report characterization of the endogenous TBX5 cardiac interactome and demonstrate that TBX5, long considered a transcriptional activator, interacts biochemically and genetically with the Nucleosome Remodeling and Deacetylase (NuRD) repressor complex. Incompatible gene programs are repressed by TBX5 in the developing heart. CHD missense mutations that disrupt the TBX5-NuRD interaction cause depression of a subset of repressed genes. Furthermore, the TBX5-NuRD interaction is required for heart development. Phylogenetic analysis showed that the TBX5-NuRD interaction domain evolved during early diversification of vertebrates, simultaneous with the evolution of cardiac septation. Collectively, this work defines a TBX5-NuRD interaction essential to cardiac development and the evolution of the mammalian heart, and when altered may contribute to human CHD. PMID:26859351

Protein-mRNA interactome capture: cartography of the mRNP landscape

PubMed Central

Ryder, Sean P.

2016-01-01

RNA-binding proteins play a variety of roles in cellular physiology. Some regulate mRNA processing, mRNA abundance, and translation efficiency. Some fight off invader RNA through small RNA-driven silencing pathways. Others sense foreign sequences in the form of double-stranded RNA and activate the innate immune response. Yet others, for example cytoplasmic aconitase, act as bi-functional proteins, processing metabolites in one conformation and regulating metabolic gene expression in another. Not all are involved in gene regulation. Some play structural roles, for example, connecting the translational machinery to the endoplasmic reticulum outer membrane. Despite their pervasive role and relative importance, it has remained difficult to identify new RNA-binding proteins in a systematic, unbiased way. A recent body of literature from several independent labs has defined robust, easily adaptable protocols for mRNA interactome discovery. In this review, I summarize the methods and review some of the intriguing findings from their application to a wide variety of biological systems. PMID:29098073

Proteomic Analysis of the Mediator Complex Interactome in Saccharomyces cerevisiae.

PubMed

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

2017-02-27

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

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

PubMed

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

2017-05-25

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

Global changes of the RNA-bound proteome during the maternal-to-zygotic transition in Drosophila

PubMed Central

Sysoev, Vasiliy O.; Fischer, Bernd; Frese, Christian K.; Gupta, Ishaan; Krijgsveld, Jeroen; Hentze, Matthias W.; Castello, Alfredo; Ephrussi, Anne

2016-01-01

The maternal-to-zygotic transition (MZT) is a process that occurs in animal embryos at the earliest developmental stages, during which maternally deposited mRNAs and other molecules are degraded and replaced by products of the zygotic genome. The zygotic genome is not activated immediately upon fertilization, and in the pre-MZT embryo post-transcriptional control by RNA-binding proteins (RBPs) orchestrates the first steps of development. To identify relevant Drosophila RBPs organism-wide, we refined the RNA interactome capture method for comparative analysis of the pre- and post-MZT embryos. We determine 523 proteins as high-confidence RBPs, half of which were not previously reported to bind RNA. Comparison of the RNA interactomes of pre- and post-MZT embryos reveals high dynamicity of the RNA-bound proteome during early development, and suggests active regulation of RNA binding of some RBPs. This resource provides unprecedented insight into the system of RBPs that govern the earliest steps of Drosophila development. PMID:27378189

Reef Ecosystem Services and Decision Support Database

EPA Science Inventory

This scientific and management information database utilizes systems thinking to describe the linkages between decisions, human activities, and provisioning of reef ecosystem goods and services. This database provides: (1) Hierarchy of related topics - Click on topics to navigat...

DIMA.Tools: An R package for working with the database for inventory, monitoring, and assessment

USDA-ARS?s Scientific Manuscript database

The Database for Inventory, Monitoring, and Assessment (DIMA) is a Microsoft Access database used to collect, store and summarize monitoring data. This database is used by both local and national monitoring efforts within the National Park Service, the Forest Service, the Bureau of Land Management, ...

Graph Databases for Large-Scale Healthcare Systems: A Framework for Efficient Data Management and Data Services

DOE Office of Scientific and Technical Information (OSTI.GOV)

Park, Yubin; Shankar, Mallikarjun; Park, Byung H.

Designing a database system for both efficient data management and data services has been one of the enduring challenges in the healthcare domain. In many healthcare systems, data services and data management are often viewed as two orthogonal tasks; data services refer to retrieval and analytic queries such as search, joins, statistical data extraction, and simple data mining algorithms, while data management refers to building error-tolerant and non-redundant database systems. The gap between service and management has resulted in rigid database systems and schemas that do not support effective analytics. We compose a rich graph structure from an abstracted healthcaremore » RDBMS to illustrate how we can fill this gap in practice. We show how a healthcare graph can be automatically constructed from a normalized relational database using the proposed 3NF Equivalent Graph (3EG) transformation.We discuss a set of real world graph queries such as finding self-referrals, shared providers, and collaborative filtering, and evaluate their performance over a relational database and its 3EG-transformed graph. Experimental results show that the graph representation serves as multiple de-normalized tables, thus reducing complexity in a database and enhancing data accessibility of users. Based on this finding, we propose an ensemble framework of databases for healthcare applications.« less

Characterization of the Saccharomyces cerevisiae ATP-Interactome using the iTRAQ-SPROX Technique

NASA Astrophysics Data System (ADS)

Geer, M. Ariel; Fitzgerald, Michael C.

2016-02-01

The stability of proteins from rates of oxidation (SPROX) technique was used in combination with an isobaric mass tagging strategy to identify adenosine triphosphate (ATP) interacting proteins in the Saccharomyces cerevisiae proteome. The SPROX methodology utilized in this work enabled 373 proteins in a yeast cell lysate to be assayed for ATP interactions (both direct and indirect) using the non-hydrolyzable ATP analog, adenylyl imidodiphosphate (AMP-PNP). A total of 28 proteins were identified with AMP-PNP-induced thermodynamic stability changes. These protein hits included 14 proteins that were previously annotated as ATP-binding proteins in the Saccharomyces Genome Database (SGD). The 14 non-annotated ATP-binding proteins included nine proteins that were previously found to be ATP-sensitive in an earlier SPROX study using a stable isotope labeling with amino acids in cell culture (SILAC)-based approach. A bioinformatics analysis of the protein hits identified here and in the earlier SILAC-SPROX experiments revealed that many of the previously annotated ATP-binding protein hits were kinases, ligases, and chaperones. In contrast, many of the newly discovered ATP-sensitive proteins were not from these protein classes, but rather were hydrolases, oxidoreductases, and nucleic acid-binding proteins.

Net Venn - An integrated network analysis web platform for gene lists

USDA-ARS?s Scientific Manuscript database

Many lists containing biological identifiers such as gene lists have been generated in various genomics projects. Identifying the overlap among gene lists can enable us to understand the similarities and differences between the datasets. Here, we present an interactome network-based web application...

Analysis of the STAT3 interactome using in-situ biotinylation and SILAC.

PubMed

Blumert, Conny; Kalkhof, Stefan; Brocke-Heidrich, Katja; Kohajda, Tibor; von Bergen, Martin; Horn, Friedemann

2013-12-06

Signal transducer and activator of transcription 3 (STAT3) is activated by a variety of cytokines and growth factors. To generate a comprehensive data set of proteins interacting specifically with STAT3, we applied stable isotope labeling with amino acids in cell culture (SILAC). For high-affinity pull-down using streptavidin, we fused STAT3 with a short peptide tag allowing biotinylation in situ (bio-tag), which did not affect STAT3 functions. By this approach, 3642 coprecipitated proteins were detected in human embryonic kidney-293 cells. Filtering using statistical and functional criteria finally extracted 136 proteins as putative interaction partners of STAT3. Both, a physical interaction network analysis and the enrichment of known and predicted interaction partners suggested that our filtering criteria successfully enriched true STAT3 interactors. Our approach identified numerous novel interactors, including ones previously predicted to associate with STAT3. By reciprocal coprecipitation, we were able to verify the physical association between STAT3 and selected interactors, including the novel interaction with TOX4, a member of the TOX high mobility group box family. Applying the same method, we next investigated the activation-dependency of the STAT3 interactome. Again, we identified both known and novel interactions. Thus, our approach allows to study protein-protein interaction effectively and comprehensively. The location, activity, function, degradation, and synthesis of proteins are significantly regulated by interactions of proteins with other proteins, biopolymers and small molecules. Thus, the comprehensive characterization of interactions of proteins in a given proteome is the next milestone on the path to understanding the biochemistry of the cell. In order to generate a comprehensive interactome dataset of proteins specifically interacting with a selected bait protein, we fused our bait protein STAT3 with a short peptide tag allowing biotinylation in situ (bio-tag). This bio-tag allows an affinity pull-down using streptavidin but affected neither the activation of STAT3 by tyrosine phosphorylation nor its transactivating potential. We combined SILAC for accurate relative protein quantification, subcellular fractionation to increase the coverage of interacting proteins, high-affinity pull-down and a stringent filtering method to successfully analyze the interactome of STAT3. With our approach we confirmed several already known and identified numerous novel STAT3 interactors. The approach applied provides a rapid and effective method, which is broadly applicable for studying protein-protein interactions and their dependency on post-translational modifications. © 2013. Published by Elsevier B.V. All rights reserved.

SEER Linked Databases - SEER Datasets

Cancer.gov

SEER-Medicare database of elderly persons with cancer is useful for epidemiologic and health services research. SEER-MHOS has health-related quality of life information about elderly persons with cancer. SEER-CAHPS database has clinical, survey, and health services information on people with cancer.

Clever generation of rich SPARQL queries from annotated relational schema: application to Semantic Web Service creation for biological databases.

PubMed

Wollbrett, Julien; Larmande, Pierre; de Lamotte, Frédéric; Ruiz, Manuel

2013-04-15

In recent years, a large amount of "-omics" data have been produced. However, these data are stored in many different species-specific databases that are managed by different institutes and laboratories. Biologists often need to find and assemble data from disparate sources to perform certain analyses. Searching for these data and assembling them is a time-consuming task. The Semantic Web helps to facilitate interoperability across databases. A common approach involves the development of wrapper systems that map a relational database schema onto existing domain ontologies. However, few attempts have been made to automate the creation of such wrappers. We developed a framework, named BioSemantic, for the creation of Semantic Web Services that are applicable to relational biological databases. This framework makes use of both Semantic Web and Web Services technologies and can be divided into two main parts: (i) the generation and semi-automatic annotation of an RDF view; and (ii) the automatic generation of SPARQL queries and their integration into Semantic Web Services backbones. We have used our framework to integrate genomic data from different plant databases. BioSemantic is a framework that was designed to speed integration of relational databases. We present how it can be used to speed the development of Semantic Web Services for existing relational biological databases. Currently, it creates and annotates RDF views that enable the automatic generation of SPARQL queries. Web Services are also created and deployed automatically, and the semantic annotations of our Web Services are added automatically using SAWSDL attributes. BioSemantic is downloadable at http://southgreen.cirad.fr/?q=content/Biosemantic.

Clever generation of rich SPARQL queries from annotated relational schema: application to Semantic Web Service creation for biological databases

PubMed Central

2013-01-01

Background In recent years, a large amount of “-omics” data have been produced. However, these data are stored in many different species-specific databases that are managed by different institutes and laboratories. Biologists often need to find and assemble data from disparate sources to perform certain analyses. Searching for these data and assembling them is a time-consuming task. The Semantic Web helps to facilitate interoperability across databases. A common approach involves the development of wrapper systems that map a relational database schema onto existing domain ontologies. However, few attempts have been made to automate the creation of such wrappers. Results We developed a framework, named BioSemantic, for the creation of Semantic Web Services that are applicable to relational biological databases. This framework makes use of both Semantic Web and Web Services technologies and can be divided into two main parts: (i) the generation and semi-automatic annotation of an RDF view; and (ii) the automatic generation of SPARQL queries and their integration into Semantic Web Services backbones. We have used our framework to integrate genomic data from different plant databases. Conclusions BioSemantic is a framework that was designed to speed integration of relational databases. We present how it can be used to speed the development of Semantic Web Services for existing relational biological databases. Currently, it creates and annotates RDF views that enable the automatic generation of SPARQL queries. Web Services are also created and deployed automatically, and the semantic annotations of our Web Services are added automatically using SAWSDL attributes. BioSemantic is downloadable at http://southgreen.cirad.fr/?q=content/Biosemantic. PMID:23586394

Emory University: "LC-MS analysis of PRAS40 protein-protein interactions" | Office of Cancer Genomics

Cancer.gov

This study focuses on subcellular localization and interactome of nuclear PRAS40 in HeLa cells.  Read the abstract.  Experimental Approaches Read the detailed Experimental Approaches. If you cannot access the manuscript, or if you have additional questions, please email Andrei Ivanov.

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

USDA-ARS?s Scientific Manuscript database

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

An "on-matrix" digestion procedure for AP-MS experiments dissects the interplay between complex-conserved and serotype-specific reactivities in Dengue virus-human plasma interactome.

PubMed

Ramos, Yassel; Huerta, Vivian; Martín, Dayron; Palomares, Sucel; Yero, Alexis; Pupo, Dianne; Gallien, Sebastien; Martín, Alejandro M; Pérez-Riverol, Yasset; Sarría, Mónica; Guirola, Osmany; Chinea, Glay; Domon, Bruno; González, Luis Javier

2017-07-13

The interactions between the four Dengue virus (DENV) serotypes and plasma proteins are crucial in the initial steps of viral infection to humans. Affinity purification combined with quantitative mass spectrometry analysis, has become one of the most powerful tools for the investigation on novel protein-protein interactions. Using this approach, we report here that a significant number of bait-interacting proteins do not dissociate under standard elution conditions, i.e. acid pH and chaotropic agents, and that this problem can be circumvented by using the "on-matrix" digestion procedure described here. This procedure enabled the identification of 16 human plasma proteins interacting with domain III from the envelope protein of DENV serotypes 1, 3 and 4 that would have not been detected otherwise and increased the known DIIIE interactors in human plasma to 59 proteins. Selected Reaction Monitoring analysis evidenced DENV interactome in human plasma is rather conserved although significant differences on the reactivity of viral serotypes with specific proteins do exist. A comparison between the serotype-dependent profile of reactivity and the conservation pattern of amino acid residues suggests an evolutionary selection of highly conserved interactions with the host and other interactions mediated for surface regions of higher variability. False negative results on the identification of interacting proteins in pull-down experiments compromise the subsequent interpretation of results and the formulation of a working hypothesis for the derived future work. In this study we demonstrate the presence of bait-interacting proteins reluctant to dissociate under elution conditions of acid pH and presence of chaotropics. We propose the direct proteolytic digestion of proteins while still bound to the affinity matrix ("on-matrix" digestion) and evaluate the impact of this methodology in the comparative study of the interactome of the four serotypes of Dengue virus mediated by the domain III of the viral envelope glycoprotein. Fifty nine proteins were identified as putative interaction partners of Dengue virus (IPs) either due to direct binding or by co-isolation with interacting proteins. Collectively the IPs identified from the pull-down with the recombinant domain III proteins representing the four viral serotypes, 29% were identified only after "on-matrix" digestion which demonstrate the usefulness of this method of recovering bait-bound proteins. Results highlight a particular importance of "on-matrix" digestion procedure for comparative studies where a stronger interaction with one of the interest baits could prevent a bound protein to elute under standard conditions thus leading to misinterpretation as absent in the interactome of this particular bait. The analysis of the Interaction Network indicates that Dengue virus interactome mediated by the domain III of the envelope protein is rather conserved in the viral complex suggesting a key role of these interactions for viral infection thus making candidates to explore for potential biomarkers of clinical outcome in DENV-caused disease. Interestingly, some particular IPs exhibit significant differences in the strength of the interaction with the viral serotypes representing interactions that involve more variable regions in the surface of the domain III. Since such variable regions are the consequence of the interaction with antibodies generated by human immune response; this result relates the interaction with proteins from human plasma with the interplay of the virus and the human immune system. Copyright © 2017 Elsevier B.V. All rights reserved.

Redefining Information Access to Serials Information.

ERIC Educational Resources Information Center

Chen, Ching-chih

1992-01-01

Describes full-text document delivery services that have been introduced in conjunction with available databases in response to economic and technological changes affecting libraries: (1) CARL System's UnCover database and UnCover2 service; (2) Research Libraries Group's CitaDel delivery service; and (3) Faxon Research Service's Faxon Finder and…

Applications of Technology to CAS Data-Base Production.

ERIC Educational Resources Information Center

Weisgerber, David W.

1984-01-01

Reviews the economic importance of applying computer technology to Chemical Abstracts Service database production from 1973 to 1983. Database building, technological applications for editorial processing (online editing, Author Index Manufacturing System), and benefits (increased staff productivity, reduced rate of increase of cost of services,…

ePlant: Visualizing and Exploring Multiple Levels of Data for Hypothesis Generation in Plant Biology[OPEN

PubMed Central

Waese, Jamie; Fan, Jim; Yu, Hans; Fucile, Geoffrey; Shi, Ruian; Cumming, Matthew; Town, Chris; Stuerzlinger, Wolfgang

2017-01-01

A big challenge in current systems biology research arises when different types of data must be accessed from separate sources and visualized using separate tools. The high cognitive load required to navigate such a workflow is detrimental to hypothesis generation. Accordingly, there is a need for a robust research platform that incorporates all data and provides integrated search, analysis, and visualization features through a single portal. Here, we present ePlant (http://bar.utoronto.ca/eplant), a visual analytic tool for exploring multiple levels of Arabidopsis thaliana data through a zoomable user interface. ePlant connects to several publicly available web services to download genome, proteome, interactome, transcriptome, and 3D molecular structure data for one or more genes or gene products of interest. Data are displayed with a set of visualization tools that are presented using a conceptual hierarchy from big to small, and many of the tools combine information from more than one data type. We describe the development of ePlant in this article and present several examples illustrating its integrative features for hypothesis generation. We also describe the process of deploying ePlant as an “app” on Araport. Building on readily available web services, the code for ePlant is freely available for any other biological species research. PMID:28808136

Emory University: "LC-MS analysis of PRAS40 protein-protein interactions" | Office of Cancer Genomics

Cancer.gov

This study focuses on subcellular localization and interactome of nuclear PRAS40 in HeLa cells.  Read the abstract.  Experimental Approaches Read the detailed Experimental Approaches. If you cannot access the manuscript, or if you have additional questions, please email Andrei Ivanov. Data

Use of The Yeast Two-Hybrid System to Identify Targets of Fungal Effectors

USDA-ARS?s Scientific Manuscript database

The yeast-two hybrid (Y2H) system is a binary method widely used to determine direct interactions between paired proteins. Although having certain limitations, this method has become one of the two main systemic tools (along with affinity purification/mass spectrometry) for interactome mapping in mo...

The interactomic analysis reveals pathogenic protein networks in Phomopsis longicolla underlying seed decay of soybean

USDA-ARS?s Scientific Manuscript database

Phomopsis longicolla T. W. Hobbs (syn. Diaporthe longicolla) is the primary cause of Phomopsis seed decay (PSD) in soybean, Glycine max (L.) Merrill. This disease causes poor seed quality and is one of the most economically important diseases in soybean. The objectives of this study were to perform ...

On an algorithmic definition for the components of the minimal cell.

PubMed

Martínez, Octavio; Reyes-Valdés, M Humberto

2018-01-01

Living cells are highly complex systems comprising a multitude of elements that are engaged in the many convoluted processes observed during the cell cycle. However, not all elements and processes are essential for cell survival and reproduction under steady-state environmental conditions. To distinguish between essential from expendable cell components and thus define the 'minimal cell' and the corresponding 'minimal genome', we postulate that the synthesis of all cell elements can be represented as a finite set of binary operators, and within this framework we show that cell elements that depend on their previous existence to be synthesized are those that are essential for cell survival. An algorithm to distinguish essential cell elements is presented and demonstrated within an interactome. Data and functions implementing the algorithm are given as supporting information. We expect that this algorithmic approach will lead to the determination of the complete interactome of the minimal cell, which could then be experimentally validated. The assumptions behind this hypothesis as well as its consequences for experimental and theoretical biology are discussed.

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

PubMed

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

2018-01-18

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

Distinctive Behaviors of Druggable Proteins in Cellular Networks

PubMed Central

Workman, Paul; Al-Lazikani, Bissan

2015-01-01

The interaction environment of a protein in a cellular network is important in defining the role that the protein plays in the system as a whole, and thus its potential suitability as a drug target. Despite the importance of the network environment, it is neglected during target selection for drug discovery. Here, we present the first systematic, comprehensive computational analysis of topological, community and graphical network parameters of the human interactome and identify discriminatory network patterns that strongly distinguish drug targets from the interactome as a whole. Importantly, we identify striking differences in the network behavior of targets of cancer drugs versus targets from other therapeutic areas and explore how they may relate to successful drug combinations to overcome acquired resistance to cancer drugs. We develop, computationally validate and provide the first public domain predictive algorithm for identifying druggable neighborhoods based on network parameters. We also make available full predictions for 13,345 proteins to aid target selection for drug discovery. All target predictions are available through canSAR.icr.ac.uk. Underlying data and tools are available at https://cansar.icr.ac.uk/cansar/publications/druggable_network_neighbourhoods/. PMID:26699810

Factors affecting interactome-based prediction of human genes associated with clinical signs.

PubMed

González-Pérez, Sara; Pazos, Florencio; Chagoyen, Mónica

2017-07-17

Clinical signs are a fundamental aspect of human pathologies. While disease diagnosis is problematic or impossible in many cases, signs are easier to perceive and categorize. Clinical signs are increasingly used, together with molecular networks, to prioritize detected variants in clinical genomics pipelines, even if the patient is still undiagnosed. Here we analyze the ability of these network-based methods to predict genes that underlie clinical signs from the human interactome. Our analysis reveals that these approaches can locate genes associated with clinical signs with variable performance that depends on the sign and associated disease. We analyzed several clinical and biological factors that explain these variable results, including number of genes involved (mono- vs. oligogenic diseases), mode of inheritance, type of clinical sign and gene product function. Our results indicate that the characteristics of the clinical signs and their related diseases should be considered for interpreting the results of network-prediction methods, such as those aimed at discovering disease-related genes and variants. These results are important due the increasing use of clinical signs as an alternative to diseases for studying the molecular basis of human pathologies.

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dmitriev, Ruslan I.; Korneenko, Tatyana V.; Department of Physiology, Pharmacology, Metabolism, and Cardiovascular Sciences, University of Toledo College of Medicine, Toledo, OH 43614

2007-04-20

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

The nuclear DEK interactome supports multi-functionality.

PubMed

Smith, Eric A; Krumpelbeck, Eric F; Jegga, Anil G; Prell, Malte; Matrka, Marie M; Kappes, Ferdinand; Greis, Kenneth D; Ali, Abdullah M; Meetei, Amom R; Wells, Susanne I

2018-01-01

DEK is an oncoprotein that is overexpressed in many forms of cancer and participates in numerous cellular pathways. Of these different pathways, relevant interacting partners and functions of DEK are well described in regard to the regulation of chromatin structure, epigenetic marks, and transcription. Most of this understanding was derived by investigating DNA-binding and chromatin processing capabilities of the oncoprotein. To facilitate the generation of mechanism-driven hypotheses regarding DEK activities in underexplored areas, we have developed the first DEK interactome model using tandem-affinity purification and mass spectrometry. With this approach, we identify IMPDH2, DDX21, and RPL7a as novel DEK binding partners, hinting at new roles for the oncogene in de novo nucleotide biosynthesis and ribosome formation. Additionally, a hydroxyurea-specific interaction with replication protein A (RPA) was observed, suggesting that a DEK-RPA complex may form in response to DNA replication fork stalling. Taken together, these findings highlight diverse activities for DEK across cellular pathways and support a model wherein this molecule performs a plethora of functions. © 2017 Wiley Periodicals, Inc.

Interactome Analysis of Microtubule-targeting Agents Reveals Cytotoxicity Bases in Normal Cells.

PubMed

Gutiérrez-Escobar, Andrés Julián; Méndez-Callejas, Gina

2017-12-01

Cancer causes millions of deaths annually and microtubule-targeting agents (MTAs) are the most commonly-used anti-cancer drugs. However, the high toxicity of MTAs on normal cells raises great concern. Due to the non-selectivity of MTA targets, we analyzed the interaction network in a non-cancerous human cell. Subnetworks of fourteen MTAs were reconstructed and the merged network was compared against a randomized network to evaluate the functional richness. We found that 71.4% of the MTA interactome nodes are shared, which affects cellular processes such as apoptosis, cell differentiation, cell cycle control, stress response, and regulation of energy metabolism. Additionally, possible secondary targets were identified as client proteins of interphase microtubules. MTAs affect apoptosis signaling pathways by interacting with client proteins of interphase microtubules, suggesting that their primary targets are non-tumor cells. The paclitaxel and doxorubicin networks share essential topological axes, suggesting synergistic effects. This may explain the exacerbated toxicity observed when paclitaxel and doxorubicin are used in combination for cancer treatment. Copyright © 2017 The Authors. Production and hosting by Elsevier B.V. All rights reserved.

Evidence for dynamically organized modularity in the yeast protein-protein interaction network

NASA Astrophysics Data System (ADS)

Han, Jing-Dong J.; Bertin, Nicolas; Hao, Tong; Goldberg, Debra S.; Berriz, Gabriel F.; Zhang, Lan V.; Dupuy, Denis; Walhout, Albertha J. M.; Cusick, Michael E.; Roth, Frederick P.; Vidal, Marc

2004-07-01

In apparently scale-free protein-protein interaction networks, or `interactome' networks, most proteins interact with few partners, whereas a small but significant proportion of proteins, the `hubs', interact with many partners. Both biological and non-biological scale-free networks are particularly resistant to random node removal but are extremely sensitive to the targeted removal of hubs. A link between the potential scale-free topology of interactome networks and genetic robustness seems to exist, because knockouts of yeast genes encoding hubs are approximately threefold more likely to confer lethality than those of non-hubs. Here we investigate how hubs might contribute to robustness and other cellular properties for protein-protein interactions dynamically regulated both in time and in space. We uncovered two types of hub: `party' hubs, which interact with most of their partners simultaneously, and `date' hubs, which bind their different partners at different times or locations. Both in silico studies of network connectivity and genetic interactions described in vivo support a model of organized modularity in which date hubs organize the proteome, connecting biological processes-or modules -to each other, whereas party hubs function inside modules.

A Synthetic Coiled-Coil Interactome Provides Heterospecific Modules for Molecular Engineering

DOE Office of Scientific and Technical Information (OSTI.GOV)

Reinke, Aaron W.; Grant, Robert A.; Keating, Amy E.

2010-06-21

The versatile coiled-coil protein motif is widely used to induce and control macromolecular interactions in biology and materials science. Yet the types of interaction patterns that can be constructed using known coiled coils are limited. Here we greatly expand the coiled-coil toolkit by measuring the complete pairwise interactions of 48 synthetic coiled coils and 7 human bZIP coiled coils using peptide microarrays. The resulting 55-member protein 'interactome' includes 27 pairs of interacting peptides that preferentially heteroassociate. The 27 pairs can be used in combinations to assemble sets of 3 to 6 proteins that compose networks of varying topologies. Of specialmore » interest are heterospecific peptide pairs that participate in mutually orthogonal interactions. Such pairs provide the opportunity to dimerize two separate molecular systems without undesired crosstalk. Solution and structural characterization of two such sets of orthogonal heterodimers provide details of their interaction geometries. The orthogonal pair, along with the many other network motifs discovered in our screen, provide new capabilities for synthetic biology and other applications.« less

HTS-Net: An integrated regulome-interactome approach for establishing network regulation models in high-throughput screenings

PubMed Central

Rioualen, Claire; Da Costa, Quentin; Chetrit, Bernard; Charafe-Jauffret, Emmanuelle; Ginestier, Christophe

2017-01-01

High-throughput RNAi screenings (HTS) allow quantifying the impact of the deletion of each gene in any particular function, from virus-host interactions to cell differentiation. However, there has been less development for functional analysis tools dedicated to RNAi analyses. HTS-Net, a network-based analysis program, was developed to identify gene regulatory modules impacted in high-throughput screenings, by integrating transcription factors-target genes interaction data (regulome) and protein-protein interaction networks (interactome) on top of screening z-scores. HTS-Net produces exhaustive HTML reports for results navigation and exploration. HTS-Net is a new pipeline for RNA interference screening analyses that proves better performance than simple gene rankings by z-scores, by re-prioritizing genes and replacing them in their biological context, as shown by the three studies that we reanalyzed. Formatted input data for the three studied datasets, source code and web site for testing the system are available from the companion web site at http://htsnet.marseille.inserm.fr/. We also compared our program with existing algorithms (CARD and hotnet2). PMID:28949986

Proteomic Analysis of the Mediator Complex Interactome in Saccharomyces cerevisiae

PubMed Central

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

2017-01-01

Here we present the most comprehensive analysis of the yeast Mediator complex interactome to date. Particularly gentle cell lysis and co-immunopurification conditions allowed us to preserve even transient protein-protein interactions and to comprehensively probe the molecular environment of the Mediator complex in the cell. Metabolic 15N-labeling thereby enabled stringent discrimination between bona fide interaction partners and nonspecifically captured proteins. Our data indicates a functional role for Mediator beyond transcription initiation. We identified a large number of Mediator-interacting proteins and protein complexes, such as RNA polymerase II, general transcription factors, a large number of transcriptional activators, the SAGA complex, chromatin remodeling complexes, histone chaperones, highly acetylated histones, as well as proteins playing a role in co-transcriptional processes, such as splicing, mRNA decapping and mRNA decay. Moreover, our data provides clear evidence, that the Mediator complex interacts not only with RNA polymerase II, but also with RNA polymerases I and III, and indicates a functional role of the Mediator complex in rRNA processing and ribosome biogenesis. PMID:28240253

Polyubiquitin-Photoactivatable Crosslinking Reagents for Mapping Ubiquitin Interactome Identify Rpn1 as a Proteasome Ubiquitin-Associating Subunit.

PubMed

Chojnacki, Michal; Mansour, Wissam; Hameed, Dharjath S; Singh, Rajesh K; El Oualid, Farid; Rosenzweig, Rina; Nakasone, Mark A; Yu, Zanlin; Glaser, Fabian; Kay, Lewis E; Fushman, David; Ovaa, Huib; Glickman, Michael H

2017-04-20

Ubiquitin (Ub) signaling is a diverse group of processes controlled by covalent attachment of small protein Ub and polyUb chains to a range of cellular protein targets. The best documented Ub signaling pathway is the one that delivers polyUb proteins to the 26S proteasome for degradation. However, studies of molecular interactions involved in this process have been hampered by the transient and hydrophobic nature of these interactions and the lack of tools to study them. Here, we develop Ub-phototrap (Ub PT ), a synthetic Ub variant containing a photoactivatable crosslinking side chain. Enzymatic polymerization into chains of defined lengths and linkage types provided a set of reagents that led to identification of Rpn1 as a third proteasome ubiquitin-associating subunit that coordinates docking of substrate shuttles, unloading of substrates, and anchoring of polyUb conjugates. Our work demonstrates the value of Ub PT , and we expect that its future uses will help define and investigate the ubiquitin interactome. Copyright © 2017 Elsevier Ltd. All rights reserved.

The DBCLS BioHackathon: standardization and interoperability for bioinformatics web services and workflows. The DBCLS BioHackathon Consortium*.

PubMed

Katayama, Toshiaki; Arakawa, Kazuharu; Nakao, Mitsuteru; Ono, Keiichiro; Aoki-Kinoshita, Kiyoko F; Yamamoto, Yasunori; Yamaguchi, Atsuko; Kawashima, Shuichi; Chun, Hong-Woo; Aerts, Jan; Aranda, Bruno; Barboza, Lord Hendrix; Bonnal, Raoul Jp; Bruskiewich, Richard; Bryne, Jan C; Fernández, José M; Funahashi, Akira; Gordon, Paul Mk; Goto, Naohisa; Groscurth, Andreas; Gutteridge, Alex; Holland, Richard; Kano, Yoshinobu; Kawas, Edward A; Kerhornou, Arnaud; Kibukawa, Eri; Kinjo, Akira R; Kuhn, Michael; Lapp, Hilmar; Lehvaslaiho, Heikki; Nakamura, Hiroyuki; Nakamura, Yasukazu; Nishizawa, Tatsuya; Nobata, Chikashi; Noguchi, Tamotsu; Oinn, Thomas M; Okamoto, Shinobu; Owen, Stuart; Pafilis, Evangelos; Pocock, Matthew; Prins, Pjotr; Ranzinger, René; Reisinger, Florian; Salwinski, Lukasz; Schreiber, Mark; Senger, Martin; Shigemoto, Yasumasa; Standley, Daron M; Sugawara, Hideaki; Tashiro, Toshiyuki; Trelles, Oswaldo; Vos, Rutger A; Wilkinson, Mark D; York, William; Zmasek, Christian M; Asai, Kiyoshi; Takagi, Toshihisa

2010-08-21

Web services have become a key technology for bioinformatics, since life science databases are globally decentralized and the exponential increase in the amount of available data demands for efficient systems without the need to transfer entire databases for every step of an analysis. However, various incompatibilities among database resources and analysis services make it difficult to connect and integrate these into interoperable workflows. To resolve this situation, we invited domain specialists from web service providers, client software developers, Open Bio* projects, the BioMoby project and researchers of emerging areas where a standard exchange data format is not well established, for an intensive collaboration entitled the BioHackathon 2008. The meeting was hosted by the Database Center for Life Science (DBCLS) and Computational Biology Research Center (CBRC) and was held in Tokyo from February 11th to 15th, 2008. In this report we highlight the work accomplished and the common issues arisen from this event, including the standardization of data exchange formats and services in the emerging fields of glycoinformatics, biological interaction networks, text mining, and phyloinformatics. In addition, common shared object development based on BioSQL, as well as technical challenges in large data management, asynchronous services, and security are discussed. Consequently, we improved interoperability of web services in several fields, however, further cooperation among major database centers and continued collaborative efforts between service providers and software developers are still necessary for an effective advance in bioinformatics web service technologies.

The DBCLS BioHackathon: standardization and interoperability for bioinformatics web services and workflows. The DBCLS BioHackathon Consortium*

PubMed Central

2010-01-01

Web services have become a key technology for bioinformatics, since life science databases are globally decentralized and the exponential increase in the amount of available data demands for efficient systems without the need to transfer entire databases for every step of an analysis. However, various incompatibilities among database resources and analysis services make it difficult to connect and integrate these into interoperable workflows. To resolve this situation, we invited domain specialists from web service providers, client software developers, Open Bio* projects, the BioMoby project and researchers of emerging areas where a standard exchange data format is not well established, for an intensive collaboration entitled the BioHackathon 2008. The meeting was hosted by the Database Center for Life Science (DBCLS) and Computational Biology Research Center (CBRC) and was held in Tokyo from February 11th to 15th, 2008. In this report we highlight the work accomplished and the common issues arisen from this event, including the standardization of data exchange formats and services in the emerging fields of glycoinformatics, biological interaction networks, text mining, and phyloinformatics. In addition, common shared object development based on BioSQL, as well as technical challenges in large data management, asynchronous services, and security are discussed. Consequently, we improved interoperability of web services in several fields, however, further cooperation among major database centers and continued collaborative efforts between service providers and software developers are still necessary for an effective advance in bioinformatics web service technologies. PMID:20727200

Publishing Your Database on CD-ROM for Profit: The FISHLIT and NISC Experience.

ERIC Educational Resources Information Center

Crampton, Margaret

1995-01-01

Details the development of the FISHLIT bibliographic database at the JLB Smith Institute of Ichthyology Library at Rhodes University (South Africa), and the subsequent CD-ROM publication of the database by NISC (National Information Services Corporation). Discusses the advantages of CD-ROM publication, costs and information service provision,…

Choosing a Database for Social Work: A Comparison of Social Work Abstracts and Social Service Abstracts

ERIC Educational Resources Information Center

Flatley, Robert K.; Lilla, Rick; Widner, Jack

2007-01-01

This study compared Social Work Abstracts and Social Services Abstracts databases in terms of indexing, journal coverage, and searches. The authors interviewed editors, analyzed journal coverage, and compared searches. It was determined that the databases complement one another more than compete. The authors conclude with some considerations.

Enabling On-Demand Database Computing with MIT SuperCloud Database Management System

DTIC Science & Technology

2015-09-15

arc.liv.ac.uk/trac/SGE) provides these services and is independent of programming language (C, Fortran, Java , Matlab, etc) or parallel programming...a MySQL database to store DNS records. The DNS records are controlled via a simple web service interface that allows records to be created

Chapter 51: How to Build a Simple Cone Search Service Using a Local Database

NASA Astrophysics Data System (ADS)

Kent, B. R.; Greene, G. R.

The cone search service protocol will be examined from the server side in this chapter. A simple cone search service will be setup and configured locally using MySQL. Data will be read into a table, and the Java JDBC will be used to connect to the database. Readers will understand the VO cone search specification and how to use it to query a database on their local systems and return an XML/VOTable file based on an input of RA/DEC coordinates and a search radius. The cone search in this example will be deployed as a Java servlet. The resulting cone search can be tested with a verification service. This basic setup can be used with other languages and relational databases.

75 FR 41140 - Agency Information Collection Activities: Proposed Collection; Comment Request-Child Nutrition...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-07-15

... DEPARTMENT OF AGRICULTURE Food and Nutrition Service Agency Information Collection Activities: Proposed Collection; Comment Request--Child Nutrition Database AGENCY: Food and Nutrition Service, USDA... nutrient data from the food service industry to update and expand the Child Nutrition Database in support...

Identification of host cellular proteins that interact with the M protein of a highly pathogenic porcine reproductive and respiratory syndrome virus vaccine strain.

PubMed

Wang, Qian; Li, Yanwei; Dong, Hong; Wang, Li; Peng, Jinmei; An, Tongqing; Yang, Xufu; Tian, Zhijun; Cai, Xuehui

2017-02-22

The highly pathogenic porcine reproductive and respiratory syndrome virus (HP-PRRSV) continues to pose one of the greatest threats to the swine industry. M protein is the most conserved and important structural protein of PRRSV. However, information about the host cellular proteins that interact with M protein remains limited. Host cellular proteins that interact with the M protein of HP-PRRSV were immunoprecipitated from MARC-145 cells infected with PRRSV HuN4-F112 using the M monoclonal antibody (mAb). The differentially expressed proteins were identified by LC-MS/MS. The screened proteins were used for bioinformatics analysis including Gene Ontology, the interaction network, and the enriched KEGG pathways. Some interested cellular proteins were validated to interact with M protein by CO-IP. The PRRSV HuN4-F112 infection group had 10 bands compared with the control group. The bands included 219 non-redundant cellular proteins that interact with M protein, which were identified by LC-MS/MS with high confidence. The gene ontology and Kyoto encyclopedia of genes and genomes (KEGG) pathway bioinformatic analyses indicated that the identified proteins could be assigned to several different subcellular locations and functional classes. Functional analysis of the interactome profile highlighted cellular pathways associated with protein translation, infectious disease, and signal transduction. Two interested cellular proteins-nuclear factor of activated T cells 45 kDa (NF45) and proliferating cell nuclear antigen (PCNA)-that could interact with M protein were validated by Co-IP and confocal analyses. The interactome data between PRRSV M protein and cellular proteins were identified and contribute to the understanding of the roles of M protein in the replication and pathogenesis of PRRSV. The interactome of M protein will aid studies of virus/host interactions and provide means to decrease the threat of PRRSV to the swine industry in the future.

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

PubMed Central

Coelho Filho, Mauricio Antônio; Morillon, Raphaël; Bonatto, Diego; da Silva Gesteira, Abelmon

2017-01-01

Scion/rootstock interaction is important for plant development and for breeding programs. In this context, polyploid rootstocks presented several advantages, mainly in relation to biotic and abiotic stresses. Here we analyzed the response to drought of two different scion/rootstock combinations presenting different polyploidy: the diploid (2x) and autotetraploid (4x) Rangpur lime (Citrus limonia, Osbeck) rootstocks grafted with 2x Valencia Delta sweet orange (Citrus sinensis) scions, named V/2xRL and V/4xRL, respectively. Based on previous gene expression data, we developed an interactomic approach to identify proteins involved in V/2xRL and V/4xRL response to drought. A main interactomic network containing 3,830 nodes and 97,652 edges was built from V/2xRL and V/4xRL data. Exclusive proteins of the V/2xRL and V/4xRL networks (2,056 and 1,001, respectively), as well as common to both networks (773) were identified. Functional clusters were obtained and two models of drought stress response for the V/2xRL and V/4xRL genotypes were designed. Even if the V/2xRL plant implement some tolerance mechanisms, the global plant response to drought was rapid and quickly exhaustive resulting in a general tendency to dehydration avoidance, which presented some advantage in short and strong drought stress conditions, but which, in long terms, does not allow the plant survival. At the contrary, the V/4xRL plants presented a response which strong impacts on development but that present some advantages in case of prolonged drought. Finally, some specific proteins, which presented high centrality on interactomic analysis were identified as good candidates for subsequent functional analysis of citrus genes related to drought response, as well as be good markers of one or another physiological mechanism implemented by the plants. PMID:28545114

Notch3 Interactome Analysis Identified WWP2 as a Negative Regulator of Notch3 Signaling in Ovarian Cancer

PubMed Central

Guan, Bin; Wu, Ren-Chin; Zhu, Heng; Blackshaw, Seth; Shih, Ie-Ming; Wang, Tian-Li

2014-01-01

The Notch3 signaling pathway is thought to play a critical role in cancer development, as evidenced by the Notch3 amplification and rearrangement observed in human cancers. However, the molecular mechanism by which Notch3 signaling contributes to tumorigenesis is largely unknown. In an effort to identify the molecular modulators of the Notch3 signaling pathway, we screened for Notch3-intracellular domain (N3-ICD) interacting proteins using a human proteome microarray. Pathway analysis of the Notch3 interactome demonstrated that ubiquitin C was the molecular hub of the top functional network, suggesting the involvement of ubiquitination in modulating Notch3 signaling. Thereby, we focused on functional characterization of an E3 ubiquitin-protein ligase, WWP2, a top candidate in the Notch3 interactome list. Co-immunoprecipitation experiments showed that WWP2 interacted with N3-ICD but not with intracellular domains from other Notch receptors. Wild-type WWP2 but not ligase-deficient mutant WWP2 increases mono-ubiquitination of the membrane-tethered Notch3 fragment, therefore attenuating Notch3 pathway activity in cancer cells and leading to cell cycle arrest. The mono-ubiquitination by WWP2 may target an endosomal/lysosomal degradation fate for Notch3 as suggested by the fact that the process could be suppressed by the endosomal/lysosomal inhibitor. Analysis of The Cancer Genome Atlas dataset showed that the majority of ovarian carcinomas harbored homozygous or heterozygous deletions in WWP2 locus, and there was an inverse correlation in the expression levels between WWP2 and Notch3 in ovarian carcinomas. Furthermore, ectopic expression of WWP2 decreased tumor development in a mouse xenograft model and suppressed the Notch3-induced phenotypes including increase in cancer stem cell-like cell population and platinum resistance. Taken together, our results provide evidence that WWP2 serves as a tumor suppressor by negatively regulating Notch3 signaling in ovarian cancer. PMID:25356737

Hub Protein Controversy: Taking a Closer Look at Plant Stress Response Hubs

PubMed Central

Vandereyken, Katy; Van Leene, Jelle; De Coninck, Barbara; Cammue, Bruno P. A.

2018-01-01

Plant stress responses involve numerous changes at the molecular and cellular level and are regulated by highly complex signaling pathways. Studying protein-protein interactions (PPIs) and the resulting networks is therefore becoming increasingly important in understanding these responses. Crucial in PPI networks are the so-called hubs or hub proteins, commonly defined as the most highly connected central proteins in scale-free PPI networks. However, despite their importance, a growing amount of confusion and controversy seems to exist regarding hub protein identification, characterization and classification. In order to highlight these inconsistencies and stimulate further clarification, this review critically analyses the current knowledge on hub proteins in the plant interactome field. We focus on current hub protein definitions, including the properties generally seen as hub-defining, and the challenges and approaches associated with hub protein identification. Furthermore, we give an overview of the most important large-scale plant PPI studies of the last decade that identified hub proteins, pointing out the lack of overlap between different studies. As such, it appears that although major advances are being made in the plant interactome field, defining hub proteins is still heavily dependent on the quality, origin and interpretation of the acquired PPI data. Nevertheless, many hub proteins seem to have a reported role in the plant stress response, including transcription factors, protein kinases and phosphatases, ubiquitin proteasome system related proteins, (co-)chaperones and redox signaling proteins. A significant number of identified plant stress hubs are however still functionally uncharacterized, making them interesting targets for future research. This review clearly shows the ongoing improvements in the plant interactome field but also calls attention to the need for a more comprehensive and precise identification of hub proteins, allowing a more efficient systems biology driven unraveling of complex processes, including those involved in stress responses. PMID:29922309

NNDC Stand: Activities and Services of the National Nuclear Data Center

NASA Astrophysics Data System (ADS)

Pritychenko, B.; Arcilla, R.; Burrows, T. W.; Dunford, C. L.; Herman, M. W.; McLane, V.; Obložinský, P.; Sonzogni, A. A.; Tuli, J. K.; Winchell, D. F.

2005-05-01

The National Nuclear Data Center (NNDC) collects, evaluates, and disseminates nuclear physics data for basic nuclear research, applied nuclear technologies including energy, shielding, medical and homeland security. In 2004, to answer the needs of nuclear data users community, NNDC completed a project to modernize data storage and management of its databases and began offering new nuclear data Web services. The principles of database and Web application development as well as related nuclear reaction and structure database services are briefly described.

Database Deposit Service through JOIS : JAFIC File on Food Industry and Osaka Urban Engineering File

NASA Astrophysics Data System (ADS)

Kataoka, Akihiro

JICST has launched the database deposit service for the excellent quality in small-and medium size, both of which have no dissemination network. JAFIC File on Food Industry produced by the Japan Food Industry Center and Osaka Urban Engineering File by Osaka City have been in service by JOIS since March 2, 1987. In this paper the outline of the above databases is introduced in focussing on the items covered and retrieved by JOIS.

Experience in running relational databases on clustered storage

NASA Astrophysics Data System (ADS)

Gaspar Aparicio, Ruben; Potocky, Miroslav

2015-12-01

For past eight years, CERN IT Database group has based its backend storage on NAS (Network-Attached Storage) architecture, providing database access via NFS (Network File System) protocol. In last two and half years, our storage has evolved from a scale-up architecture to a scale-out one. This paper describes our setup and a set of functionalities providing key features to other services like Database on Demand [1] or CERN Oracle backup and recovery service. It also outlines possible trend of evolution that, storage for databases could follow.

Providing Database Services in a Nationwide Research Organisation--Coexistence of Traditional Information Services and a Modern CD-ROM/Online Hybrid Solution.

ERIC Educational Resources Information Center

Bowman, Benjamin F.

For the past two decades the central Information Retrieval Services of the Max Planck Society has been providing database searches for scientists in Max Planck Institutes and Research Groups throughout Germany. As a supplement to traditional search services offered by professional intermediaries, they have recently fostered the introduction of a…

Ocean Drilling Program: Information Services: Database Services

Science.gov Websites

Available Examples of Data Core Photos Logging Database (LDEO-BRG) RIDGE Petrological Database (LDEO from postcruise research All ODP and DSDP core photos All ODP data are available online through Janus proprietary for a period of one year after the end of a cruise and are available only to the participating

Ocean Drilling Program: Mirror Sites

Science.gov Websites

Publication services and products Drilling services and tools Online Janus database Search the ODP/TAMU web information, see www.iodp-usio.org. ODP | Search | Database | Drilling | Publications | Science | Cruise Info

Lessons Learned With a Global Graph and Ozone Widget Framework (OWF) Testbed

DTIC Science & Technology

2013-05-01

of operating system and database environments. The following is one example. Requirements are: Java 1.6 + and a Relational Database Management...We originally tried to use MySQL as our database, because we were more familiar with it, but since the database dumps as well as most of the...Global Graph Rest Services In order to set up the Global Graph Rest Services, you will need to have the following dependencies installed: Java 1.6

Discovery and targeted LC-MS/MS of purified polerovirus reveals differences in the virus-host interactome associated with altered aphid transmission

USDA-ARS?s Scientific Manuscript database

The transmission of viruses in the Luteoviridae, such as Cereal yellow dwarf virus (CYDV), requires a series of precisely orchestrated interactions between virus proteins, plant proteins, and aphid proteins. These viruses are retained in the phloem for aphid acquisition and are transmitted by aphids...

Escherichia coli O157:H7 and rectoanal junction cell interactome

USDA-ARS?s Scientific Manuscript database

Introduction. Cattle are the primary E. coli O157 (O157) reservoir and principal source of human infection. The anatomical site of O157 persistence is the bovine recto-anal (RAJ) junction; hence, an in-depth understanding of O157-RAJ interactions will help develop novel modalities to limit O157 in c...

A Web-Based Tool to Support Data-Based Early Intervention Decision Making

ERIC Educational Resources Information Center

Buzhardt, Jay; Greenwood, Charles; Walker, Dale; Carta, Judith; Terry, Barbara; Garrett, Matthew

2010-01-01

Progress monitoring and data-based intervention decision making have become key components of providing evidence-based early childhood special education services. Unfortunately, there is a lack of tools to support early childhood service providers' decision-making efforts. The authors describe a Web-based system that guides service providers…

76 FR 5503 - Airworthiness Directives; The Boeing Company Model 777-200 Series Airplanes

Federal Register 2010, 2011, 2012, 2013, 2014

2011-02-01

... software, as applicable; and making a change to the cabin services system (CSS) configuration database and... software, as applicable; and make a change to the cabin services system (CSS) configuration database and... 5 p.m., Monday through Friday, except Federal holidays. For service information identified in this...

The NOAO Data Lab PHAT Photometry Database

NASA Astrophysics Data System (ADS)

Olsen, Knut; Williams, Ben; Fitzpatrick, Michael; PHAT Team

2018-01-01

We present a database containing both the combined photometric object catalog and the single epoch measurements from the Panchromatic Hubble Andromeda Treasury (PHAT). This database is hosted by the NOAO Data Lab (http://datalab.noao.edu), and as such exposes a number of data services to the PHAT photometry, including access through a Table Access Protocol (TAP) service, direct PostgreSQL queries, web-based and programmatic query interfaces, remote storage space for personal database tables and files, and a JupyterHub-based Notebook analysis environment, as well as image access through a Simple Image Access (SIA) service. We show how the Data Lab database and Jupyter Notebook environment allow for straightforward and efficient analyses of PHAT catalog data, including maps of object density, depth, and color, extraction of light curves of variable objects, and proper motion exploration.

An Update on Electronic Information Sources.

ERIC Educational Resources Information Center

Ackerman, Katherine

1987-01-01

This review of new developments and products in online services discusses trends in travel related services; full text databases; statistical source databases; an emphasis on regional and international business news; and user friendly systems. (Author/CLB)

Repositioning of drugs using open-access data portal DTome: A test case with probenecid (Review).

PubMed

Ahmed, Mohammad U; Bennett, Dylan J; Hsieh, Tze-Chen; Doonan, Barbara B; Ahmed, Saba; Wu, Joseph M

2016-01-01

The one gene-one enzyme hypothesis, first introduced by Beadle and Tatum in the 1940s and based on their genetic analysis and observation of phenotype changes in Neurospora crassa challenged by various experimental conditions, has witnessed significant advances in recent decades. Much of our understanding of the association between genes and their phenotype expression has benefited from the completion of the human genome project, and has shown continual transformation guided by the effort directed at the annotation and characterization of human genes. Similarly, the idea of one drug‑one primary disease indication that traditionally has been the benchmark for the labeling and usage of drugs has also undergone evident progressive refinements; in recent years the science and practice of pharmaceutical development has notable success in the strategy of drug repurposing. Drug repurposing is an innovative approach where, instead of de novo synthesis and discovery of new drugs with novel indications, drug candidates with the desired usage are identified by a process of re‑profiling using an open‑source database or knowledge of known or failed drugs already in existence. In the present study, the repurposing drug strategy employing open‑access data portal drug‑target interactome (DTome) is applied to the uncovering of new clinical usage for probenecid.

The Novice User and CD-ROM Database Services. ERIC Digest.

ERIC Educational Resources Information Center

Schamber, Linda

This digest answers the following questions that beginning or novice users may have about CD-ROM (a compact disk with read-only memory) database services: (1) What is CD-ROM? (2) What databases are available? (3) Is CD-ROM difficult to use? (4) How much does CD-ROM cost? and (5) What is the future of CD-ROM? (15 references) (MES)

JICST Factual Database(1)

NASA Astrophysics Data System (ADS)

Kurosawa, Shinji

The outline of JICST factual database (JOIS-F), which JICST has started from January, 1988, and its online service are described in this paper. First, the author mentions the circumstances from 1973, when its planning was started, to the present, and its relation to "Project by Special Coordination Founds for Promoting Science and Technology". Secondly, databases, which are now under development aiming to start its services from fiscal 1988 or fiscal 1989, of DNA, metallic material intensity, crystal structure, chemical substance regulations, and so forth, are described. Lastly, its online service is briefly explained.

Who's Gonna Pay the Piper for Free Online Databases?

ERIC Educational Resources Information Center

Jacso, Peter

1996-01-01

Discusses new pricing models for some online services and considers the possibilities for the traditional online database market. Topics include multimedia music databases, including copyright implications; other retail-oriented databases; and paying for free databases with advertising. (LRW)

A Review of Healthcare Service and Education Provision of Autism Spectrum Condition in Mainland China

ERIC Educational Resources Information Center

Sun, Xiang; Allison, Carrie; Auyeung, Bonnie; Baron-Cohen, Simon; Brayne, Carol

2013-01-01

Little is known about the current situation regarding Autism Spectrum Conditions in mainland China. Electronic databases and bibliographies were searched to identify literature on service provision for ASC in both English and Chinese databases. 14 studies and 6 reports were reviewed. The findings of identified papers on service provision were…

Virtual Queue in a Centralized Database Environment

NASA Astrophysics Data System (ADS)

Kar, Amitava; Pal, Dibyendu Kumar

2010-10-01

Today is the era of the Internet. Every matter whether it be a gather of knowledge or planning a holiday or booking of ticket etc everything can be obtained from the internet. This paper intends to calculate the different queuing measures when some booking or purchase is done through the internet subject to the limitations in the number of tickets or seats. It involves a lot of database activities like read and write. This paper takes care of the time involved in the requests of a service, taken as arrival and the time involved in providing the required information, taken as service and thereby tries to calculate the distribution of arrival and service and the various measures of the queuing. This paper considers the database as centralized database for the sake of simplicity as the alternating concept of distributed database would rather complicate the calculation.

Long-term effects of lactocrine-deficiency on the global porcine endometrial transcriptome and the microRNA-mRNA interactome at pregnancy day 13

USDA-ARS?s Scientific Manuscript database

Through lactocrine mechanisms, bioactive factors are transferred from mother to offspring as a specific consequence of nursing to support development. A large, long-term study in pigs showed that minimal colostrum consumption on the day of birth [postnatal day (PND) 0], reflected by low serum immuno...

Plant peptides in defense and signaling.

PubMed

Marmiroli, Nelson; Maestri, Elena

2014-06-01

This review focuses on plant peptides involved in defense against pathogen infection and those involved in the regulation of growth and development. Defense peptides, defensins, cyclotides and anti-microbial peptides are compared and contrasted. Signaling peptides are classified according to their major sites of activity. Finally, a network approach to creating an interactomic peptide map is described. Copyright © 2014 Elsevier Inc. All rights reserved.

Lysine methylation modulates the protein-protein interactions of yeast cytochrome C Cyc1p.

PubMed

Winter, Daniel L; Abeygunawardena, Dhanushi; Hart-Smith, Gene; Erce, Melissa A; Wilkins, Marc R

2015-07-01

In recent years, protein methylation has been established as a major intracellular PTM. It has also been proposed to modulate protein-protein interactions (PPIs) in the interactome. To investigate the effect of PTMs on PPIs, we recently developed the conditional two-hybrid (C2H) system. With this, we demonstrated that arginine methylation can modulate PPIs in the yeast interactome. Here, we used the C2H system to investigate the effect of lysine methylation. Specifically, we asked whether Ctm1p-mediated trimethylation of yeast cytochrome c Cyc1p, on lysine 78, modulates its interactions with Erv1p, Ccp1p, Cyc2p and Cyc3p. We show that the interactions between Cyc1p and Erv1p, and between Cyc1p and Cyc3p, are significantly increased upon trimethylation of lysine 78. This increase of interaction helps explain the reported facilitation of Cyc1p import into the mitochondrial intermembrane space upon methylation. This first application of the C2H system to the study of methyllysine-modulated interactions further confirms its robustness and flexibility. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

The Two-pore channel (TPC) interactome unmasks isoform-specific roles for TPCs in endolysosomal morphology and cell pigmentation

PubMed Central

Lin-Moshier, Yaping; Keebler, Michael V.; Hooper, Robert; Boulware, Michael J.; Liu, Xiaolong; Churamani, Dev; Abood, Mary E.; Walseth, Timothy F.; Brailoiu, Eugen; Patel, Sandip; Marchant, Jonathan S.

2014-01-01

The two-pore channels (TPC1 and TPC2) belong to an ancient family of intracellular ion channels expressed in the endolysosomal system. Little is known about how regulatory inputs converge to modulate TPC activity, and proposed activation mechanisms are controversial. Here, we compiled a proteomic characterization of the human TPC interactome, which revealed that TPCs complex with many proteins involved in Ca2+ homeostasis, trafficking, and membrane organization. Among these interactors, TPCs were resolved to scaffold Rab GTPases and regulate endomembrane dynamics in an isoform-specific manner. TPC2, but not TPC1, caused a proliferation of endolysosomal structures, dysregulating intracellular trafficking, and cellular pigmentation. These outcomes required both TPC2 and Rab activity, as well as their interactivity, because TPC2 mutants that were inactive, or rerouted away from their endogenous expression locale, or deficient in Rab binding, failed to replicate these outcomes. Nicotinic acid adenine dinucleotide phosphate (NAADP)-evoked Ca2+ release was also impaired using either a Rab binding-defective TPC2 mutant or a Rab inhibitor. These data suggest a fundamental role for the ancient TPC complex in trafficking that holds relevance for lysosomal proliferative scenarios observed in disease. PMID:25157141

The Two-pore channel (TPC) interactome unmasks isoform-specific roles for TPCs in endolysosomal morphology and cell pigmentation.

PubMed

Lin-Moshier, Yaping; Keebler, Michael V; Hooper, Robert; Boulware, Michael J; Liu, Xiaolong; Churamani, Dev; Abood, Mary E; Walseth, Timothy F; Brailoiu, Eugen; Patel, Sandip; Marchant, Jonathan S

2014-09-09

The two-pore channels (TPC1 and TPC2) belong to an ancient family of intracellular ion channels expressed in the endolysosomal system. Little is known about how regulatory inputs converge to modulate TPC activity, and proposed activation mechanisms are controversial. Here, we compiled a proteomic characterization of the human TPC interactome, which revealed that TPCs complex with many proteins involved in Ca(2+) homeostasis, trafficking, and membrane organization. Among these interactors, TPCs were resolved to scaffold Rab GTPases and regulate endomembrane dynamics in an isoform-specific manner. TPC2, but not TPC1, caused a proliferation of endolysosomal structures, dysregulating intracellular trafficking, and cellular pigmentation. These outcomes required both TPC2 and Rab activity, as well as their interactivity, because TPC2 mutants that were inactive, or rerouted away from their endogenous expression locale, or deficient in Rab binding, failed to replicate these outcomes. Nicotinic acid adenine dinucleotide phosphate (NAADP)-evoked Ca(2+) release was also impaired using either a Rab binding-defective TPC2 mutant or a Rab inhibitor. These data suggest a fundamental role for the ancient TPC complex in trafficking that holds relevance for lysosomal proliferative scenarios observed in disease.

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

PubMed

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

2017-09-15

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

Do cancer proteins really interact strongly in the human protein-protein interaction network?

PubMed

Xia, Junfeng; Sun, Jingchun; Jia, Peilin; Zhao, Zhongming

2011-06-01

Protein-protein interaction (PPI) network analysis has been widely applied in the investigation of the mechanisms of diseases, especially cancer. Recent studies revealed that cancer proteins tend to interact more strongly than other categories of proteins, even essential proteins, in the human interactome. However, it remains unclear whether this observation was introduced by the bias towards more cancer studies in humans. Here, we examined this important issue by uniquely comparing network characteristics of cancer proteins with three other sets of proteins in four organisms, three of which (fly, worm, and yeast) whose interactomes are essentially not biased towards cancer or other diseases. We confirmed that cancer proteins had stronger connectivity, shorter distance, and larger betweenness centrality than non-cancer disease proteins, essential proteins, and control proteins. Our statistical evaluation indicated that such observations were overall unlikely attributed to random events. Considering the large size and high quality of the PPI data in the four organisms, the conclusion that cancer proteins interact strongly in the PPI networks is reliable and robust. This conclusion suggests that perturbation of cancer proteins might cause major changes of cellular systems and result in abnormal cell function leading to cancer. © 2011 Elsevier Ltd. All rights reserved.

Do cancer proteins really interact strongly in the human protein-protein interaction network?

PubMed Central

Xia, Junfeng; Sun, Jingchun; Jia, Peilin; Zhao, Zhongming

2011-01-01

Protein-protein interaction (PPI) network analysis has been widely applied in the investigation of the mechanisms of diseases, especially cancer. Recent studies revealed that cancer proteins tend to interact more strongly than other categories of proteins, even essential proteins, in the human interactome. However, it remains unclear whether this observation was introduced by the bias towards more cancer studies in humans. Here, we examined this important issue by uniquely comparing network characteristics of cancer proteins with three other sets of proteins in four organisms, three of which (fly, worm, and yeast) whose interactomes are essentially not biased towards cancer or other diseases. We confirmed that cancer proteins had stronger connectivity, shorter distance, and larger betweenness centrality than non-cancer disease proteins, essential proteins, and control proteins. Our statistical evaluation indicated that such observations were overall unlikely attributed to random events. Considering the large size and high quality of the PPI data in the four organisms, the conclusion that cancer proteins interact strongly in the PPI networks is reliable and robust. This conclusion suggests that perturbation of cancer proteins might cause major changes of cellular systems and result in abnormal cell function leading to cancer. PMID:21666777

The amyloid interactome: Exploring protein aggregation

PubMed Central

Mastrokalou, Chara V.; Hamodrakas, Stavros J.

2017-01-01

Protein-protein interactions are the quintessence of physiological activities, but also participate in pathological conditions. Amyloid formation, an abnormal protein-protein interaction process, is a widespread phenomenon in divergent proteins and peptides, resulting in a variety of aggregation disorders. The complexity of the mechanisms underlying amyloid formation/amyloidogenicity is a matter of great scientific interest, since their revelation will provide important insight on principles governing protein misfolding, self-assembly and aggregation. The implication of more than one protein in the progression of different aggregation disorders, together with the cited synergistic occurrence between amyloidogenic proteins, highlights the necessity for a more universal approach, during the study of these proteins. In an attempt to address this pivotal need we constructed and analyzed the human amyloid interactome, a protein-protein interaction network of amyloidogenic proteins and their experimentally verified interactors. This network assembled known interconnections between well-characterized amyloidogenic proteins and proteins related to amyloid fibril formation. The consecutive extended computational analysis revealed significant topological characteristics and unraveled the functional roles of all constituent elements. This study introduces a detailed protein map of amyloidogenicity that will aid immensely towards separate intervention strategies, specifically targeting sub-networks of significant nodes, in an attempt to design possible novel therapeutics for aggregation disorders. PMID:28249044

Towards Inferring Protein Interactions: Challenges and Solutions

NASA Astrophysics Data System (ADS)

Zhang, Ya; Zha, Hongyuan; Chu, Chao-Hsien; Ji, Xiang

2006-12-01

Discovering interacting proteins has been an essential part of functional genomics. However, existing experimental techniques only uncover a small portion of any interactome. Furthermore, these data often have a very high false rate. By conceptualizing the interactions at domain level, we provide a more abstract representation of interactome, which also facilitates the discovery of unobserved protein-protein interactions. Although several domain-based approaches have been proposed to predict protein-protein interactions, they usually assume that domain interactions are independent on each other for the convenience of computational modeling. A new framework to predict protein interactions is proposed in this paper, where no assumption is made about domain interactions. Protein interactions may be the result of multiple domain interactions which are dependent on each other. A conjunctive norm form representation is used to capture the relationships between protein interactions and domain interactions. The problem of interaction inference is then modeled as a constraint satisfiability problem and solved via linear programing. Experimental results on a combined yeast data set have demonstrated the robustness and the accuracy of the proposed algorithm. Moreover, we also map some predicted interacting domains to three-dimensional structures of protein complexes to show the validity of our predictions.

The nuclear F-actin interactome of Xenopus oocytes reveals an actin-bundling kinesin that is essential for meiotic cytokinesis

PubMed Central

Samwer, Matthias; Dehne, Heinz-Jürgen; Spira, Felix; Kollmar, Martin; Gerlich, Daniel W; Urlaub, Henning; Görlich, Dirk

2013-01-01

Nuclei of Xenopus laevis oocytes grow 100 000-fold larger in volume than a typical somatic nucleus and require an unusual intranuclear F-actin scaffold for mechanical stability. We now developed a method for mapping F-actin interactomes and identified a comprehensive set of F-actin binders from the oocyte nuclei. Unexpectedly, the most prominent interactor was a novel kinesin termed NabKin (Nuclear and meiotic actin-bundling Kinesin). NabKin not only binds microtubules but also F-actin structures, such as the intranuclear actin bundles in prophase and the contractile actomyosin ring during cytokinesis. The interaction between NabKin and F-actin is negatively regulated by Importin-β and is responsive to spatial information provided by RanGTP. Disconnecting NabKin from F-actin during meiosis caused cytokinesis failure and egg polyploidy. We also found actin-bundling activity in Nabkin's somatic paralogue KIF14, which was previously shown to be essential for somatic cell division. Our data are consistent with the notion that NabKin/KIF14 directly link microtubules with F-actin and that such link is essential for cytokinesis. PMID:23727888

Transcriptional atlas of cardiogenesis maps congenital heart disease interactome.

PubMed

Li, Xing; Martinez-Fernandez, Almudena; Hartjes, Katherine A; Kocher, Jean-Pierre A; Olson, Timothy M; Terzic, Andre; Nelson, Timothy J

2014-07-01

Mammalian heart development is built on highly conserved molecular mechanisms with polygenetic perturbations resulting in a spectrum of congenital heart diseases (CHD). However, knowledge of cardiogenic ontogeny that regulates proper cardiogenesis remains largely based on candidate-gene approaches. Mapping the dynamic transcriptional landscape of cardiogenesis from a genomic perspective is essential to integrate the knowledge of heart development into translational applications that accelerate disease discovery efforts toward mechanistic-based treatment strategies. Herein, we designed a time-course transcriptome analysis to investigate the genome-wide dynamic expression landscape of innate murine cardiogenesis ranging from embryonic stem cells to adult cardiac structures. This comprehensive analysis generated temporal and spatial expression profiles, revealed stage-specific gene functions, and mapped the dynamic transcriptome of cardiogenesis to curated pathways. Reconciling known genetic underpinnings of CHD, we deconstructed a disease-centric dynamic interactome encoded within this cardiogenic atlas to identify stage-specific developmental disturbances clustered on regulation of epithelial-to-mesenchymal transition (EMT), BMP signaling, NF-AT signaling, TGFb-dependent EMT, and Notch signaling. Collectively, this cardiogenic transcriptional landscape defines the time-dependent expression of cardiac ontogeny and prioritizes regulatory networks at the interface between health and disease. Copyright © 2014 the American Physiological Society.

The Rab-binding Profiles of Bacterial Virulence Factors during Infection*

PubMed Central

So, Ernest C.; Schroeder, Gunnar N.; Carson, Danielle; Mattheis, Corinna; Mousnier, Aurélie; Broncel, Malgorzata; Tate, Edward W.; Frankel, Gad

2016-01-01

Legionella pneumophila, the causative agent of Legionnaire's disease, uses its type IV secretion system to translocate over 300 effector proteins into host cells. These effectors subvert host cell signaling pathways to ensure bacterial proliferation. Despite their importance for pathogenesis, the roles of most of the effectors are yet to be characterized. Key to understanding the function of effectors is the identification of host proteins they bind during infection. We previously developed a novel tandem-affinity purification (TAP) approach using hexahistidine and BirA-specific biotinylation tags for isolating translocated effector complexes from infected cells whose composition were subsequently deciphered by mass spectrometry. Here we further advanced the workflow for the TAP approach and determined the infection-dependent interactomes of the effectors SidM and LidA, which were previously reported to promiscuously bind multiple Rab GTPases in vitro. In this study we defined a stringent subset of Rab GTPases targeted by SidM and LidA during infection, comprising of Rab1A, 1B, 6, and 10; in addition, LidA targets Rab14 and 18. Taken together, this study illustrates the power of this approach to profile the intracellular interactomes of bacterial effectors during infection. PMID:26755725

ePlant: Visualizing and Exploring Multiple Levels of Data for Hypothesis Generation in Plant Biology.

PubMed

Waese, Jamie; Fan, Jim; Pasha, Asher; Yu, Hans; Fucile, Geoffrey; Shi, Ruian; Cumming, Matthew; Kelley, Lawrence A; Sternberg, Michael J; Krishnakumar, Vivek; Ferlanti, Erik; Miller, Jason; Town, Chris; Stuerzlinger, Wolfgang; Provart, Nicholas J

2017-08-01

A big challenge in current systems biology research arises when different types of data must be accessed from separate sources and visualized using separate tools. The high cognitive load required to navigate such a workflow is detrimental to hypothesis generation. Accordingly, there is a need for a robust research platform that incorporates all data and provides integrated search, analysis, and visualization features through a single portal. Here, we present ePlant (http://bar.utoronto.ca/eplant), a visual analytic tool for exploring multiple levels of Arabidopsis thaliana data through a zoomable user interface. ePlant connects to several publicly available web services to download genome, proteome, interactome, transcriptome, and 3D molecular structure data for one or more genes or gene products of interest. Data are displayed with a set of visualization tools that are presented using a conceptual hierarchy from big to small, and many of the tools combine information from more than one data type. We describe the development of ePlant in this article and present several examples illustrating its integrative features for hypothesis generation. We also describe the process of deploying ePlant as an "app" on Araport. Building on readily available web services, the code for ePlant is freely available for any other biological species research. © 2017 American Society of Plant Biologists. All rights reserved.

A Molecular Framework for Understanding DCIS

DTIC Science & Technology

2016-10-01

well. Pathologic and Clinical Annotation Database A clinical annotation database titled the Breast Oncology Database has been established to...complement the procured SPORE sample characteristics and annotated pathology data. This Breast Oncology Database is an offsite clinical annotation...database adheres to CSMC Enterprise Information Services (EIS) research database security standards. The Breast Oncology Database consists of: 9 Baseline

Enabling heterogenous multi-scale database for emergency service functions through geoinformation technologies

NASA Astrophysics Data System (ADS)

Bhanumurthy, V.; Venugopala Rao, K.; Srinivasa Rao, S.; Ram Mohan Rao, K.; Chandra, P. Satya; Vidhyasagar, J.; Diwakar, P. G.; Dadhwal, V. K.

2014-11-01

Geographical Information Science (GIS) is now graduated from traditional desktop system to Internet system. Internet GIS is emerging as one of the most promising technologies for addressing Emergency Management. Web services with different privileges are playing an important role in dissemination of the emergency services to the decision makers. Spatial database is one of the most important components in the successful implementation of Emergency Management. It contains spatial data in the form of raster, vector, linked with non-spatial information. Comprehensive data is required to handle emergency situation in different phases. These database elements comprise core data, hazard specific data, corresponding attribute data, and live data coming from the remote locations. Core data sets are minimum required data including base, thematic, infrastructure layers to handle disasters. Disaster specific information is required to handle a particular disaster situation like flood, cyclone, forest fire, earth quake, land slide, drought. In addition to this Emergency Management require many types of data with spatial and temporal attributes that should be made available to the key players in the right format at right time. The vector database needs to be complemented with required resolution satellite imagery for visualisation and analysis in disaster management. Therefore, the database is interconnected and comprehensive to meet the requirement of an Emergency Management. This kind of integrated, comprehensive and structured database with appropriate information is required to obtain right information at right time for the right people. However, building spatial database for Emergency Management is a challenging task because of the key issues such as availability of data, sharing policies, compatible geospatial standards, data interoperability etc. Therefore, to facilitate using, sharing, and integrating the spatial data, there is a need to define standards to build emergency database systems. These include aspects such as i) data integration procedures namely standard coding scheme, schema, meta data format, spatial format ii) database organisation mechanism covering data management, catalogues, data models iii) database dissemination through a suitable environment, as a standard service for effective service dissemination. National Database for Emergency Management (NDEM) is such a comprehensive database for addressing disasters in India at the national level. This paper explains standards for integrating, organising the multi-scale and multi-source data with effective emergency response using customized user interfaces for NDEM. It presents standard procedure for building comprehensive emergency information systems for enabling emergency specific functions through geospatial technologies.

Enhancing the role of veterinary vaccines reducing zoonotic diseases of humans: Linking systems biology with vaccine development

DOE Office of Scientific and Technical Information (OSTI.GOV)

Adams, Leslie G.; Khare, Sangeeta; Lawhon, Sara D.

The aim of research on infectious diseases is their prevention, and brucellosis and salmonellosis as such are classic examples of worldwide zoonoses for application of a systems biology approach for enhanced rational vaccine development. When used optimally, vaccines prevent disease manifestations, reduce transmission of disease, decrease the need for pharmaceutical intervention, and improve the health and welfare of animals, as well as indirectly protecting against zoonotic diseases of people. Advances in the last decade or so using comprehensive systems biology approaches linking genomics, proteomics, bioinformatics, and biotechnology with immunology, pathogenesis and vaccine formulation and delivery are expected to enable enhancedmore » approaches to vaccine development. The goal of this paper is to evaluate the role of computational systems biology analysis of host:pathogen interactions (the interactome) as a tool for enhanced rational design of vaccines. Systems biology is bringing a new, more robust approach to veterinary vaccine design based upon a deeper understanding of the host pathogen interactions and its impact on the host's molecular network of the immune system. A computational systems biology method was utilized to create interactome models of the host responses to Brucella melitensis (BMEL), Mycobacterium avium paratuberculosis (MAP), Salmonella enterica Typhimurium (STM), and a Salmonella mutant (isogenic *sipA, sopABDE2) and linked to the basis for rational development of vaccines for brucellosis and salmonellosis as reviewed by Adams et al. and Ficht et al. [1,2]. A bovine ligated ileal loop biological model was established to capture the host gene expression response at multiple time points post infection. New methods based on Dynamic Bayesian Network (DBN) machine learning were employed to conduct a comparative pathogenicity analysis of 219 signaling and metabolic pathways and 1620 gene ontology (GO) categories that defined the host's biosignatures to each infectious condition. Through this DBN computational approach, the method identified significantly perturbed pathways and GO category groups of genes that define the pathogenicity signatures of the infectious agent. Our preliminary results provide deeper understanding of the overall complexity of host innate immune response as well as the identification of host gene perturbations that defines a unique host temporal biosignature response to each pathogen. The application of advanced computational methods for developing interactome models based on DBNs has proven to be instrumental in elucidating novel host responses and improved functional biological insight into the host defensive mechanisms. Evaluating the unique differences in pathway and GO perturbations across pathogen conditions allowed the identification of plausible host pathogen interaction mechanisms. Accordingly, a systems biology approach to study molecular pathway gene expression profiles of host cellular responses to microbial pathogens holds great promise as a methodology to identify, model and predict the overall dynamics of the host pathogen interactome. Thus, we propose that such an approach has immediate application to the rational design of brucellosis and salmonellosis vaccines.« less

Enhancing the role of veterinary vaccines reducing zoonotic diseases of humans: linking systems biology with vaccine development.

PubMed

Adams, L Garry; Khare, Sangeeta; Lawhon, Sara D; Rossetti, Carlos A; Lewin, Harris A; Lipton, Mary S; Turse, Joshua E; Wylie, Dennis C; Bai, Yu; Drake, Kenneth L

2011-09-22

The aim of research on infectious diseases is their prevention, and brucellosis and salmonellosis as such are classic examples of worldwide zoonoses for application of a systems biology approach for enhanced rational vaccine development. When used optimally, vaccines prevent disease manifestations, reduce transmission of disease, decrease the need for pharmaceutical intervention, and improve the health and welfare of animals, as well as indirectly protecting against zoonotic diseases of people. Advances in the last decade or so using comprehensive systems biology approaches linking genomics, proteomics, bioinformatics, and biotechnology with immunology, pathogenesis and vaccine formulation and delivery are expected to enable enhanced approaches to vaccine development. The goal of this paper is to evaluate the role of computational systems biology analysis of host:pathogen interactions (the interactome) as a tool for enhanced rational design of vaccines. Systems biology is bringing a new, more robust approach to veterinary vaccine design based upon a deeper understanding of the host-pathogen interactions and its impact on the host's molecular network of the immune system. A computational systems biology method was utilized to create interactome models of the host responses to Brucella melitensis (BMEL), Mycobacterium avium paratuberculosis (MAP), Salmonella enterica Typhimurium (STM), and a Salmonella mutant (isogenic ΔsipA, sopABDE2) and linked to the basis for rational development of vaccines for brucellosis and salmonellosis as reviewed by Adams et al. and Ficht et al. [1,2]. A bovine ligated ileal loop biological model was established to capture the host gene expression response at multiple time points post infection. New methods based on Dynamic Bayesian Network (DBN) machine learning were employed to conduct a comparative pathogenicity analysis of 219 signaling and metabolic pathways and 1620 gene ontology (GO) categories that defined the host's biosignatures to each infectious condition. Through this DBN computational approach, the method identified significantly perturbed pathways and GO category groups of genes that define the pathogenicity signatures of the infectious agent. Our preliminary results provide deeper understanding of the overall complexity of host innate immune response as well as the identification of host gene perturbations that defines a unique host temporal biosignature response to each pathogen. The application of advanced computational methods for developing interactome models based on DBNs has proven to be instrumental in elucidating novel host responses and improved functional biological insight into the host defensive mechanisms. Evaluating the unique differences in pathway and GO perturbations across pathogen conditions allowed the identification of plausible host-pathogen interaction mechanisms. Accordingly, a systems biology approach to study molecular pathway gene expression profiles of host cellular responses to microbial pathogens holds great promise as a methodology to identify, model and predict the overall dynamics of the host-pathogen interactome. Thus, we propose that such an approach has immediate application to the rational design of brucellosis and salmonellosis vaccines. Copyright © 2011 Elsevier Ltd. All rights reserved.

The Help Desk.

ERIC Educational Resources Information Center

Klein, Regina; And Others

1988-01-01

The first of three articles describes the results of a survey that examined characteristics and responsibilities of help-desk personnel at major database and online services. The second provides guidelines to using such customer services, and the third lists help-desk numbers for online databases and systems. (CLB)

A service-oriented data access control model

NASA Astrophysics Data System (ADS)

Meng, Wei; Li, Fengmin; Pan, Juchen; Song, Song; Bian, Jiali

2017-01-01

The development of mobile computing, cloud computing and distributed computing meets the growing individual service needs. Facing with complex application system, it's an urgent problem to ensure real-time, dynamic, and fine-grained data access control. By analyzing common data access control models, on the basis of mandatory access control model, the paper proposes a service-oriented access control model. By regarding system services as subject and data of databases as object, the model defines access levels and access identification of subject and object, and ensures system services securely to access databases.

JICST Factual Database JICST DNA Database

NASA Astrophysics Data System (ADS)

Shirokizawa, Yoshiko; Abe, Atsushi

Japan Information Center of Science and Technology (JICST) has started the on-line service of DNA database in October 1988. This database is composed of EMBL Nucleotide Sequence Library and Genetic Sequence Data Bank. The authors outline the database system, data items and search commands. Examples of retrieval session are presented.

PrimateLit Database

Science.gov Websites

Primate Info Net Related Databases NCRR PrimateLit: A bibliographic database for primatology Top of any problems with this service. We welcome your feedback. The PrimateLit database is no longer being Resources, National Institutes of Health. The database is a collaborative project of the Wisconsin Primate

RESIS-II: An Updated Version of the Original Reservoir Sedimentation Survey Information System (RESIS) Database

USGS Publications Warehouse

Ackerman, Katherine V.; Mixon, David M.; Sundquist, Eric T.; Stallard, Robert F.; Schwarz, Gregory E.; Stewart, David W.

2009-01-01

The Reservoir Sedimentation Survey Information System (RESIS) database, originally compiled by the Soil Conservation Service (now the Natural Resources Conservation Service) in collaboration with the Texas Agricultural Experiment Station, is the most comprehensive compilation of data from reservoir sedimentation surveys throughout the conterminous United States (U.S.). The database is a cumulative historical archive that includes data from as early as 1755 and as late as 1993. The 1,823 reservoirs included in the database range in size from farm ponds to the largest U.S. reservoirs (such as Lake Mead). Results from 6,617 bathymetric surveys are available in the database. This Data Series provides an improved version of the original RESIS database, termed RESIS-II, and a report describing RESIS-II. The RESIS-II relational database is stored in Microsoft Access and includes more precise location coordinates for most of the reservoirs than the original database but excludes information on reservoir ownership. RESIS-II is anticipated to be a template for further improvements in the database.

On-Line Databases in Mexico.

ERIC Educational Resources Information Center

Molina, Enzo

1986-01-01

Use of online bibliographic databases in Mexico is provided through Servicio de Consulta a Bancos de Informacion, a public service that provides information retrieval, document delivery, translation, technical support, and training services. Technical infrastructure is based on a public packet-switching network and institutional users may receive…

48 CFR 852.215-70 - Service-disabled veteran-owned and veteran-owned small business evaluation factors.

Code of Federal Regulations, 2010 CFR

2010-10-01

...) database. (http://www.VetBiz.gov). (c) Non-veteran offerors proposing to use service-disabled veteran-owned... must be registered and verified in the VetBiz.gov VIP database (http://www.vetbiz.gov). (End of Clause...

Online Reference Service--How to Begin: A Selected Bibliography.

ERIC Educational Resources Information Center

Shroder, Emelie J., Ed.

1982-01-01

Materials in this bibliography were selected and recommended by members of the Use of Machine-Assisted Reference in Public Libraries Committee, Reference and Adult Services Division, American Library Association. Topics include: financial aspects, equipment and communications considerations, comparing databases and database systems, advertising…

The Fabric for Frontier Experiments Project at Fermilab

NASA Astrophysics Data System (ADS)

Kirby, Michael

2014-06-01

The FabrIc for Frontier Experiments (FIFE) project is a new, far-reaching initiative within the Fermilab Scientific Computing Division to drive the future of computing services for experiments at FNAL and elsewhere. It is a collaborative effort between computing professionals and experiment scientists to produce an end-to-end, fully integrated set of services for computing on the grid and clouds, managing data, accessing databases, and collaborating within experiments. FIFE includes 1) easy to use job submission services for processing physics tasks on the Open Science Grid and elsewhere; 2) an extensive data management system for managing local and remote caches, cataloging, querying, moving, and tracking the use of data; 3) custom and generic database applications for calibrations, beam information, and other purposes; 4) collaboration tools including an electronic log book, speakers bureau database, and experiment membership database. All of these aspects will be discussed in detail. FIFE sets the direction of computing at Fermilab experiments now and in the future, and therefore is a major driver in the design of computing services worldwide.

Experience with Multi-Tier Grid MySQL Database Service Resiliency at BNL

NASA Astrophysics Data System (ADS)

Wlodek, Tomasz; Ernst, Michael; Hover, John; Katramatos, Dimitrios; Packard, Jay; Smirnov, Yuri; Yu, Dantong

2011-12-01

We describe the use of F5's BIG-IP smart switch technology (3600 Series and Local Traffic Manager v9.0) to provide load balancing and automatic fail-over to multiple Grid services (GUMS, VOMS) and their associated back-end MySQL databases. This resiliency is introduced in front of the external application servers and also for the back-end database systems, which is what makes it "multi-tier". The combination of solutions chosen to ensure high availability of the services, in particular the database replication and fail-over mechanism, are discussed in detail. The paper explains the design and configuration of the overall system, including virtual servers, machine pools, and health monitors (which govern routing), as well as the master-slave database scheme and fail-over policies and procedures. Pre-deployment planning and stress testing will be outlined. Integration of the systems with our Nagios-based facility monitoring and alerting is also described. And application characteristics of GUMS and VOMS which enable effective clustering will be explained. We then summarize our practical experiences and real-world scenarios resulting from operating a major US Grid center, and assess the applicability of our approach to other Grid services in the future.

The Ties that Bind (the Igh Locus).

PubMed

Krangel, Michael S

2016-05-01

Immunoglobulin heavy-chain locus V(D)J recombination requires a 3D chromatin organization which permits widely distributed variable (V) gene segments to contact distant diversity (D) and joining (J) gene segments. A recent study has identified key nodes in the locus interactome, paving the way for new molecular insights into how the locus is configured for recombination. Copyright © 2016 Elsevier Ltd. All rights reserved.

The Ties That Bind: Mapping the Dynamic Enhancer-Promoter Interactome

DOE PAGES

Spurrell, Cailyn H.; Dickel, Diane E.; Visel, Axel

2016-11-17

Coupling chromosome conformation capture to molecular enrichment for promoter-containing DNA fragments enables the systematic mapping of interactions between individual distal regulatory sequences and their target genes. Here in this Minireview, we describe recent progress in the application of this technique and related complementary approaches to gain insight into the lineage- and cell-type-specific dynamics of interactions between regulators and gene promoters.

Prediction of scaffold proteins based on protein interaction and domain architectures.

PubMed

Oh, Kimin; Yi, Gwan-Su

2016-07-28

Scaffold proteins are known for being crucial regulators of various cellular functions by assembling multiple proteins involved in signaling and metabolic pathways. Identification of scaffold proteins and the study of their molecular mechanisms can open a new aspect of cellular systemic regulation and the results can be applied in the field of medicine and engineering. Despite being highlighted as the regulatory roles of dozens of scaffold proteins, there was only one known computational approach carried out so far to find scaffold proteins from interactomes. However, there were limitations in finding diverse types of scaffold proteins because their criteria were restricted to the classical scaffold proteins. In this paper, we will suggest a systematic approach to predict massive scaffold proteins from interactomes and to characterize the roles of scaffold proteins comprehensively. From a total of 10,419 basic scaffold protein candidates in protein interactomes, we classified them into three classes according to the structural evidences for scaffolding, such as domain architectures, domain interactions and protein complexes. Finally, we could define 2716 highly reliable scaffold protein candidates and their characterized functional features. To assess the accuracy of our prediction, the gold standard positive and negative data sets were constructed. We prepared 158 gold standard positive data and 844 gold standard negative data based on the functional information from Gene Ontology consortium. The precision, sensitivity and specificity of our testing was 80.3, 51.0, and 98.5 % respectively. Through the function enrichment analysis of highly reliable scaffold proteins, we could confirm the significantly enriched functions that are related to scaffold protein binding. We also identified functional association between scaffold proteins and their recruited proteins. Furthermore, we checked that the disease association of scaffold proteins is higher than kinases. In conclusion, we could predict larger volume of scaffold proteins and analyzed their functional characteristics. Deeper understandings about the roles of scaffold proteins from this study will provide a higher opportunity to find therapeutic or engineering applications of scaffold proteins using their functional characteristics.

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Park, Sung-Dong; Department of Biotechnology, College of Life Science and Biotechnology, Yonsei University, Seoul 120-749; Cheon, So Yeong

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

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

PubMed Central

Lee, Yeunkum; Kim, Sun Gyun; Lee, Bokyoung; Zhang, Yinhua; Kim, Yoonhee; Kim, Shinhyun; Kim, Eunjoon; Kang, Hyojin; Han, Kihoon

2017-01-01

Mania causes symptoms of hyperactivity, impulsivity, elevated mood, reduced anxiety and decreased need for sleep, which suggests that the dysfunction of the striatum, a critical component of the brain motor and reward system, can be causally associated with mania. However, detailed molecular pathophysiology underlying the striatal dysfunction in mania remains largely unknown. In this study, we aimed to identify the molecular pathways showing alterations in the striatum of SH3 and multiple ankyrin repeat domains 3 (Shank3)-overexpressing transgenic (TG) mice that display manic-like behaviors. The results of transcriptome analysis suggested that mammalian target of rapamycin complex 1 (mTORC1) signaling may be the primary molecular signature altered in the Shank3 TG striatum. Indeed, we found that striatal mTORC1 activity, as measured by mTOR S2448 phosphorylation, was significantly decreased in the Shank3 TG mice compared to wild-type (WT) mice. To elucidate the potential underlying mechanism, we re-analyzed previously reported protein interactomes, and detected a high connectivity between Shank3 and several upstream regulators of mTORC1, such as tuberous sclerosis 1 (TSC1), TSC2 and Ras homolog enriched in striatum (Rhes), via 94 common interactors that we denominated “Shank3-mTORC1 interactome”. We noticed that, among the 94 common interactors, 11 proteins were related to actin filaments, the level of which was increased in the dorsal striatum of Shank3 TG mice. Furthermore, we could co-immunoprecipitate Shank3, Rhes and Wiskott-Aldrich syndrome protein family verprolin-homologous protein 1 (WAVE1) proteins from the striatal lysate of Shank3 TG mice. By comparing with the gene sets of psychiatric disorders, we also observed that the 94 proteins of Shank3-mTORC1 interactome were significantly associated with bipolar disorder (BD). Altogether, our results suggest a protein interaction-mediated connectivity between Shank3 and certain upstream regulators of mTORC1 that might contribute to the abnormal striatal mTORC1 activity and to the manic-like behaviors of Shank3 TG mice. PMID:28701918

Economic evaluation of manual therapy for musculoskeletal diseases: a protocol for a systematic review and narrative synthesis of evidence.

PubMed

Kim, Chang-Gon; Mun, Su-Jeong; Kim, Ka-Na; Shin, Byung-Cheul; Kim, Nam-Kwen; Lee, Dong-Hyo; Lee, Jung-Han

2016-05-13

Manual therapy is the non-surgical conservative management of musculoskeletal disorders using the practitioner's hands on the patient's body for diagnosing and treating disease. The aim of this study is to systematically review trial-based economic evaluations of manual therapy relative to other interventions used for the management of musculoskeletal diseases. Randomised clinical trials (RCTs) on the economic evaluation of manual therapy for musculoskeletal diseases will be included in the review. The following databases will be searched from their inception: Medline, Embase, Cochrane Central Register of Controlled Trials (CENTRAL), Cumulative Index to Nursing and Allied Health Literature (CINAHL), Econlit, Mantis, Index to Chiropractic Literature, Science Citation Index, Social Science Citation Index, Allied and Complementary Medicine Database (AMED), Cochrane Database of Systematic Reviews (CDSR), National Health Service Database of Abstracts of Reviews of Effects (NHS DARE), National Health Service Health Technology Assessment Database (NHS HTA), National Health Service Economic Evaluation Database (NHS EED), CENTRAL, five Korean medical databases (Oriental Medicine Advanced Searching Integrated System (OASIS), Research Information Service System (RISS), DBPIA, Korean Traditional Knowledge Portal (KTKP) and KoreaMed) and three Chinese databases (China National Knowledge Infrastructure (CNKI), VIP and Wanfang). The evidence for the cost-effectiveness, cost-utility and cost-benefit of manual therapy for musculoskeletal diseases will be assessed as the primary outcome. Health-related quality of life and adverse effects will be assessed as secondary outcomes. We will critically appraise the included studies using the Cochrane risk of bias tool and the Drummond checklist. Results will be summarised using Slavin's qualitative best-evidence synthesis approach. The results of the study will be disseminated via a peer-reviewed journal and/or conference presentations. PROSPERO CRD42015026757. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

78 FR 79660 - Agency Information Collection Activities: Proposed Collection; Comment Request-Child Nutrition...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-12-31

... DEPARTMENT OF AGRICULTURE Food and Nutrition Service Agency Information Collection Activities: Proposed Collection; Comment Request--Child Nutrition Database AGENCY: Food and Nutrition Service, USDA... Nutrition Database in support of the Healthy Hunger Free Kids Act. DATES: Written comments on this notice...

Do Librarians Really Do That? Or Providing Custom, Fee-Based Services.

ERIC Educational Resources Information Center

Whitmore, Susan; Heekin, Janet

This paper describes some of the fee-based, custom services provided by National Institutes of Health (NIH) Library to NIH staff, including knowledge management, clinical liaisons, specialized database searching, bibliographic database development, Web resource guide development, and journal management. The first section discusses selecting the…

--No Title--

Science.gov Websites

interoperability emerging infrastructure for data management on computational grids Software Packages Services : ATLAS: Management and Steering: Computing Management Board Software Project Management Board Database Model Group Computing TDR: 4.5 Event Data 4.8 Database and Data Management Services 6.3.4 Production and

Giving you the business - Competitive pricing of selected Predicasts' databases

NASA Technical Reports Server (NTRS)

Jack, Robert F.

1987-01-01

The pricing policies of different data-base services offering Predicast data bases are examined from a user perspective. The services carrying these data bases are listed; the problems introduced by varying exchange rates and seemingly idiosyncratic price structures are discussed; and numerous specific examples are given.

The Future of Database Information Services.

ERIC Educational Resources Information Center

Auld, Dennis

Changes affecting the delivery of information over the next 10 years are going to be more numerous, farther reaching, and more rapid than those experienced in the last 10 years. Technological, legislative, economic, and sociological factors are all playing vital roles in shaping the environment within which database information services operate.…

A Brief Assessment of LC2IEDM, MIST and Web Services for use in Naval Tactical Data Management

DTIC Science & Technology

2004-07-01

server software, messaging between the client and server, and a database. The MIST database is implemented in an open source DBMS named PostGreSQL ... PostGreSQL had its beginnings at the University of California, Berkley, in 1986 [11]. The development of PostGreSQL has since evolved into a...contact history from the database. DRDC Atlantic TM 2004-148 9 Request Software Request Software Server Side Response from service

Analysis Tool Web Services from the EMBL-EBI.

PubMed

McWilliam, Hamish; Li, Weizhong; Uludag, Mahmut; Squizzato, Silvano; Park, Young Mi; Buso, Nicola; Cowley, Andrew Peter; Lopez, Rodrigo

2013-07-01

Since 2004 the European Bioinformatics Institute (EMBL-EBI) has provided access to a wide range of databases and analysis tools via Web Services interfaces. This comprises services to search across the databases available from the EMBL-EBI and to explore the network of cross-references present in the data (e.g. EB-eye), services to retrieve entry data in various data formats and to access the data in specific fields (e.g. dbfetch), and analysis tool services, for example, sequence similarity search (e.g. FASTA and NCBI BLAST), multiple sequence alignment (e.g. Clustal Omega and MUSCLE), pairwise sequence alignment and protein functional analysis (e.g. InterProScan and Phobius). The REST/SOAP Web Services (http://www.ebi.ac.uk/Tools/webservices/) interfaces to these databases and tools allow their integration into other tools, applications, web sites, pipeline processes and analytical workflows. To get users started using the Web Services, sample clients are provided covering a range of programming languages and popular Web Service tool kits, and a brief guide to Web Services technologies, including a set of tutorials, is available for those wishing to learn more and develop their own clients. Users of the Web Services are informed of improvements and updates via a range of methods.

Analysis Tool Web Services from the EMBL-EBI

PubMed Central

McWilliam, Hamish; Li, Weizhong; Uludag, Mahmut; Squizzato, Silvano; Park, Young Mi; Buso, Nicola; Cowley, Andrew Peter; Lopez, Rodrigo

2013-01-01

Since 2004 the European Bioinformatics Institute (EMBL-EBI) has provided access to a wide range of databases and analysis tools via Web Services interfaces. This comprises services to search across the databases available from the EMBL-EBI and to explore the network of cross-references present in the data (e.g. EB-eye), services to retrieve entry data in various data formats and to access the data in specific fields (e.g. dbfetch), and analysis tool services, for example, sequence similarity search (e.g. FASTA and NCBI BLAST), multiple sequence alignment (e.g. Clustal Omega and MUSCLE), pairwise sequence alignment and protein functional analysis (e.g. InterProScan and Phobius). The REST/SOAP Web Services (http://www.ebi.ac.uk/Tools/webservices/) interfaces to these databases and tools allow their integration into other tools, applications, web sites, pipeline processes and analytical workflows. To get users started using the Web Services, sample clients are provided covering a range of programming languages and popular Web Service tool kits, and a brief guide to Web Services technologies, including a set of tutorials, is available for those wishing to learn more and develop their own clients. Users of the Web Services are informed of improvements and updates via a range of methods. PMID:23671338

DNA Data Bank of Japan

PubMed Central

Mashima, Jun; Kodama, Yuichi; Fujisawa, Takatomo; Katayama, Toshiaki; Okuda, Yoshihiro; Kaminuma, Eli; Ogasawara, Osamu; Okubo, Kousaku; Nakamura, Yasukazu; Takagi, Toshihisa

2017-01-01

The DNA Data Bank of Japan (DDBJ) (http://www.ddbj.nig.ac.jp) has been providing public data services for thirty years (since 1987). We are collecting nucleotide sequence data from researchers as a member of the International Nucleotide Sequence Database Collaboration (INSDC, http://www.insdc.org), in collaboration with the US National Center for Biotechnology Information (NCBI) and European Bioinformatics Institute (EBI). The DDBJ Center also services Japanese Genotype-phenotype Archive (JGA), with the National Bioscience Database Center to collect human-subjected data from Japanese researchers. Here, we report our database activities for INSDC and JGA over the past year, and introduce retrieval and analytical services running on our supercomputer system and their recent modifications. Furthermore, with the Database Center for Life Science, the DDBJ Center improves semantic web technologies to integrate and to share biological data, for providing the RDF version of the sequence data. PMID:27924010

The Breast Cancer DNA Interactome

DTIC Science & Technology

2014-12-01

Research and Education 8. PERFORMING ORGANIZATION REPORT NUMBER Palo Alto, CA 94304 9 . SPONSORING / MONITORING AGENCY NAME(S) AND ADDRESS(ES) 10...act as a growth modulator (7- 9 ). While correlations between serum levels of IGFBP3 and breast cancer have yielded contradictory results (3-5, 10...receptor (EGFR), another breast cancer related gene. EGFR is located approximately 9 Mb from IGFBP3 on chromosome 7. To examine this long-range

The TRiC/CCT chaperone is implicated in Alzheimer's disease based on patient GWAS and an RNAi screen in Aβ-expressing Caenorhabditis elegans.

PubMed

Khabirova, Eleonora; Moloney, Aileen; Marciniak, Stefan J; Williams, Julie; Lomas, David A; Oliver, Stephen G; Favrin, Giorgio; Sattelle, David B; Crowther, Damian C

2014-01-01

The human Aβ peptide causes progressive paralysis when expressed in the muscles of the nematode worm, C. elegans. We have exploited this model of Aβ toxicity by carrying out an RNAi screen to identify genes whose reduced expression modifies the severity of this locomotor phenotype. Our initial finding was that none of the human orthologues of these worm genes is identical with the genome-wide significant GWAS genes reported to date (the "white zone"); moreover there was no identity between worm screen hits and the longer list of GWAS genes which included those with borderline levels of significance (the "grey zone"). This indicates that Aβ toxicity should not be considered as equivalent to sporadic AD. To increase the sensitivity of our analysis, we then considered the physical interactors (+1 interactome) of the products of the genes in both the worm and the white+grey zone lists. When we consider these worm and GWAS gene lists we find that 4 of the 60 worm genes have a +1 interactome overlap that is larger than expected by chance. Two of these genes form a chaperonin complex, the third is closely associated with this complex and the fourth gene codes for actin, the major substrate of the same chaperonin.

Triangular Alignment (TAME). A Tensor-based Approach for Higher-order Network Alignment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mohammadi, Shahin; Gleich, David F.; Kolda, Tamara G.

2015-11-01

Network alignment is an important tool with extensive applications in comparative interactomics. Traditional approaches aim to simultaneously maximize the number of conserved edges and the underlying similarity of aligned entities. We propose a novel formulation of the network alignment problem that extends topological similarity to higher-order structures and provide a new objective function that maximizes the number of aligned substructures. This objective function corresponds to an integer programming problem, which is NP-hard. Consequently, we approximate this objective function as a surrogate function whose maximization results in a tensor eigenvalue problem. Based on this formulation, we present an algorithm called Triangularmore » AlignMEnt (TAME), which attempts to maximize the number of aligned triangles across networks. We focus on alignment of triangles because of their enrichment in complex networks; however, our formulation and resulting algorithms can be applied to general motifs. Using a case study on the NAPABench dataset, we show that TAME is capable of producing alignments with up to 99% accuracy in terms of aligned nodes. We further evaluate our method by aligning yeast and human interactomes. Our results indicate that TAME outperforms the state-of-art alignment methods both in terms of biological and topological quality of the alignments.« less

The RNA-binding protein LARP1 is a post-transcriptional regulator of survival and tumorigenesis in ovarian cancer

PubMed Central

Hopkins, Thomas G.; Mura, Manuela; Al-Ashtal, Hiba A.; Lahr, Roni M.; Abd-Latip, Normala; Sweeney, Katrina; Lu, Haonan; Weir, Justin; El-Bahrawy, Mona; Steel, Jennifer H.; Ghaem-Maghami, Sadaf; Aboagye, Eric O.; Berman, Andrea J.; Blagden, Sarah P.

2016-01-01

RNA-binding proteins (RBPs) are increasingly identified as post-transcriptional drivers of cancer progression. The RBP LARP1 is an mRNA stability regulator, and elevated expression of the protein in hepatocellular and lung cancers is correlated with adverse prognosis. LARP1 associates with an mRNA interactome that is enriched for oncogenic transcripts. Here we explore the role of LARP1 in epithelial ovarian cancer, a disease characterized by the rapid acquisition of resistance to chemotherapy through the induction of pro-survival signalling. We show, using ovarian cell lines and xenografts, that LARP1 is required for cancer cell survival and chemotherapy resistance. LARP1 promotes tumour formation in vivo and maintains cancer stem cell-like populations. Using transcriptomic analysis following LARP1 knockdown, cross-referenced against the LARP1 interactome, we identify BCL2 and BIK as LARP1 mRNA targets. We demonstrate that, through an interaction with the 3′ untranslated regions (3′ UTRs) of BCL2 and BIK, LARP1 stabilizes BCL2 but destabilizes BIK with the net effect of resisting apoptosis. Together, our data indicate that by differentially regulating the stability of a selection of mRNAs, LARP1 promotes ovarian cancer progression and chemotherapy resistance. PMID:26717985

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

PubMed

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

2009-10-01

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

A computational interactome for prioritizing genes associated with complex agronomic traits in rice (Oryza sativa).

PubMed

Liu, Shiwei; Liu, Yihui; Zhao, Jiawei; Cai, Shitao; Qian, Hongmei; Zuo, Kaijing; Zhao, Lingxia; Zhang, Lida

2017-04-01

Rice (Oryza sativa) is one of the most important staple foods for more than half of the global population. Many rice traits are quantitative, complex and controlled by multiple interacting genes. Thus, a full understanding of genetic relationships will be critical to systematically identify genes controlling agronomic traits. We developed a genome-wide rice protein-protein interaction network (RicePPINet, http://netbio.sjtu.edu.cn/riceppinet) using machine learning with structural relationship and functional information. RicePPINet contained 708 819 predicted interactions for 16 895 non-transposable element related proteins. The power of the network for discovering novel protein interactions was demonstrated through comparison with other publicly available protein-protein interaction (PPI) prediction methods, and by experimentally determined PPI data sets. Furthermore, global analysis of domain-mediated interactions revealed RicePPINet accurately reflects PPIs at the domain level. Our studies showed the efficiency of the RicePPINet-based method in prioritizing candidate genes involved in complex agronomic traits, such as disease resistance and drought tolerance, was approximately 2-11 times better than random prediction. RicePPINet provides an expanded landscape of computational interactome for the genetic dissection of agronomically important traits in rice. © 2017 The Authors The Plant Journal © 2017 John Wiley & Sons Ltd.

Chemokine interactome mapping enables tailored intervention in acute and chronic inflammation.

PubMed

von Hundelshausen, Philipp; Agten, Stijn M; Eckardt, Veit; Blanchet, Xavier; Schmitt, Martin M; Ippel, Hans; Neideck, Carlos; Bidzhekov, Kiril; Leberzammer, Julian; Wichapong, Kanin; Faussner, Alexander; Drechsler, Maik; Grommes, Jochen; van Geffen, Johanna P; Li, He; Ortega-Gomez, Almudena; Megens, Remco T A; Naumann, Ronald; Dijkgraaf, Ingrid; Nicolaes, Gerry A F; Döring, Yvonne; Soehnlein, Oliver; Lutgens, Esther; Heemskerk, Johan W M; Koenen, Rory R; Mayo, Kevin H; Hackeng, Tilman M; Weber, Christian

2017-04-05

Chemokines orchestrate leukocyte trafficking and function in health and disease. Heterophilic interactions between chemokines in a given microenvironment may amplify, inhibit, or modulate their activity; however, a systematic evaluation of the chemokine interactome has not been performed. We used immunoligand blotting and surface plasmon resonance to obtain a comprehensive map of chemokine-chemokine interactions and to confirm their specificity. Structure-function analyses revealed that chemokine activity can be enhanced by CC-type heterodimers but inhibited by CXC-type heterodimers. Functional synergism was achieved through receptor heteromerization induced by CCL5-CCL17 or receptor retention at the cell surface via auxiliary proteoglycan binding of CCL5-CXCL4. In contrast, inhibitory activity relied on conformational changes (in CXCL12), affecting receptor signaling. Obligate CC-type heterodimers showed high efficacy and potency and drove acute lung injury and atherosclerosis, processes abrogated by specific CCL5-derived peptide inhibitors or knock-in of an interaction-deficient CXCL4 variant. Atheroprotective effects of CCL17 deficiency were phenocopied by a CCL5-derived peptide disrupting CCL5-CCL17 heterodimers, whereas a CCL5 α-helix peptide mimicked inhibitory effects on CXCL12-driven platelet aggregation. Thus, formation of specific chemokine heterodimers differentially dictates functional activity and can be exploited for therapeutic targeting. Copyright © 2017, American Association for the Advancement of Science.

DPDR-CPI, a server that predicts Drug Positioning and Drug Repositioning via Chemical-Protein Interactome.

PubMed

Luo, Heng; Zhang, Ping; Cao, Xi Hang; Du, Dizheng; Ye, Hao; Huang, Hui; Li, Can; Qin, Shengying; Wan, Chunling; Shi, Leming; He, Lin; Yang, Lun

2016-11-02

The cost of developing a new drug has increased sharply over the past years. To ensure a reasonable return-on-investment, it is useful for drug discovery researchers in both industry and academia to identify all the possible indications for early pipeline molecules. For the first time, we propose the term computational "drug candidate positioning" or "drug positioning", to describe the above process. It is distinct from drug repositioning, which identifies new uses for existing drugs and maximizes their value. Since many therapeutic effects are mediated by unexpected drug-protein interactions, it is reasonable to analyze the chemical-protein interactome (CPI) profiles to predict indications. Here we introduce the server DPDR-CPI, which can make real-time predictions based only on the structure of the small molecule. When a user submits a molecule, the server will dock it across 611 human proteins, generating a CPI profile of features that can be used for predictions. It can suggest the likelihood of relevance of the input molecule towards ~1,000 human diseases with top predictions listed. DPDR-CPI achieved an overall AUROC of 0.78 during 10-fold cross-validations and AUROC of 0.76 for the independent validation. The server is freely accessible via http://cpi.bio-x.cn/dpdr/.

Examining the Interactome of Huperzine A by Magnetic Biopanning

PubMed Central

Guo, Wei; Liu, Shupeng; Peng, Jinliang; Wei, Xiaohui; Sun, Ye; Qiu, Yangsheng; Gao, Guangwei; Wang, Peng; Xu, Yuhong

2012-01-01

Huperzine A is a bioactive compound derived from traditional Chinese medicine plant Qian Ceng Ta (Huperzia serrata), and was found to have multiple neuroprotective effects. In addition to being a potent acetylcholinesterase inhibitor, it was thought to act through other mechanisms such as antioxidation, antiapoptosis, etc. However, the molecular targets involved with these mechanisms were not identified. In this study, we attempted to exam the interactome of Huperzine A using a cDNA phage display library and also mammalian brain tissue extracts. The drugs were chemically linked on the surface of magnetic particles and the interactive phages or proteins were collected and analyzed. Among the various cDNA expressing phages selected, one was identified to encode the mitochondria NADH dehydrogenase subunit 1. Specific bindings between the drug and the target phages and target proteins were confirmed. Another enriched phage clone was identified as mitochondria ATP synthase, which was also panned out from the proteome of mouse brain tissue lysate. These data indicated the possible involvement of mitochondrial respiratory chain matrix enzymes in Huperzine A's pharmacological effects. Such involvement had been suggested by previous studies based on enzyme activity changes. Our data supported the new mechanism. Overall we demonstrated the feasibility of using magnetic biopanning as a simple and viable method for investigating the complex molecular mechanisms of bioactive molecules. PMID:22615909

Split luciferase complementation assay to detect regulated protein-protein interactions in rice protoplasts in a large-scale format

PubMed Central

2014-01-01

Background The rice interactome, in which a network of protein-protein interactions has been elucidated in rice, is a useful resource to identify functional modules of rice signal transduction pathways. Protein-protein interactions occur in cells in two ways, constitutive and regulative. While a yeast-based high-throughput method has been widely used to identify the constitutive interactions, a method to detect the regulated interactions is rarely developed for a large-scale analysis. Results A split luciferase complementation assay was applied to detect the regulated interactions in rice. A transformation method of rice protoplasts in a 96-well plate was first established for a large-scale analysis. In addition, an antibody that specifically recognizes a carboxyl-terminal fragment of Renilla luciferase was newly developed. A pair of antibodies that recognize amino- and carboxyl- terminal fragments of Renilla luciferase, respectively, was then used to monitor quality and quantity of interacting recombinant-proteins accumulated in the cells. For a proof-of-concept, the method was applied to detect the gibberellin-dependent interaction between GIBBERELLIN INSENSITIVE DWARF1 and SLENDER RICE 1. Conclusions A method to detect regulated protein-protein interactions was developed towards establishment of the rice interactome. PMID:24987490

The Co-Metabolism within the Gut-Brain Metabolic Interaction: Potential Targets for Drug Treatment and Design.

PubMed

Obrenovich, Mark; Flückiger, Rudolf; Sykes, Lorraine; Donskey, Curtis

2016-01-01

We know that within the complex mammalian gut is any number of metabolic biomes. The gut has been sometimes called the "second brain" within the "gut-brain axis". A more informative term would be the gut-brain metabolic interactome, which is coined here to underscore the relationship between the digestive system and cognitive function or dysfunction as the case may be. Co-metabolism between the host and the intestinal microbiota is essential for life's processes. How diet, lifestyle, antibiotics and other factors shape the gut microbiome constitutes a rapidly growing area of research. Conversely, the gut microbiome also affects mammalian systems. Metabolites of the gut-brain axis are potential targets for treatment and drug design since the interaction or biochemical interplay results in net metabolite production or end-products with either positive or negative effects on human health. This review explores the gut-brain metabolic interactome, with particular emphasis on drug design and treatment strategies and how commensal bacteria or their disruption lead to dysbiosis and the effect this has on neurochemistry. Increasing data indicate that the intestinal microbiome can affect neurobiology, from mental and even behavioral health to memory, depression, mood, anxiety, obesity, cravings and even the creation and maintenance of the blood brain barrier.

Proteomic analyses of signalling complexes associated with receptor tyrosine kinase identify novel members of fibroblast growth factor receptor 3 interactome.

PubMed

Balek, Lukas; Nemec, Pavel; Konik, Peter; Kunova Bosakova, Michaela; Varecha, Miroslav; Gudernova, Iva; Medalova, Jirina; Krakow, Deborah; Krejci, Pavel

2018-01-01

Receptor tyrosine kinases (RTKs) form multiprotein complexes that initiate and propagate intracellular signals and determine the RTK-specific signalling patterns. Unravelling the full complexity of protein interactions within the RTK-associated complexes is essential for understanding of RTK functions, yet it remains an understudied area of cell biology. We describe a comprehensive approach to characterize RTK interactome. A single tag immunoprecipitation and phosphotyrosine protein isolation followed by mass-spectrometry was used to identify proteins interacting with fibroblast growth factor receptor 3 (FGFR3). A total of 32 experiments were carried out in two different cell types and identified 66 proteins out of which only 20 (30.3%) proteins were already known FGFR interactors. Using co-immunoprecipitations, we validated FGFR3 interaction with adapter protein STAM1, transcriptional regulator SHOX2, translation elongation factor eEF1A1, serine/threonine kinases ICK, MAK and CCRK, and inositol phosphatase SHIP2. We show that unappreciated signalling mediators exist for well-studied RTKs, such as FGFR3, and may be identified via proteomic approaches described here. These approaches are easily adaptable to other RTKs, enabling identification of novel signalling mediators for majority of the known human RTKs. Copyright © 2017 Elsevier Inc. All rights reserved.

Network topological analysis reveals the functional cohesiveness for the newly discovered links by Yeast 2 Hybrid approach

NASA Astrophysics Data System (ADS)

Ghiassian, Susan; Pevzner, Sam; Rolland, Thomas; Tassan, Murat; Barabasi, Albert Laszlo; Vidal, Mark; CCNR, Northeastern University Collaboration; Dana Farber Cancer Institute Collaboration

2014-03-01

Protein-protein interaction maps and interactomes are the blueprint of Network Medicine and systems biology and are being experimentally studied by different groups. Despite the wide usage of Literature Curated Interactome (LCI), these sources are biased towards different parameters such as highly studied proteins. Yeast two hybrid method is a high throughput experimental setup which screens proteins in an unbiased fashion. Current knowledge of protein interactions is far from complete. In fact the previous offered data from Y2H method (2005), is estimated to offer only 5% of all potential protein interactions. Currently this coverage has increased to 20% of what is known as reference HI In this work we study the topological properties of Y2H protein-protein interactions network with LCI and show although they both agree on some properties, LCI shows a clear unbiased nature of interaction selections. Most importantly, we assess the properties of PPI as it evolves with increasing the coverage. We show that, the newly discovered interactions tend to connect proteins that have been closer than average in the previous PPI release. reinforcing the modular structure of PPI. Furthermore, we show, some unseen effects on PPI (as opposed to LCI) can be explained by its incompleteness.

The SSU processome interactome in Saccharomyces cerevisiae reveals novel protein subcomplexes.

PubMed

Vincent, Nicholas G; Charette, J Michael; Baserga, Susan J

2018-01-01

Ribosome assembly is an evolutionarily conserved and energy intensive process required for cellular growth, proliferation, and maintenance. In yeast, assembly of the small ribosomal subunit (SSU) requires approximately 75 assembly factors that act in coordination to form the SSU processome, a 6 MDa ribonucleoprotein complex. The SSU processome is required for processing, modifying, and folding the preribosomal RNA (rRNA) to prepare it for incorporation into the mature SSU. Although the protein composition of the SSU processome has been known for some time, the interaction network of the proteins required for its assembly has remained poorly defined. Here, we have used a semi-high-throughput yeast two-hybrid (Y2H) assay and coimmunoprecipitation validation method to produce a high-confidence interactome of SSU processome assembly factors (SPAFs), providing essential insight into SSU assembly and ribosome biogenesis. Further, we used glycerol density-gradient sedimentation to reveal the presence of protein subcomplexes that have not previously been observed. Our work not only provides essential insight into SSU assembly and ribosome biogenesis, but also serves as an important resource for future investigations into how defects in biogenesis and assembly cause congenital disorders of ribosomes known as ribosomopathies. © 2018 Vincent et al.; Published by Cold Spring Harbor Laboratory Press for the RNA Society.

Elucidation of the Ebola virus VP24 cellular interactome and disruption of virus biology through targeted inhibition of host-cell protein function.

PubMed

García-Dorival, Isabel; Wu, Weining; Dowall, Stuart; Armstrong, Stuart; Touzelet, Olivier; Wastling, Jonathan; Barr, John N; Matthews, David; Carroll, Miles; Hewson, Roger; Hiscox, Julian A

2014-11-07

Viral pathogenesis in the infected cell is a balance between antiviral responses and subversion of host-cell processes. Many viral proteins specifically interact with host-cell proteins to promote virus biology. Understanding these interactions can lead to knowledge gains about infection and provide potential targets for antiviral therapy. One such virus is Ebola, which has profound consequences for human health and causes viral hemorrhagic fever where case fatality rates can approach 90%. The Ebola virus VP24 protein plays a critical role in the evasion of the host immune response and is likely to interact with multiple cellular proteins. To map these interactions and better understand the potential functions of VP24, label-free quantitative proteomics was used to identify cellular proteins that had a high probability of forming the VP24 cellular interactome. Several known interactions were confirmed, thus placing confidence in the technique, but new interactions were also discovered including one with ATP1A1, which is involved in osmoregulation and cell signaling. Disrupting the activity of ATP1A1 in Ebola-virus-infected cells with a small molecule inhibitor resulted in a decrease in progeny virus, thus illustrating how quantitative proteomics can be used to identify potential therapeutic targets.

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

PubMed

Kast, Juergen

2008-10-01

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

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

PubMed Central

Kast, Juergen

2008-01-01

Proteins are the true workhorses of any cell. To carry out specific tasks, they frequently bind other molecules in their surroundings. Due to their structural complexity and flexibility, the most diverse array of interactions is seen with other proteins. The different geometries and affinities available for such interactions typically bestow specific functions on proteins. Having available a map of protein–protein interactions is therefore of enormous importance for any researcher interested in gaining insight into biological systems at the level of cells and organisms. In a recent report, a novel approach has been employed that relies on the spontaneous folding of complementary enzyme fragments fused to two different proteins to test whether these interact in their actual cellular context [Tarassov et al., Science 320, 1465–1470 (2008)]. Genome-wide application of this protein-fragment complementation assay has resulted in the first map of the in vivo interactome of Saccharomyces cerevisiae. The current data show striking similarities but also significant differences to those obtained using other large-scale approaches for the same task. This warrants a general discussion of the current state of affairs of protein–protein interaction studies and foreseeable future trends, highlighting their significance for a variety of applications and their potential to revolutionize our understanding of the architecture and dynamics of biological systems. PMID:19404434

The Rab-binding Profiles of Bacterial Virulence Factors during Infection.

PubMed

So, Ernest C; Schroeder, Gunnar N; Carson, Danielle; Mattheis, Corinna; Mousnier, Aurélie; Broncel, Malgorzata; Tate, Edward W; Frankel, Gad

2016-03-11

Legionella pneumophila, the causative agent of Legionnaire's disease, uses its type IV secretion system to translocate over 300 effector proteins into host cells. These effectors subvert host cell signaling pathways to ensure bacterial proliferation. Despite their importance for pathogenesis, the roles of most of the effectors are yet to be characterized. Key to understanding the function of effectors is the identification of host proteins they bind during infection. We previously developed a novel tandem-affinity purification (TAP) approach using hexahistidine and BirA-specific biotinylation tags for isolating translocated effector complexes from infected cells whose composition were subsequently deciphered by mass spectrometry. Here we further advanced the workflow for the TAP approach and determined the infection-dependent interactomes of the effectors SidM and LidA, which were previously reported to promiscuously bind multiple Rab GTPases in vitro. In this study we defined a stringent subset of Rab GTPases targeted by SidM and LidA during infection, comprising of Rab1A, 1B, 6, and 10; in addition, LidA targets Rab14 and 18. Taken together, this study illustrates the power of this approach to profile the intracellular interactomes of bacterial effectors during infection. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

iCAVE: an open source tool for visualizing biomolecular networks in 3D, stereoscopic 3D and immersive 3D

PubMed Central

Liluashvili, Vaja; Kalayci, Selim; Fluder, Eugene; Wilson, Manda; Gabow, Aaron

2017-01-01

Abstract Visualizations of biomolecular networks assist in systems-level data exploration in many cellular processes. Data generated from high-throughput experiments increasingly inform these networks, yet current tools do not adequately scale with concomitant increase in their size and complexity. We present an open source software platform, interactome-CAVE (iCAVE), for visualizing large and complex biomolecular interaction networks in 3D. Users can explore networks (i) in 3D using a desktop, (ii) in stereoscopic 3D using 3D-vision glasses and a desktop, or (iii) in immersive 3D within a CAVE environment. iCAVE introduces 3D extensions of known 2D network layout, clustering, and edge-bundling algorithms, as well as new 3D network layout algorithms. Furthermore, users can simultaneously query several built-in databases within iCAVE for network generation or visualize their own networks (e.g., disease, drug, protein, metabolite). iCAVE has modular structure that allows rapid development by addition of algorithms, datasets, or features without affecting other parts of the code. Overall, iCAVE is the first freely available open source tool that enables 3D (optionally stereoscopic or immersive) visualizations of complex, dense, or multi-layered biomolecular networks. While primarily designed for researchers utilizing biomolecular networks, iCAVE can assist researchers in any field. PMID:28814063

iCAVE: an open source tool for visualizing biomolecular networks in 3D, stereoscopic 3D and immersive 3D.

PubMed

Liluashvili, Vaja; Kalayci, Selim; Fluder, Eugene; Wilson, Manda; Gabow, Aaron; Gümüs, Zeynep H

2017-08-01

Visualizations of biomolecular networks assist in systems-level data exploration in many cellular processes. Data generated from high-throughput experiments increasingly inform these networks, yet current tools do not adequately scale with concomitant increase in their size and complexity. We present an open source software platform, interactome-CAVE (iCAVE), for visualizing large and complex biomolecular interaction networks in 3D. Users can explore networks (i) in 3D using a desktop, (ii) in stereoscopic 3D using 3D-vision glasses and a desktop, or (iii) in immersive 3D within a CAVE environment. iCAVE introduces 3D extensions of known 2D network layout, clustering, and edge-bundling algorithms, as well as new 3D network layout algorithms. Furthermore, users can simultaneously query several built-in databases within iCAVE for network generation or visualize their own networks (e.g., disease, drug, protein, metabolite). iCAVE has modular structure that allows rapid development by addition of algorithms, datasets, or features without affecting other parts of the code. Overall, iCAVE is the first freely available open source tool that enables 3D (optionally stereoscopic or immersive) visualizations of complex, dense, or multi-layered biomolecular networks. While primarily designed for researchers utilizing biomolecular networks, iCAVE can assist researchers in any field. © The Authors 2017. Published by Oxford University Press.

Pre-Service Teachers' Use of Library Databases: Some Insights

ERIC Educational Resources Information Center

Lamb, Janeen; Howard, Sarah; Easey, Michael

2014-01-01

The aim of this study is to investigate if providing mathematics education pre-service teachers with animated library tutorials on library and database searches changes their searching practices. This study involved the completion of a survey by 138 students and seven individual interviews before and after library search demonstration videos were…

The Fabric for Frontier Experiments Project at Fermilab

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kirby, Michael

2014-01-01

The FabrIc for Frontier Experiments (FIFE) project is a new, far-reaching initiative within the Fermilab Scientific Computing Division to drive the future of computing services for experiments at FNAL and elsewhere. It is a collaborative effort between computing professionals and experiment scientists to produce an end-to-end, fully integrated set of services for computing on the grid and clouds, managing data, accessing databases, and collaborating within experiments. FIFE includes 1) easy to use job submission services for processing physics tasks on the Open Science Grid and elsewhere, 2) an extensive data management system for managing local and remote caches, cataloging, querying,more » moving, and tracking the use of data, 3) custom and generic database applications for calibrations, beam information, and other purposes, 4) collaboration tools including an electronic log book, speakers bureau database, and experiment membership database. All of these aspects will be discussed in detail. FIFE sets the direction of computing at Fermilab experiments now and in the future, and therefore is a major driver in the design of computing services worldwide.« less

76 FR 56657 - Unlicensed Operation in the TV Broadcast Bands

Federal Register 2010, 2011, 2012, 2013, 2014

2011-09-14

... Second Report and Order the Commission decided to designate one or more database administrator from the private sector to create and operate TV band databases. The TV band database administrators will act on behalf of the FCC, but will offer a privately owned and operated service. Each database administrator...

The Neotoma Paleoecology Database

NASA Astrophysics Data System (ADS)

Grimm, E. C.; Ashworth, A. C.; Barnosky, A. D.; Betancourt, J. L.; Bills, B.; Booth, R.; Blois, J.; Charles, D. F.; Graham, R. W.; Goring, S. J.; Hausmann, S.; Smith, A. J.; Williams, J. W.; Buckland, P.

2015-12-01

The Neotoma Paleoecology Database (www.neotomadb.org) is a multiproxy, open-access, relational database that includes fossil data for the past 5 million years (the late Neogene and Quaternary Periods). Modern distributional data for various organisms are also being made available for calibration and paleoecological analyses. The project is a collaborative effort among individuals from more than 20 institutions worldwide, including domain scientists representing a spectrum of Pliocene-Quaternary fossil data types, as well as experts in information technology. Working groups are active for diatoms, insects, ostracodes, pollen and plant macroscopic remains, testate amoebae, rodent middens, vertebrates, age models, geochemistry and taphonomy. Groups are also active in developing online tools for data analyses and for developing modules for teaching at different levels. A key design concept of NeotomaDB is that stewards for various data types are able to remotely upload and manage data. Cooperatives for different kinds of paleo data, or from different regions, can appoint their own stewards. Over the past year, much progress has been made on development of the steward software-interface that will enable this capability. The steward interface uses web services that provide access to the database. More generally, these web services enable remote programmatic access to the database, which both desktop and web applications can use and which provide real-time access to the most current data. Use of these services can alleviate the need to download the entire database, which can be out-of-date as soon as new data are entered. In general, the Neotoma web services deliver data either from an entire table or from the results of a view. Upon request, new web services can be quickly generated. Future developments will likely expand the spatial and temporal dimensions of the database. NeotomaDB is open to receiving new datasets and stewards from the global Quaternary community. Research is supported by NSF EAR-0622349.

Accessing the SEED genome databases via Web services API: tools for programmers.

PubMed

Disz, Terry; Akhter, Sajia; Cuevas, Daniel; Olson, Robert; Overbeek, Ross; Vonstein, Veronika; Stevens, Rick; Edwards, Robert A

2010-06-14

The SEED integrates many publicly available genome sequences into a single resource. The database contains accurate and up-to-date annotations based on the subsystems concept that leverages clustering between genomes and other clues to accurately and efficiently annotate microbial genomes. The backend is used as the foundation for many genome annotation tools, such as the Rapid Annotation using Subsystems Technology (RAST) server for whole genome annotation, the metagenomics RAST server for random community genome annotations, and the annotation clearinghouse for exchanging annotations from different resources. In addition to a web user interface, the SEED also provides Web services based API for programmatic access to the data in the SEED, allowing the development of third-party tools and mash-ups. The currently exposed Web services encompass over forty different methods for accessing data related to microbial genome annotations. The Web services provide comprehensive access to the database back end, allowing any programmer access to the most consistent and accurate genome annotations available. The Web services are deployed using a platform independent service-oriented approach that allows the user to choose the most suitable programming platform for their application. Example code demonstrate that Web services can be used to access the SEED using common bioinformatics programming languages such as Perl, Python, and Java. We present a novel approach to access the SEED database. Using Web services, a robust API for access to genomics data is provided, without requiring large volume downloads all at once. The API ensures timely access to the most current datasets available, including the new genomes as soon as they come online.

Experience with ATLAS MySQL PanDA database service

NASA Astrophysics Data System (ADS)

Smirnov, Y.; Wlodek, T.; De, K.; Hover, J.; Ozturk, N.; Smith, J.; Wenaus, T.; Yu, D.

2010-04-01

The PanDA distributed production and analysis system has been in production use for ATLAS data processing and analysis since late 2005 in the US, and globally throughout ATLAS since early 2008. Its core architecture is based on a set of stateless web services served by Apache and backed by a suite of MySQL databases that are the repository for all PanDA information: active and archival job queues, dataset and file catalogs, site configuration information, monitoring information, system control parameters, and so on. This database system is one of the most critical components of PanDA, and has successfully delivered the functional and scaling performance required by PanDA, currently operating at a scale of half a million jobs per week, with much growth still to come. In this paper we describe the design and implementation of the PanDA database system, its architecture of MySQL servers deployed at BNL and CERN, backup strategy and monitoring tools. The system has been developed, thoroughly tested, and brought to production to provide highly reliable, scalable, flexible and available database services for ATLAS Monte Carlo production, reconstruction and physics analysis.

Geo-spatial Service and Application based on National E-government Network Platform and Cloud

NASA Astrophysics Data System (ADS)

Meng, X.; Deng, Y.; Li, H.; Yao, L.; Shi, J.

2014-04-01

With the acceleration of China's informatization process, our party and government take a substantive stride in advancing development and application of digital technology, which promotes the evolution of e-government and its informatization. Meanwhile, as a service mode based on innovative resources, cloud computing may connect huge pools together to provide a variety of IT services, and has become one relatively mature technical pattern with further studies and massive practical applications. Based on cloud computing technology and national e-government network platform, "National Natural Resources and Geospatial Database (NRGD)" project integrated and transformed natural resources and geospatial information dispersed in various sectors and regions, established logically unified and physically dispersed fundamental database and developed national integrated information database system supporting main e-government applications. Cross-sector e-government applications and services are realized to provide long-term, stable and standardized natural resources and geospatial fundamental information products and services for national egovernment and public users.

The INFN-CNAF Tier-1 GEMSS Mass Storage System and database facility activity

NASA Astrophysics Data System (ADS)

Ricci, Pier Paolo; Cavalli, Alessandro; Dell'Agnello, Luca; Favaro, Matteo; Gregori, Daniele; Prosperini, Andrea; Pezzi, Michele; Sapunenko, Vladimir; Zizzi, Giovanni; Vagnoni, Vincenzo

2015-05-01

The consolidation of Mass Storage services at the INFN-CNAF Tier1 Storage department that has occurred during the last 5 years, resulted in a reliable, high performance and moderately easy-to-manage facility that provides data access, archive, backup and database services to several different use cases. At present, the GEMSS Mass Storage System, developed and installed at CNAF and based upon an integration between the IBM GPFS parallel filesystem and the Tivoli Storage Manager (TSM) tape management software, is one of the largest hierarchical storage sites in Europe. It provides storage resources for about 12% of LHC data, as well as for data of other non-LHC experiments. Files are accessed using standard SRM Grid services provided by the Storage Resource Manager (StoRM), also developed at CNAF. Data access is also provided by XRootD and HTTP/WebDaV endpoints. Besides these services, an Oracle database facility is in production characterized by an effective level of parallelism, redundancy and availability. This facility is running databases for storing and accessing relational data objects and for providing database services to the currently active use cases. It takes advantage of several Oracle technologies, like Real Application Cluster (RAC), Automatic Storage Manager (ASM) and Enterprise Manager centralized management tools, together with other technologies for performance optimization, ease of management and downtime reduction. The aim of the present paper is to illustrate the state-of-the-art of the INFN-CNAF Tier1 Storage department infrastructures and software services, and to give a brief outlook to forthcoming projects. A description of the administrative, monitoring and problem-tracking tools that play a primary role in managing the whole storage framework is also given.

Towards a Global Service Registry for the World-Wide LHC Computing Grid

NASA Astrophysics Data System (ADS)

Field, Laurence; Alandes Pradillo, Maria; Di Girolamo, Alessandro

2014-06-01

The World-Wide LHC Computing Grid encompasses a set of heterogeneous information systems; from central portals such as the Open Science Grid's Information Management System and the Grid Operations Centre Database, to the WLCG information system, where the information sources are the Grid services themselves. Providing a consistent view of the information, which involves synchronising all these informations systems, is a challenging activity that has lead the LHC virtual organisations to create their own configuration databases. This experience, whereby each virtual organisation's configuration database interfaces with multiple information systems, has resulted in the duplication of effort, especially relating to the use of manual checks for the handling of inconsistencies. The Global Service Registry aims to address this issue by providing a centralised service that aggregates information from multiple information systems. It shows both information on registered resources (i.e. what should be there) and available resources (i.e. what is there). The main purpose is to simplify the synchronisation of the virtual organisation's own configuration databases, which are used for job submission and data management, through the provision of a single interface for obtaining all the information. By centralising the information, automated consistency and validation checks can be performed to improve the overall quality of information provided. Although internally the GLUE 2.0 information model is used for the purpose of integration, the Global Service Registry in not dependent on any particular information model for ingestion or dissemination. The intention is to allow the virtual organisation's configuration databases to be decoupled from the underlying information systems in a transparent way and hence simplify any possible future migration due to the evolution of those systems. This paper presents the Global Service Registry architecture, its advantages compared to the current situation and how it can support the evolution of information systems.

Annual Review of Database Developments: 1993.

ERIC Educational Resources Information Center

Basch, Reva

1993-01-01

Reviews developments in the database industry for 1993. Topics addressed include scientific and technical information; environmental issues; social sciences; legal information; business and marketing; news services; documentation; databases and document delivery; electronic bulletin boards and the Internet; and information industry organizational…

Annual Review of Database Development: 1992.

ERIC Educational Resources Information Center

Basch, Reva

1992-01-01

Reviews recent trends in databases and online systems. Topics discussed include new access points for established databases; acquisitions, consolidations, and competition between vendors; European coverage; international services; online reference materials, including telephone directories; political and legal materials and public records;…

The new IAGOS Database Portal

NASA Astrophysics Data System (ADS)

Boulanger, Damien; Gautron, Benoit; Thouret, Valérie; Fontaine, Alain

2016-04-01

IAGOS (In-service Aircraft for a Global Observing System) is a European Research Infrastructure which aims at the provision of long-term, regular and spatially resolved in situ observations of the atmospheric composition. IAGOS observation systems are deployed on a fleet of commercial aircraft. The IAGOS database is an essential part of the global atmospheric monitoring network. It contains IAGOS-core data and IAGOS-CARIBIC (Civil Aircraft for the Regular Investigation of the Atmosphere Based on an Instrument Container) data. The IAGOS Database Portal (http://www.iagos.fr, damien.boulanger@obs-mip.fr) is part of the French atmospheric chemistry data center AERIS (http://www.aeris-data.fr). The new IAGOS Database Portal has been released in December 2015. The main improvement is the interoperability implementation with international portals or other databases in order to improve IAGOS data discovery. In the frame of the IGAS project (IAGOS for the Copernicus Atmospheric Service), a data network has been setup. It is composed of three data centers: the IAGOS database in Toulouse; the HALO research aircraft database at DLR (https://halo-db.pa.op.dlr.de); and the CAMS data center in Jülich (http://join.iek.fz-juelich.de). The CAMS (Copernicus Atmospheric Monitoring Service) project is a prominent user of the IGAS data network. The new portal provides improved and new services such as the download in NetCDF or NASA Ames formats, plotting tools (maps, time series, vertical profiles, etc.) and user management. Added value products are available on the portal: back trajectories, origin of air masses, co-location with satellite data, etc. The link with the CAMS data center, through JOIN (Jülich OWS Interface), allows to combine model outputs with IAGOS data for inter-comparison. Finally IAGOS metadata has been standardized (ISO 19115) and now provides complete information about data traceability and quality.

The Universal Protein Resource (UniProt): an expanding universe of protein information.

PubMed

Wu, Cathy H; Apweiler, Rolf; Bairoch, Amos; Natale, Darren A; Barker, Winona C; Boeckmann, Brigitte; Ferro, Serenella; Gasteiger, Elisabeth; Huang, Hongzhan; Lopez, Rodrigo; Magrane, Michele; Martin, Maria J; Mazumder, Raja; O'Donovan, Claire; Redaschi, Nicole; Suzek, Baris

2006-01-01

The Universal Protein Resource (UniProt) provides a central resource on protein sequences and functional annotation with three database components, each addressing a key need in protein bioinformatics. The UniProt Knowledgebase (UniProtKB), comprising the manually annotated UniProtKB/Swiss-Prot section and the automatically annotated UniProtKB/TrEMBL section, is the preeminent storehouse of protein annotation. The extensive cross-references, functional and feature annotations and literature-based evidence attribution enable scientists to analyse proteins and query across databases. The UniProt Reference Clusters (UniRef) speed similarity searches via sequence space compression by merging sequences that are 100% (UniRef100), 90% (UniRef90) or 50% (UniRef50) identical. Finally, the UniProt Archive (UniParc) stores all publicly available protein sequences, containing the history of sequence data with links to the source databases. UniProt databases continue to grow in size and in availability of information. Recent and upcoming changes to database contents, formats, controlled vocabularies and services are described. New download availability includes all major releases of UniProtKB, sequence collections by taxonomic division and complete proteomes. A bibliography mapping service has been added, and an ID mapping service will be available soon. UniProt databases can be accessed online at http://www.uniprot.org or downloaded at ftp://ftp.uniprot.org/pub/databases/.

Veterans Administration Databases

Cancer.gov

The Veterans Administration Information Resource Center provides database and informatics experts, customer service, expert advice, information products, and web technology to VA researchers and others.

78 FR 2363 - Notification of Deletion of a System of Records; Automated Trust Funds Database

Federal Register 2010, 2011, 2012, 2013, 2014

2013-01-11

... Database AGENCY: Animal and Plant Health Inspection Service, USDA. ACTION: Notice of deletion of a system... establishing the Automated Trust Funds (ATF) database system of records. The Federal Information Security... Integrity Act of 1982, Public Law 97-255, provided authority for the system. The ATF database has been...

76 FR 25344 - Information Collection(s) Being Reviewed by the Federal Communications Commission

Federal Register 2010, 2011, 2012, 2013, 2014

2011-05-04

... Second Report and Order the Commission decided to designate one or more database administrators from the private sector to create and operate TV bands databases. The TV band database administrators will act on behalf of the FCC, but will offer a privately owned and operated service. Each database administrator...

NNDC Data Services

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tuli, J.K.; Sonzogni,A.

The National Nuclear Data Center has provided remote access to some of its resources since 1986. The major databases and other resources available currently through NNDC Web site are summarized. The National Nuclear Data Center (NNDC) has provided remote access to the nuclear physics databases it maintains and to other resources since 1986. With considerable innovation access is now mostly through the Web. The NNDC Web pages have been modernized to provide a consistent state-of-the-art style. The improved database services and other resources available from the NNOC site at www.nndc.bnl.govwill be described.

Conceptual Model Formalization in a Semantic Interoperability Service Framework: Transforming Relational Database Schemas to OWL.

PubMed

Bravo, Carlos; Suarez, Carlos; González, Carolina; López, Diego; Blobel, Bernd

2014-01-01

Healthcare information is distributed through multiple heterogeneous and autonomous systems. Access to, and sharing of, distributed information sources are a challenging task. To contribute to meeting this challenge, this paper presents a formal, complete and semi-automatic transformation service from Relational Databases to Web Ontology Language. The proposed service makes use of an algorithm that allows to transform several data models of different domains by deploying mainly inheritance rules. The paper emphasizes the relevance of integrating the proposed approach into an ontology-based interoperability service to achieve semantic interoperability.

Latest developments for the IAGOS database: Interoperability and metadata

NASA Astrophysics Data System (ADS)

Boulanger, Damien; Gautron, Benoit; Thouret, Valérie; Schultz, Martin; van Velthoven, Peter; Broetz, Bjoern; Rauthe-Schöch, Armin; Brissebrat, Guillaume

2014-05-01

In-service Aircraft for a Global Observing System (IAGOS, http://www.iagos.org) aims at the provision of long-term, frequent, regular, accurate, and spatially resolved in situ observations of the atmospheric composition. IAGOS observation systems are deployed on a fleet of commercial aircraft. The IAGOS database is an essential part of the global atmospheric monitoring network. Data access is handled by open access policy based on the submission of research requests which are reviewed by the PIs. Users can access the data through the following web sites: http://www.iagos.fr or http://www.pole-ether.fr as the IAGOS database is part of the French atmospheric chemistry data centre ETHER (CNES and CNRS). The database is in continuous development and improvement. In the framework of the IGAS project (IAGOS for GMES/COPERNICUS Atmospheric Service), major achievements will be reached, such as metadata and format standardisation in order to interoperate with international portals and other databases, QA/QC procedures and traceability, CARIBIC (Civil Aircraft for the Regular Investigation of the Atmosphere Based on an Instrument Container) data integration within the central database, and the real-time data transmission. IGAS work package 2 aims at providing the IAGOS data to users in a standardized format including the necessary metadata and information on data processing, data quality and uncertainties. We are currently redefining and standardizing the IAGOS metadata for interoperable use within GMES/Copernicus. The metadata are compliant with the ISO 19115, INSPIRE and NetCDF-CF conventions. IAGOS data will be provided to users in NetCDF or NASA Ames format. We also are implementing interoperability between all the involved IAGOS data services, including the central IAGOS database, the former MOZAIC and CARIBIC databases, Aircraft Research DLR database and the Jülich WCS web application JOIN (Jülich OWS Interface) which combines model outputs with in situ data for intercomparison. The optimal data transfer protocol is being investigated to insure the interoperability. To facilitate satellite and model validation, tools will be made available for co-location and comparison with IAGOS. We will enhance the JOIN application in order to properly display aircraft data as vertical profiles and along individual flight tracks and to allow for graphical comparison to model results that are accessible through interoperable web services, such as the daily products from the GMES/Copernicus atmospheric service.

The Ties That Bind: Mapping the Dynamic Enhancer-Promoter Interactome.

PubMed

Spurrell, Cailyn H; Dickel, Diane E; Visel, Axel

2016-11-17

Coupling chromosome conformation capture to molecular enrichment for promoter-containing DNA fragments enables the systematic mapping of interactions between individual distal regulatory sequences and their target genes. In this Minireview, we describe recent progress in the application of this technique and related complementary approaches to gain insight into the lineage- and cell-type-specific dynamics of interactions between regulators and gene promoters. Copyright © 2016 Elsevier Inc. All rights reserved.

The data and system Nikkei Telecom "Industry/Technology Information Service"

NASA Astrophysics Data System (ADS)

Kurata, Shizuya; Sueyoshi, Yukio

Nihoh Keizai Shimbun started supplying "Industry/Technology Information Service" from July 1989 as a part of Nikkei Telecom Package, which is online information service using personal computers for its terminals. Previously Nikkei's database service mainly covered such areas as economy, corporations and markets. On the other hand, the new "Industry/Technology Information Service" (main data covers industry by industry information-semi macro) is attracting a good deal of attention as it is the first to supply science and technology related database which has not been touched before. Moreover it is attracting attention technically as it has an access by gateway system to JOIS which is the first class science technology file in Japan. This report introduces data and system of "Industry/Technology Information Service" briefly.

Behavioral health services utilization among older adults identified within a state abuse hotline database.

PubMed

Schonfeld, Lawrence; Larsen, Rebecca G; Stiles, Paul G

2006-04-01

This study examined the extent to which older adults identified in a statewide abuse hotline registry utilized behavioral health services. This is important as mental health issues have been identified as a high priority for filling gaps in services for victims of mistreatment. We compared Medicaid and Medicare claims data for two groups of older adults: those using health services and identified within a statewide abuse hotline information system and those claimants not identified within the hotline database. Behavioral health service use was greater among those identified in the abuse hotline database. The penetration rate (percentage of service users out of all enrollees) for Medicaid behavioral health service claims was more than twice that of other service users, with costs of services about 30% greater. Analyses of Medicare data revealed that the penetration rate for those in the hotline data was almost 6 times greater at approximately twice the cost compared to other service users. The results provide evidence for previous assumptions that mistreated individuals experience a higher rate of behavioral health disorders. As mental health screening by adult protective services is rarely conducted, the results suggest the need to train investigators and other service providers to screen older adults for behavioral health and substance-abuse issues as well as physical signs of abuse. Further research on the relationship of abuse to behavioral health might focus on collection of additional data involving more specific victim-related characteristics and comparisons of cases of mistreatment versus self-neglect.

circlncRNAnet: an integrated web-based resource for mapping functional networks of long or circular forms of noncoding RNAs.

PubMed

Wu, Shao-Min; Liu, Hsuan; Huang, Po-Jung; Chang, Ian Yi-Feng; Lee, Chi-Ching; Yang, Chia-Yu; Tsai, Wen-Sy; Tan, Bertrand Chin-Ming

2018-01-01

Despite their lack of protein-coding potential, long noncoding RNAs (lncRNAs) and circular RNAs (circRNAs) have emerged as key determinants in gene regulation, acting to fine-tune transcriptional and signaling output. These noncoding RNA transcripts are known to affect expression of messenger RNAs (mRNAs) via epigenetic and post-transcriptional regulation. Given their widespread target spectrum, as well as extensive modes of action, a complete understanding of their biological relevance will depend on integrative analyses of systems data at various levels. While a handful of publicly available databases have been reported, existing tools do not fully capture, from a network perspective, the functional implications of lncRNAs or circRNAs of interest. Through an integrated and streamlined design, circlncRNAnet aims to broaden the understanding of ncRNA candidates by testing in silico several hypotheses of ncRNA-based functions, on the basis of large-scale RNA-seq data. This web server is implemented with several features that represent advances in the bioinformatics of ncRNAs: (1) a flexible framework that accepts and processes user-defined next-generation sequencing-based expression data; (2) multiple analytic modules that assign and productively assess the regulatory networks of user-selected ncRNAs by cross-referencing extensively curated databases; (3) an all-purpose, information-rich workflow design that is tailored to all types of ncRNAs. Outputs on expression profiles, co-expression networks and pathways, and molecular interactomes, are dynamically and interactively displayed according to user-defined criteria. In short, users may apply circlncRNAnet to obtain, in real time, multiple lines of functionally relevant information on circRNAs/lncRNAs of their interest. In summary, circlncRNAnet provides a "one-stop" resource for in-depth analyses of ncRNA biology. circlncRNAnet is freely available at http://app.cgu.edu.tw/circlnc/. © The Authors 2017. Published by Oxford University Press.

EQUIP: A European Survey of Quality Criteria for the Evaluation of Databases.

ERIC Educational Resources Information Center

Wilson, T. D.

1998-01-01

Reports on two stages of an investigation into the perceived quality of online databases. Presents data from 989 questionnaires from 600 database users in 12 European and Scandinavian countries and results of a test of the SERVQUAL methodology for identifying user expectations about database services. Lists statements used in the SERVQUAL survey.…

47 CFR 52.105 - Warehousing.

Code of Federal Regulations, 2014 CFR

2014-10-01

... the Service Management System database without having an actual toll free subscriber for whom those... database; or (2) The Responsible Organization does not have an identified toll free subscriber agreeing to... database shall serve as that Responsible Organization's certification that there is an identified toll free...

47 CFR 52.105 - Warehousing.

Code of Federal Regulations, 2011 CFR

2011-10-01

... the Service Management System database without having an actual toll free subscriber for whom those... database; or (2) The Responsible Organization does not have an identified toll free subscriber agreeing to... database shall serve as that Responsible Organization's certification that there is an identified toll free...

47 CFR 52.105 - Warehousing.

Code of Federal Regulations, 2013 CFR

2013-10-01

... the Service Management System database without having an actual toll free subscriber for whom those... database; or (2) The Responsible Organization does not have an identified toll free subscriber agreeing to... database shall serve as that Responsible Organization's certification that there is an identified toll free...

47 CFR 52.105 - Warehousing.

Code of Federal Regulations, 2010 CFR

2010-10-01

... the Service Management System database without having an actual toll free subscriber for whom those... database; or (2) The Responsible Organization does not have an identified toll free subscriber agreeing to... database shall serve as that Responsible Organization's certification that there is an identified toll free...

47 CFR 52.105 - Warehousing.

Code of Federal Regulations, 2012 CFR

2012-10-01

... the Service Management System database without having an actual toll free subscriber for whom those... database; or (2) The Responsible Organization does not have an identified toll free subscriber agreeing to... database shall serve as that Responsible Organization's certification that there is an identified toll free...

Improving Care And Research Electronic Data Trust Antwerp (iCAREdata): a research database of linked data on out-of-hours primary care.

PubMed

Colliers, Annelies; Bartholomeeusen, Stefaan; Remmen, Roy; Coenen, Samuel; Michiels, Barbara; Bastiaens, Hilde; Van Royen, Paul; Verhoeven, Veronique; Holmgren, Philip; De Ruyck, Bernard; Philips, Hilde

2016-05-04

Primary out-of-hours care is developing throughout Europe. High-quality databases with linked data from primary health services can help to improve research and future health services. In 2014, a central clinical research database infrastructure was established (iCAREdata: Improving Care And Research Electronic Data Trust Antwerp, www.icaredata.eu ) for primary and interdisciplinary health care at the University of Antwerp, linking data from General Practice Cooperatives, Emergency Departments and Pharmacies during out-of-hours care. Medical data are pseudonymised using the services of a Trusted Third Party, which encodes private information about patients and physicians before data is sent to iCAREdata. iCAREdata provides many new research opportunities in the fields of clinical epidemiology, health care management and quality of care. A key aspect will be to ensure the quality of data registration by all health care providers. This article describes the establishment of a research database and the possibilities of linking data from different primary out-of-hours care providers, with the potential to help to improve research and the quality of health care services.

Pharmacoepidemiology resources in Ireland-an introduction to pharmacy claims data.

PubMed

Sinnott, Sarah-Jo; Bennett, Kathleen; Cahir, Caitriona

2017-11-01

Administrative health data, such as pharmacy claims data, present a valuable resource for conducting pharmacoepidemiological and health services research. Often, data are available for whole populations allowing population level analyses. Moreover, their routine collection ensures that the data reflect health care utilisation in the real-world setting compared to data collected in clinical trials. The Irish Health Service Executive-Primary Care Reimbursement Service (HSE-PCRS) community pharmacy claims database is described. The availability of demographic variables and drug-related information is discussed. The strengths and limitations associated using this database for conducting research are presented, in particular, internal and external validity. Examples of recently conducted research using the HSE-PCRS pharmacy claims database are used to illustrate the breadth of its use. The HSE-PCRS national pharmacy claims database is a large, high-quality, valid and accurate data source for measuring drug exposure in specific populations in Ireland. The main limitation is the lack of generalisability for those aged <70 years and the lack of information on indication or outcome.

The designing and implementation of PE teaching information resource database based on broadband network

NASA Astrophysics Data System (ADS)

Wang, Jian

2017-01-01

In order to change traditional PE teaching mode and realize the interconnection, interworking and sharing of PE teaching resources, a distance PE teaching platform based on broadband network is designed and PE teaching information resource database is set up. The designing of PE teaching information resource database takes Windows NT 4/2000Server as operating system platform, Microsoft SQL Server 7.0 as RDBMS, and takes NAS technology for data storage and flow technology for video service. The analysis of system designing and implementation shows that the dynamic PE teaching information resource sharing platform based on Web Service can realize loose coupling collaboration, realize dynamic integration and active integration and has good integration, openness and encapsulation. The distance PE teaching platform based on Web Service and the design scheme of PE teaching information resource database can effectively solve and realize the interconnection, interworking and sharing of PE teaching resources and adapt to the informatization development demands of PE teaching.

[Quality management and participation into clinical database].

PubMed

Okubo, Suguru; Miyata, Hiroaki; Tomotaki, Ai; Motomura, Noboru; Murakami, Arata; Ono, Minoru; Iwanaka, Tadashi

2013-07-01

Quality management is necessary for establishing useful clinical database in cooperation with healthcare professionals and facilities. The ways of management are 1) progress management of data entry, 2) liaison with database participants (healthcare professionals), and 3) modification of data collection form. In addition, healthcare facilities are supposed to consider ethical issues and information security for joining clinical databases. Database participants should check ethical review boards and consultation service for patients.

Reactome graph database: Efficient access to complex pathway data

PubMed Central

Korninger, Florian; Viteri, Guilherme; Marin-Garcia, Pablo; Ping, Peipei; Wu, Guanming; Stein, Lincoln; D’Eustachio, Peter

2018-01-01

Reactome is a free, open-source, open-data, curated and peer-reviewed knowledgebase of biomolecular pathways. One of its main priorities is to provide easy and efficient access to its high quality curated data. At present, biological pathway databases typically store their contents in relational databases. This limits access efficiency because there are performance issues associated with queries traversing highly interconnected data. The same data in a graph database can be queried more efficiently. Here we present the rationale behind the adoption of a graph database (Neo4j) as well as the new ContentService (REST API) that provides access to these data. The Neo4j graph database and its query language, Cypher, provide efficient access to the complex Reactome data model, facilitating easy traversal and knowledge discovery. The adoption of this technology greatly improved query efficiency, reducing the average query time by 93%. The web service built on top of the graph database provides programmatic access to Reactome data by object oriented queries, but also supports more complex queries that take advantage of the new underlying graph-based data storage. By adopting graph database technology we are providing a high performance pathway data resource to the community. The Reactome graph database use case shows the power of NoSQL database engines for complex biological data types. PMID:29377902

Reactome graph database: Efficient access to complex pathway data.

PubMed

Fabregat, Antonio; Korninger, Florian; Viteri, Guilherme; Sidiropoulos, Konstantinos; Marin-Garcia, Pablo; Ping, Peipei; Wu, Guanming; Stein, Lincoln; D'Eustachio, Peter; Hermjakob, Henning

2018-01-01

Reactome is a free, open-source, open-data, curated and peer-reviewed knowledgebase of biomolecular pathways. One of its main priorities is to provide easy and efficient access to its high quality curated data. At present, biological pathway databases typically store their contents in relational databases. This limits access efficiency because there are performance issues associated with queries traversing highly interconnected data. The same data in a graph database can be queried more efficiently. Here we present the rationale behind the adoption of a graph database (Neo4j) as well as the new ContentService (REST API) that provides access to these data. The Neo4j graph database and its query language, Cypher, provide efficient access to the complex Reactome data model, facilitating easy traversal and knowledge discovery. The adoption of this technology greatly improved query efficiency, reducing the average query time by 93%. The web service built on top of the graph database provides programmatic access to Reactome data by object oriented queries, but also supports more complex queries that take advantage of the new underlying graph-based data storage. By adopting graph database technology we are providing a high performance pathway data resource to the community. The Reactome graph database use case shows the power of NoSQL database engines for complex biological data types.

Human Connectome Project Informatics: quality control, database services, and data visualization

PubMed Central

Marcus, Daniel S.; Harms, Michael P.; Snyder, Abraham Z.; Jenkinson, Mark; Wilson, J Anthony; Glasser, Matthew F.; Barch, Deanna M.; Archie, Kevin A.; Burgess, Gregory C.; Ramaratnam, Mohana; Hodge, Michael; Horton, William; Herrick, Rick; Olsen, Timothy; McKay, Michael; House, Matthew; Hileman, Michael; Reid, Erin; Harwell, John; Coalson, Timothy; Schindler, Jon; Elam, Jennifer S.; Curtiss, Sandra W.; Van Essen, David C.

2013-01-01

The Human Connectome Project (HCP) has developed protocols, standard operating and quality control procedures, and a suite of informatics tools to enable high throughput data collection, data sharing, automated data processing and analysis, and data mining and visualization. Quality control procedures include methods to maintain data collection consistency over time, to measure head motion, and to establish quantitative modality-specific overall quality assessments. Database services developed as customizations of the XNAT imaging informatics platform support both internal daily operations and open access data sharing. The Connectome Workbench visualization environment enables user interaction with HCP data and is increasingly integrated with the HCP's database services. Here we describe the current state of these procedures and tools and their application in the ongoing HCP study. PMID:23707591

Systematic Determination of Human Cyclin Dependent Kinase (CDK)-9 Interactome Identifies Novel Functions in RNA Splicing Mediated by the DEAD Box (DDX)-5/17 RNA Helicases.

PubMed

Yang, Jun; Zhao, Yingxin; Kalita, Mridul; Li, Xueling; Jamaluddin, Mohammad; Tian, Bing; Edeh, Chukwudi B; Wiktorowicz, John E; Kudlicki, Andrzej; Brasier, Allan R

2015-10-01

Inducible transcriptional elongation is a rapid, stereotypic mechanism for activating immediate early immune defense genes by the epithelium in response to viral pathogens. Here, the recruitment of a multifunctional complex containing the cyclin dependent kinase 9 (CDK9) triggers the process of transcriptional elongation activating resting RNA polymerase engaged with innate immune response (IIR) genes. To identify additional functional activity of the CDK9 complex, we conducted immunoprecipitation (IP) enrichment-stable isotope labeling LC-MS/MS of the CDK9 complex in unstimulated cells and from cells activated by a synthetic dsRNA, polyinosinic/polycytidylic acid [poly (I:C)]. 245 CDK9 interacting proteins were identified with high confidence in the basal state and 20 proteins in four functional classes were validated by IP-SRM-MS. These data identified that CDK9 interacts with DDX 5/17, a family of ATP-dependent RNA helicases, important in alternative RNA splicing of NFAT5, and mH2A1 mRNA two proteins controlling redox signaling. A direct comparison of the basal versus activated state was performed using stable isotope labeling and validated by IP-SRM-MS. Recruited into the CDK9 interactome in response to poly(I:C) stimulation are HSPB1, DNA dependent kinases, and cytoskeletal myosin proteins that exchange with 60S ribosomal structural proteins. An integrated human CDK9 interactome map was developed containing all known human CDK9- interacting proteins. These data were used to develop a probabilistic global map of CDK9-dependent target genes that predicted two functional states controlling distinct cellular functions, one important in immune and stress responses. The CDK9-DDX5/17 complex was shown to be functionally important by shRNA-mediated knockdown, where differential accumulation of alternatively spliced NFAT5 and mH2A1 transcripts and alterations in downstream redox signaling were seen. The requirement of CDK9 for DDX5 recruitment to NFAT5 and mH2A1 chromatin target was further demonstrated using chromatin immunoprecipitation (ChIP). These data indicate that CDK9 is a dynamic multifunctional enzyme complex mediating not only transcriptional elongation, but also alternative RNA splicing and potentially translational control. © 2015 by The American Society for Biochemistry and Molecular Biology, Inc.

MaxiK channel interactome reveals its interaction with GABA transporter 3 and heat shock protein 60 in the mammalian brain.

PubMed

Singh, H; Li, M; Hall, L; Chen, S; Sukur, S; Lu, R; Caputo, A; Meredith, A L; Stefani, E; Toro, L

2016-03-11

Large conductance voltage and calcium-activated potassium (MaxiK) channels are activated by membrane depolarization and elevated cytosolic Ca(2+). In the brain, they localize to neurons and astrocytes, where they play roles such as resetting the membrane potential during an action potential, neurotransmitter release, and neurovascular coupling. MaxiK channels are known to associate with several modulatory proteins and accessory subunits, and each of these interactions can have distinct physiological consequences. To uncover new players in MaxiK channel brain physiology, we applied a directed proteomic approach and obtained MaxiK channel pore-forming α subunit brain interactome using specific antibodies. Controls included immunoprecipitations with rabbit immunoglobulin G (IgG) and with anti-MaxiK antibodies in wild type and MaxiK channel knockout mice (Kcnma1(-/-)), respectively. We have found known and unreported interactive partners that localize to the plasma membrane, extracellular space, cytosol and intracellular organelles including mitochondria, nucleus, endoplasmic reticulum and Golgi apparatus. Localization of MaxiK channel to mitochondria was further confirmed using purified brain mitochondria colabeled with MitoTracker. Independent proof of MaxiK channel interaction with previously unidentified partners is given for GABA transporter 3 (GAT3) and heat shock protein 60 (HSP60). In human embryonic kidney 293 cells containing SV40 T-antigen (HEK293T) cells, both GAT3 and HSP60 coimmunoprecipitated and colocalized with MaxiK channel; colabeling was observed mainly at the cell periphery with GAT3 and intracellularly with HSP60 with protein proximity indices of ∼ 0.6 and ∼ 0.4, respectively. In rat primary hippocampal neurons, colocalization index was identical for GAT3 (∼ 0.6) and slightly higher for HSP60 (∼ 0.5) association with MaxiK channel. The results of this study provide a complete interactome of MaxiK channel the mouse brain, further establish the localization of MaxiK channel in the mouse brain mitochondria and demonstrate the interaction of MaxiK channel with GAT3 and HSP60 in neurons. The interaction of MaxiK channel with GAT3 opens the possibility of a role of MaxiK channel in GABA homeostasis and signaling. Copyright © 2016 IBRO. Published by Elsevier Ltd. All rights reserved.

Intelligent databases assist transparent and sound economic valuation of ecosystem services.

PubMed

Villa, Ferdinando; Ceroni, Marta; Krivov, Sergey

2007-06-01

Assessment and economic valuation of services provided by ecosystems to humans has become a crucial phase in environmental management and policy-making. As primary valuation studies are out of the reach of many institutions, secondary valuation or benefit transfer, where the results of previous studies are transferred to the geographical, environmental, social, and economic context of interest, is becoming increasingly common. This has brought to light the importance of environmental valuation databases, which provide reliable valuation data to inform secondary valuation with enough detail to enable the transfer of values across contexts. This paper describes the role of next-generation, intelligent databases (IDBs) in assisting the activity of valuation. Such databases employ artificial intelligence to inform the transfer of values across contexts, enforcing comparability of values and allowing users to generate custom valuation portfolios that synthesize previous studies and provide aggregated value estimates to use as a base for secondary valuation. After a general introduction, we introduce the Ecosystem Services Database, the first IDB for environmental valuation to be made available to the public, describe its functionalities and the lessons learned from its usage, and outline the remaining needs and expected future developments in the field.

A database application for wilderness character monitoring

Treesearch

Ashley Adams; Peter Landres; Simon Kingston

2012-01-01

The National Park Service (NPS) Wilderness Stewardship Division, in collaboration with the Aldo Leopold Wilderness Research Institute and the NPS Inventory and Monitoring Program, developed a database application to facilitate tracking and trend reporting in wilderness character. The Wilderness Character Monitoring Database allows consistent, scientifically based...

A Database as a Service for the Healthcare System to Store Physiological Signal Data.

PubMed

Chang, Hsien-Tsung; Lin, Tsai-Huei

2016-01-01

Wearable devices that measure physiological signals to help develop self-health management habits have become increasingly popular in recent years. These records are conducive for follow-up health and medical care. In this study, based on the characteristics of the observed physiological signal records- 1) a large number of users, 2) a large amount of data, 3) low information variability, 4) data privacy authorization, and 5) data access by designated users-we wish to resolve physiological signal record-relevant issues utilizing the advantages of the Database as a Service (DaaS) model. Storing a large amount of data using file patterns can reduce database load, allowing users to access data efficiently; the privacy control settings allow users to store data securely. The results of the experiment show that the proposed system has better database access performance than a traditional relational database, with a small difference in database volume, thus proving that the proposed system can improve data storage performance.

A Database as a Service for the Healthcare System to Store Physiological Signal Data

PubMed Central

Lin, Tsai-Huei

2016-01-01

Wearable devices that measure physiological signals to help develop self-health management habits have become increasingly popular in recent years. These records are conducive for follow-up health and medical care. In this study, based on the characteristics of the observed physiological signal records– 1) a large number of users, 2) a large amount of data, 3) low information variability, 4) data privacy authorization, and 5) data access by designated users—we wish to resolve physiological signal record-relevant issues utilizing the advantages of the Database as a Service (DaaS) model. Storing a large amount of data using file patterns can reduce database load, allowing users to access data efficiently; the privacy control settings allow users to store data securely. The results of the experiment show that the proposed system has better database access performance than a traditional relational database, with a small difference in database volume, thus proving that the proposed system can improve data storage performance. PMID:28033415

Library information services.

NASA Astrophysics Data System (ADS)

Michold, U.; Cummins, M.; Watson, J. M.; Holmquist, J.; Shobbrook, R.

Contents: library catalogs and holdings; indexing and abstract services; preprint services; electronic journals and newsletters; alerting services; commercial databases; informal networking; use of a thesaurus for on-line searching. An extensive list of access pointers for library catalogs and services, electronic newsletters, and publishers and bookshops is enclosed.

The University of South Carolina: College and University Computing Environment.

ERIC Educational Resources Information Center

CAUSE/EFFECT, 1987

1987-01-01

Both academic and administrative computing as well as network and communications services for the university are provided and supported by the Computer Services Division. Academic services, administrative services, systems engineering and database administration, communications, networking services, operations, and library technologies are…

Necessity and feasibility of improving mental health services in China: A systematic qualitative review.

PubMed

Zhao, Xudong; Liu, Liang; Hu, Chengping; Chen, Fazhan; Sun, Xirong

2017-07-01

It has been nearly 40 years since the reform and opening up of Mainland China. The mental health services system has developed rapidly as a part of the profound socioeconomic changes that ensued. However, its development has not been as substantial as other areas of medical care. For the current qualitative systematic review, we searched databases, including China Biology Medicine disc, Weipu, China National Knowledge Infrastructure, Wanfang digital periodical full text data, China's important newspaper full text database, China Statistical Yearbook database, etc. The content of primary research, literature, and policy papers about the evolution and development of Chinese mental health services was systemically reviewed and analysed by using thematic analysis. Two main themes relative to the necessity and feasibility of reforming the current mental health services system emerged. We discuss 5 corresponding subthemes under the umbrella of the necessity of improving the current treatment, rehabilitation, prevention, and service systems and 7 requirements for the feasibility of reforming the current system. We conclude that as the development of the Chinese economy and the spirit of humanistic care continue, the improvement and reformation of the mental health services system are both necessary and feasible. Copyright © 2017 John Wiley & Sons, Ltd.

A storage scheme for the real-time database supporting the on-line commitment

NASA Astrophysics Data System (ADS)

Dai, Hong-bin; Jing, Yu-jian; Wang, Hui

2013-07-01

The modern SCADA (Supervisory Control and Data acquisition) systems have been applied to various aspects of everyday life. As the time goes on, the requirements of the applications of the systems vary. Thus the data structure of the real-time database, which is the core of a SCADA system, often needs modification. As a result, the commitment consisting of a sequence of configuration operations modifying the data structure of the real-time database is performed from time to time. Though it is simple to perform the off-line commitment by first stopping and then restarting the system, during which all the data in the real-time database are reconstructed. It is much more preferred or in some cases even necessary to perform the on-line commitment, during which the real-time database can still provide real-time service and the system continues working normally. In this paper, a storage scheme of the data in the real-time database is proposed. It helps the real-time database support its on-line commitment, during which real-time service is still available.

Point of care use of a personal digital assistant for patient consultation management: experience of an intravenous resource nurse team in a major Canadian teaching hospital.

PubMed

Bosma, Laine; Balen, Robert M; Davidson, Erin; Jewesson, Peter J

2003-01-01

The development and integration of a personal digital assistant (PDA)-based point-of-care database into an intravenous resource nurse (IVRN) consultation service for the purposes of consultation management and service characterization are described. The IVRN team provides a consultation service 7 days a week in this 1000-bed tertiary adult care teaching hospital. No simple, reliable method for documenting IVRN patient care activity and facilitating IVRN-initiated patient follow-up evaluation was available. Implementation of a PDA database with exportability of data to statistical analysis software was undertaken in July 2001. A Palm IIIXE PDA was purchased and a three-table, 13-field database was developed using HanDBase software. During the 7-month period of data collection, the IVRN team recorded 4868 consultations for 40 patient care areas. Full analysis of service characteristics was conducted using SPSS 10.0 software. Team members adopted the new technology with few problems, and the authors now can efficiently track and analyze the services provided by their IVRN team.

A Geospatial Database that Supports Derivation of Climatological Features of Severe Weather

NASA Astrophysics Data System (ADS)

Phillips, M.; Ansari, S.; Del Greco, S.

2007-12-01

The Severe Weather Data Inventory (SWDI) at NOAA's National Climatic Data Center (NCDC) provides user access to archives of several datasets critical to the detection and evaluation of severe weather. These datasets include archives of: · NEXRAD Level-III point features describing general storm structure, hail, mesocyclone and tornado signatures · National Weather Service Storm Events Database · National Weather Service Local Storm Reports collected from storm spotters · National Weather Service Warnings · Lightning strikes from Vaisala's National Lightning Detection Network (NLDN) SWDI archives all of these datasets in a spatial database that allows for convenient searching and subsetting. These data are accessible via the NCDC web site, Web Feature Services (WFS) or automated web services. The results of interactive web page queries may be saved in a variety of formats, including plain text, XML, Google Earth's KMZ, standards-based NetCDF and Shapefile. NCDC's Storm Risk Assessment Project (SRAP) uses data from the SWDI database to derive gridded climatology products that show the spatial distributions of the frequency of various events. SRAP also can relate SWDI events to other spatial data such as roads, population, watersheds, and other geographic, sociological, or economic data to derive products that are useful in municipal planning, emergency management, the insurance industry, and other areas where there is a need to quantify and qualify how severe weather patterns affect people and property.

Computational Framework for Analysis of Prey–Prey Associations in Interaction Proteomics Identifies Novel Human Protein–Protein Interactions and Networks

PubMed Central

Saha, Sudipto; Dazard, Jean-Eudes; Xu, Hua; Ewing, Rob M.

2013-01-01

Large-scale protein–protein interaction data sets have been generated for several species including yeast and human and have enabled the identification, quantification, and prediction of cellular molecular networks. Affinity purification-mass spectrometry (AP-MS) is the preeminent methodology for large-scale analysis of protein complexes, performed by immunopurifying a specific “bait” protein and its associated “prey” proteins. The analysis and interpretation of AP-MS data sets is, however, not straightforward. In addition, although yeast AP-MS data sets are relatively comprehensive, current human AP-MS data sets only sparsely cover the human interactome. Here we develop a framework for analysis of AP-MS data sets that addresses the issues of noise, missing data, and sparsity of coverage in the context of a current, real world human AP-MS data set. Our goal is to extend and increase the density of the known human interactome by integrating bait–prey and cocomplexed preys (prey–prey associations) into networks. Our framework incorporates a score for each identified protein, as well as elements of signal processing to improve the confidence of identified protein–protein interactions. We identify many protein networks enriched in known biological processes and functions. In addition, we show that integrated bait–prey and prey–prey interactions can be used to refine network topology and extend known protein networks. PMID:22845868

Identification of LMO2 transcriptome and interactome in diffuse large B-cell lymphoma

PubMed Central

Cubedo, Elena; Gentles, Andrew J.; Huang, Chuanxin; Natkunam, Yasodha; Bhatt, Shruti; Lu, Xiaoqing; Jiang, Xiaoyu; Romero-Camarero, Isabel; Freud, Aharon; Zhao, Shuchun; Bacchi, Carlos E.; Martínez-Climent, Jose A.; Sánchez-García, Isidro; Melnick, Ari

2012-01-01

LMO2 regulates gene expression by facilitating the formation of multipartite DNA-binding complexes. In B cells, LMO2 is specifically up-regulated in the germinal center (GC) and is expressed in GC-derived non-Hodgkin lymphomas. LMO2 is one of the most powerful prognostic indicators in diffuse large B-cell (DLBCL) patients. However, its function in GC B cells and DLBCL is currently unknown. In this study, we characterized the LMO2 transcriptome and transcriptional complex in DLBCL cells. LMO2 regulates genes implicated in kinetochore function, chromosome assembly, and mitosis. Overexpression of LMO2 in DLBCL cell lines results in centrosome amplification. In DLBCL, the LMO2 complex contains some of the traditional partners, such as LDB1, E2A, HEB, Lyl1, ETO2, and SP1, but not TAL1 or GATA proteins. Furthermore, we identified novel LMO2 interacting partners: ELK1, nuclear factor of activated T-cells (NFATc1), and lymphoid enhancer-binding factor1 (LEF1) proteins. Reporter assays revealed that LMO2 increases transcriptional activity of NFATc1 and decreases transcriptional activity of LEF1 proteins. Overall, our studies identified a novel LMO2 transcriptome and interactome in DLBCL and provides a platform for future elucidation of LMO2 function in GC B cells and DLBCL pathogenesis. PMID:22517897

A systems immunology approach identifies the collective impact of 5 miRs in Th2 inflammation.

PubMed

Kılıç, Ayşe; Santolini, Marc; Nakano, Taiji; Schiller, Matthias; Teranishi, Mizue; Gellert, Pascal; Ponomareva, Yuliya; Braun, Thomas; Uchida, Shizuka; Weiss, Scott T; Sharma, Amitabh; Renz, Harald

2018-06-07

Allergic asthma is a chronic inflammatory disease dominated by a CD4+ T helper 2 (Th2) cell signature. The immune response amplifies in self-enforcing loops, promoting Th2-driven cellular immunity and leaving the host unable to terminate inflammation. Posttranscriptional mechanisms, including microRNAs (miRs), are pivotal in maintaining immune homeostasis. Since an altered expression of various miRs has been associated with T cell-driven diseases, including asthma, we hypothesized that miRs control mechanisms ensuring Th2 stability and maintenance in the lung. We isolated murine CD4+ Th2 cells from allergic inflamed lungs and profiled gene and miR expression. Instead of focusing on the magnitude of miR differential expression, here we addressed the secondary consequences for the set of molecular interactions in the cell, the interactome. We developed the Impact of Differential Expression Across Layers, a network-based algorithm to prioritize disease-relevant miRs based on the central role of their targets in the molecular interactome. This method identified 5 Th2-related miRs (mir27b, mir206, mir106b, mir203, and mir23b) whose antagonization led to a sharp reduction of the Th2 phenotype. Overall, a systems biology tool was developed and validated, highlighting the role of miRs in Th2-driven immune response. This result offers potentially novel approaches for therapeutic interventions.

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

PubMed

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

2016-06-03

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

TCTEX1D4 Interactome in Human Testis: Unraveling the Function of Dynein Light Chain in Spermatozoa

PubMed Central

Freitas, Maria João; Korrodi-Gregório, Luís; Morais-Santos, Filipa; da Cruz e Silva, Edgar

2014-01-01

Abstract Studies were designed to identify the TCTEX1D4 interactome in human testis, with the purpose of unraveling putative protein complexes essential to male reproduction and thus novel TCTEX1D4 functions. TCTEX1D4 is a dynein light chain that belongs to the DYNT1/TCTEX1 family. In spermatozoa, it appears to be important to sperm motility, intraflagellar transport, and acrosome reaction. To contribute to the knowledge on TCTEX1D4 function in testis and spermatozoa, a yeast two-hybrid assay was performed in testis, which allowed the identification of 40 novel TCTEX1D4 interactors. Curiously, another dynein light chain, TCTEX1D2, was identified and its existence demonstrated for the first time in human spermatozoa. Immunofluorescence studies proved that TCTEX1D2 is an intra-acrosomal protein also present in the midpiece, suggesting a role in cargo movement in human spermatozoa. Further, an in silico profile of TCTEX1D4 revealed that most TCTEX1D4 interacting proteins were not previously characterized and the ones described present a very broad nature. This reinforces TCTEX1D4 as a dynein light chain that is capable of interacting with a variety of functionally different proteins. These observations collectively contribute to a deeper molecular understanding of the human spermatozoa function. PMID:24606217

Examining Myddosome Formation by Luminescence-Based Mammalian Interactome Mapping (LUMIER).

PubMed

Wolz, Olaf-Oliver; Koegl, Manfred; Weber, Alexander N R

2018-01-01

Recent structural, biochemical, and functional studies have led to the notion that many of the post-receptor signaling complexes in innate immunity have a multimeric, multi-protein architecture whose hierarchical assembly is vital for function. The Myddosome is a post-receptor complex in the cytoplasmic signaling of Toll-like receptors (TLR) and the Interleukin-1 receptor (IL-1R), involving the proteins MyD88, IL-1R-associated kinase 4 (IRAK4), and IRAK2. Its importance is strikingly illustrated by the fact that rare germline mutations in MYD88 causing high susceptibility to infections are characterized by failure to assemble Myddosomes; conversely, gain-of-function MYD88 mutations leading to oncogenic hyperactivation of NF-κB show increased Myddosome formation. Reliable methods to probe Myddosome formation experimentally are therefore vital to further study the properties of this important post-receptor complex and its role in innate immunity, such as its regulation by posttranslational modification. Compared to structural and biochemical analyses, luminescence-based mammalian interactome mapping (LUMIER) is a straightforward, automatable, quantifiable, and versatile technique to study protein-protein interactions in a physiologically relevant context. We adapted LUMIER for Myddosome analysis and provide here a basic background of this technique, suitable experimental protocols, and its potential for medium-throughput screening. The principles presented herein can be adapted to other signaling pathways.

Integrated Genomic and Network-Based Analyses of Complex Diseases and Human Disease Network.

PubMed

Al-Harazi, Olfat; Al Insaif, Sadiq; Al-Ajlan, Monirah A; Kaya, Namik; Dzimiri, Nduna; Colak, Dilek

2016-06-20

A disease phenotype generally reflects various pathobiological processes that interact in a complex network. The highly interconnected nature of the human protein interaction network (interactome) indicates that, at the molecular level, it is difficult to consider diseases as being independent of one another. Recently, genome-wide molecular measurements, data mining and bioinformatics approaches have provided the means to explore human diseases from a molecular basis. The exploration of diseases and a system of disease relationships based on the integration of genome-wide molecular data with the human interactome could offer a powerful perspective for understanding the molecular architecture of diseases. Recently, subnetwork markers have proven to be more robust and reliable than individual biomarker genes selected based on gene expression profiles alone, and achieve higher accuracy in disease classification. We have applied one of these methodologies to idiopathic dilated cardiomyopathy (IDCM) data that we have generated using a microarray and identified significant subnetworks associated with the disease. In this paper, we review the recent endeavours in this direction, and summarize the existing methodologies and computational tools for network-based analysis of complex diseases and molecular relationships among apparently different disorders and human disease network. We also discuss the future research trends and topics of this promising field. Copyright © 2015 Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, and Genetics Society of China. Published by Elsevier Ltd. All rights reserved.

Magnetic nanoparticles to recover cellular organelles and study the time resolved nanoparticle-cell interactome throughout uptake.

PubMed

Bertoli, Filippo; Davies, Gemma-Louise; Monopoli, Marco P; Moloney, Micheal; Gun'ko, Yurii K; Salvati, Anna; Dawson, Kenneth A

2014-08-27

Nanoparticles in contact with cells and living organisms generate quite novel interactions at the interface between the nanoparticle surface and the surrounding biological environment. However, a detailed time resolved molecular level description of the evolving interactions as nanoparticles are internalized and trafficked within the cellular environment is still missing and will certainly be required for the emerging arena of nanoparticle-cell interactions to mature. In this paper promising methodologies to map out the time resolved nanoparticle-cell interactome for nanoparticle uptake are discussed. Thus silica coated magnetite nanoparticles are presented to cells and their magnetic properties used to isolate, in a time resolved manner, the organelles containing the nanoparticles. Characterization of the recovered fractions shows that different cell compartments are isolated at different times, in agreement with imaging results on nanoparticle intracellular location. Subsequently the internalized nanoparticles can be further isolated from the recovered organelles, allowing the study of the most tightly nanoparticle-bound biomolecules, analogous to the 'hard corona' that so far has mostly been characterized in extracellular environments. Preliminary data on the recovered nanoparticles suggest that significant portion of the original corona (derived from the serum in which particles are presented to the cells) is preserved as nanoparticles are trafficked through the cells. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A Case Study in Software Adaptation

DTIC Science & Technology

2002-01-01

1 A Case Study in Software Adaptation Giuseppe Valetto Telecom Italia Lab Via Reiss Romoli 274 10148, Turin, Italy +39 011 2288788...configuration of the service; monitoring of database connectivity from within the service; monitoring of crashes and shutdowns of IM servers; monitoring of...of the IM server all share a relational database and a common runtime state repository, which make up the backend tier, and allow replicas to

Elektronische Informationsdienste im Bildungswesen (Electronic Information Services in Education) Gesellschaft Information Bildung Conference (GIB) (2nd, Berlin, Germany, November 17-18, 1994).

ERIC Educational Resources Information Center

Diepold, Peter, Ed.; Rusch-Feja, Diann, Ed.

These papers on educational technology were presented in three workshops at the second annual conference of the Society of Information Education (GIB). Discussion includes electronic networks, CD-ROMs, and online databases in education, the quality of educational software, database services and instructional methods, and the use of the Internet in…

77 FR 12234 - Changes in Hydric Soils Database Selection Criteria

Federal Register 2010, 2011, 2012, 2013, 2014

2012-02-29

... Conservation Service [Docket No. NRCS-2011-0026] Changes in Hydric Soils Database Selection Criteria AGENCY... Changes to the National Soil Information System (NASIS) Database Selection Criteria for Hydric Soils of the United States. SUMMARY: The National Technical Committee for Hydric Soils (NTCHS) has updated the...

77 FR 39687 - Submission for OMB Review; Comment Request

Federal Register 2010, 2011, 2012, 2013, 2014

2012-07-05

..., Form, and OMB Number: Defense Sexual Assault Incident Database (DSAID); OMB Control Number 0704-0482... sexual assault data collected by the Military Services. This database shall be a centralized, case-level database for the uniform collection of data regarding incidence of sexual assaults involving persons...

A secure data outsourcing scheme based on Asmuth-Bloom secret sharing

NASA Astrophysics Data System (ADS)

Idris Muhammad, Yusuf; Kaiiali, Mustafa; Habbal, Adib; Wazan, A. S.; Sani Ilyasu, Auwal

2016-11-01

Data outsourcing is an emerging paradigm for data management in which a database is provided as a service by third-party service providers. One of the major benefits of offering database as a service is to provide organisations, which are unable to purchase expensive hardware and software to host their databases, with efficient data storage accessible online at a cheap rate. Despite that, several issues of data confidentiality, integrity, availability and efficient indexing of users' queries at the server side have to be addressed in the data outsourcing paradigm. Service providers have to guarantee that their clients' data are secured against internal (insider) and external attacks. This paper briefly analyses the existing indexing schemes in data outsourcing and highlights their advantages and disadvantages. Then, this paper proposes a secure data outsourcing scheme based on Asmuth-Bloom secret sharing which tries to address the issues in data outsourcing such as data confidentiality, availability and order preservation for efficient indexing.

Datacube Services in Action, Using Open Source and Open Standards

NASA Astrophysics Data System (ADS)

Baumann, P.; Misev, D.

2016-12-01

Array Databases comprise novel, promising technology for massive spatio-temporal datacubes, extending the SQL paradigm of "any query, anytime" to n-D arrays. On server side, such queries can be optimized, parallelized, and distributed based on partitioned array storage. The rasdaman ("raster data manager") system, which has pioneered Array Databases, is available in open source on www.rasdaman.org. Its declarative query language extends SQL with array operators which are optimized and parallelized on server side. The rasdaman engine, which is part of OSGeo Live, is mature and in operational use databases individually holding dozens of Terabytes. Further, the rasdaman concepts have strongly impacted international Big Data standards in the field, including the forthcoming MDA ("Multi-Dimensional Array") extension to ISO SQL, the OGC Web Coverage Service (WCS) and Web Coverage Processing Service (WCPS) standards, and the forthcoming INSPIRE WCS/WCPS; in both OGC and INSPIRE, OGC is WCS Core Reference Implementation. In our talk we present concepts, architecture, operational services, and standardization impact of open-source rasdaman, as well as experiences made.

DNA Data Bank of Japan: 30th anniversary.

PubMed

Kodama, Yuichi; Mashima, Jun; Kosuge, Takehide; Kaminuma, Eli; Ogasawara, Osamu; Okubo, Kousaku; Nakamura, Yasukazu; Takagi, Toshihisa

2018-01-04

The DNA Data Bank of Japan (DDBJ) Center (http://www.ddbj.nig.ac.jp) has been providing public data services for 30 years since 1987. We are collecting nucleotide sequence data and associated biological information from researchers as a member of the International Nucleotide Sequence Database Collaboration (INSDC), in collaboration with the US National Center for Biotechnology Information and the European Bioinformatics Institute. The DDBJ Center also services the Japanese Genotype-phenotype Archive (JGA) with the National Bioscience Database Center to collect genotype and phenotype data of human individuals. Here, we outline our database activities for INSDC and JGA over the past year, and introduce submission, retrieval and analysis services running on our supercomputer system and their recent developments. Furthermore, we highlight our responses to the amended Japanese rules for the protection of personal information and the launch of the DDBJ Group Cloud service for sharing pre-publication data among research groups. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

The IAGOS information system

NASA Astrophysics Data System (ADS)

Boulanger, Damien; Gautron, Benoit; Schultz, Martin; Brötz, Björn; Rauthe-Schöch, Armin; Thouret, Valérie

2015-04-01

IAGOS (In-service Aircraft for a Global Observing System) aims at the provision of long-term, frequent, regular, accurate, and spatially resolved in situ observations of the atmospheric composition. IAGOS observation systems are deployed on a fleet of commercial aircraft. The IAGOS database is an essential part of the global atmospheric monitoring network. Data access is handled by open access policy based on the submission of research requests which are reviewed by the PIs. The IAGOS database (http://www.iagos.fr, damien.boulanger@obs-mip.fr) is part of the French atmospheric chemistry data centre Ether (CNES and CNRS). In the framework of the IGAS project (IAGOS for Copernicus Atmospheric Service) interoperability with international portals or other databases is implemented in order to improve IAGOS data discovery. The IGAS data network is composed of three data centres: the IAGOS database in Toulouse including IAGOS-core data and IAGOS-CARIBIC (Civil Aircraft for the Regular Investigation of the Atmosphere Based on an Instrument Container) data since January 2015; the HALO research aircraft database at DLR (https://halo-db.pa.op.dlr.de); and the MACC data centre in Jülich (http://join.iek.fz-juelich.de). The MACC (Monitoring Atmospheric Composition and Climate) project is a prominent user of the IGAS data network. In June 2015 a new version of the IAGOS database will be released providing improved services such as download in NetCDF or NASA Ames formats; graphical tools (maps, scatter plots, etc.); standardized metadata (ISO 19115) and a better users management. The link with the MACC data centre, through JOIN (Jülich OWS Interface), will allow to combine model outputs with IAGOS data for intercomparison. The interoperability within the IGAS data network, implemented thanks to many web services, will improve the functionalities of the web interfaces of each data centre.

Biological age as a health index for mortality and major age-related disease incidence in Koreans: National Health Insurance Service – Health screening 11-year follow-up study

PubMed Central

Kang, Young Gon; Suh, Eunkyung; Lee, Jae-woo; Kim, Dong Wook; Cho, Kyung Hee; Bae, Chul-Young

2018-01-01

Purpose A comprehensive health index is needed to measure an individual’s overall health and aging status and predict the risk of death and age-related disease incidence, and evaluate the effect of a health management program. The purpose of this study is to demonstrate the validity of estimated biological age (BA) in relation to all-cause mortality and age-related disease incidence based on National Sample Cohort database. Patients and methods This study was based on National Sample Cohort database of the National Health Insurance Service – Eligibility database and the National Health Insurance Service – Medical and Health Examination database of the year 2002 through 2013. BA model was developed based on the National Health Insurance Service – National Sample Cohort (NHIS – NSC) database and Cox proportional hazard analysis was done for mortality and major age-related disease incidence. Results For every 1 year increase of the calculated BA and chronological age difference, the hazard ratio for mortality significantly increased by 1.6% (1.5% in men and 2.0% in women) and also for hypertension, diabetes mellitus, heart disease, stroke, and cancer incidence by 2.5%, 4.2%, 1.3%, 1.6%, and 0.4%, respectively (p<0.001). Conclusion Estimated BA by the developed BA model based on NHIS – NSC database is expected to be used not only as an index for assessing health and aging status and predicting mortality and major age-related disease incidence, but can also be applied to various health care fields. PMID:29593385