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Sample records for interactome predicts spatiotemporal

  1. PTIR: Predicted Tomato Interactome Resource.

    PubMed

    Yue, Junyang; Xu, Wei; Ban, Rongjun; Huang, Shengxiong; Miao, Min; Tang, Xiaofeng; Liu, Guoqing; Liu, Yongsheng

    2016-01-01

    Protein-protein interactions (PPIs) are involved in almost all biological processes and form the basis of the entire interactomics systems of living organisms. Identification and characterization of these interactions are fundamental to elucidating the molecular mechanisms of signal transduction and metabolic pathways at both the cellular and systemic levels. Although a number of experimental and computational studies have been performed on model organisms, the studies exploring and investigating PPIs in tomatoes remain lacking. Here, we developed a Predicted Tomato Interactome Resource (PTIR), based on experimentally determined orthologous interactions in six model organisms. The reliability of individual PPIs was also evaluated by shared gene ontology (GO) terms, co-evolution, co-expression, co-localization and available domain-domain interactions (DDIs). Currently, the PTIR covers 357,946 non-redundant PPIs among 10,626 proteins, including 12,291 high-confidence, 226,553 medium-confidence, and 119,102 low-confidence interactions. These interactions are expected to cover 30.6% of the entire tomato proteome and possess a reasonable distribution. In addition, ten randomly selected PPIs were verified using yeast two-hybrid (Y2H) screening or a bimolecular fluorescence complementation (BiFC) assay. The PTIR was constructed and implemented as a dedicated database and is available at http://bdg.hfut.edu.cn/ptir/index.html without registration. PMID:27121261

  2. PTIR: Predicted Tomato Interactome Resource

    PubMed Central

    Yue, Junyang; Xu, Wei; Ban, Rongjun; Huang, Shengxiong; Miao, Min; Tang, Xiaofeng; Liu, Guoqing; Liu, Yongsheng

    2016-01-01

    Protein-protein interactions (PPIs) are involved in almost all biological processes and form the basis of the entire interactomics systems of living organisms. Identification and characterization of these interactions are fundamental to elucidating the molecular mechanisms of signal transduction and metabolic pathways at both the cellular and systemic levels. Although a number of experimental and computational studies have been performed on model organisms, the studies exploring and investigating PPIs in tomatoes remain lacking. Here, we developed a Predicted Tomato Interactome Resource (PTIR), based on experimentally determined orthologous interactions in six model organisms. The reliability of individual PPIs was also evaluated by shared gene ontology (GO) terms, co-evolution, co-expression, co-localization and available domain-domain interactions (DDIs). Currently, the PTIR covers 357,946 non-redundant PPIs among 10,626 proteins, including 12,291 high-confidence, 226,553 medium-confidence, and 119,102 low-confidence interactions. These interactions are expected to cover 30.6% of the entire tomato proteome and possess a reasonable distribution. In addition, ten randomly selected PPIs were verified using yeast two-hybrid (Y2H) screening or a bimolecular fluorescence complementation (BiFC) assay. The PTIR was constructed and implemented as a dedicated database and is available at http://bdg.hfut.edu.cn/ptir/index.html without registration. PMID:27121261

  3. Computational prediction of the human-microbial oral interactome

    PubMed Central

    2014-01-01

    Background The oral cavity is a complex ecosystem where human chemical compounds coexist with a particular microbiota. However, shifts in the normal composition of this microbiota may result in the onset of oral ailments, such as periodontitis and dental caries. In addition, it is known that the microbial colonization of the oral cavity is mediated by protein-protein interactions (PPIs) between the host and microorganisms. Nevertheless, this kind of PPIs is still largely undisclosed. To elucidate these interactions, we have created a computational prediction method that allows us to obtain a first model of the Human-Microbial oral interactome. Results We collected high-quality experimental PPIs from five major human databases. The obtained PPIs were used to create our positive dataset and, indirectly, our negative dataset. The positive and negative datasets were merged and used for training and validation of a naïve Bayes classifier. For the final prediction model, we used an ensemble methodology combining five distinct PPI prediction techniques, namely: literature mining, primary protein sequences, orthologous profiles, biological process similarity, and domain interactions. Performance evaluation of our method revealed an area under the ROC-curve (AUC) value greater than 0.926, supporting our primary hypothesis, as no single set of features reached an AUC greater than 0.877. After subjecting our dataset to the prediction model, the classified result was filtered for very high confidence PPIs (probability ≥ 1-10−7), leading to a set of 46,579 PPIs to be further explored. Conclusions We believe this dataset holds not only important pathways involved in the onset of infectious oral diseases, but also potential drug-targets and biomarkers. The dataset used for training and validation, the predictions obtained and the network final network are available at http://bioinformatics.ua.pt/software/oralint. PMID:24576332

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

    PubMed Central

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

    2015-01-01

    ABSTRACT 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. IMPORTANCE 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. PMID:25986902

  5. Prediction and comparison of Salmonella-human and Salmonella-Arabidopsis interactomes

    PubMed Central

    Schleker, Sylvia; Garcia-Garcia, Javier

    2011-01-01

    Salmonellosis caused by Salmonella bacteria is a food-borne disease and worldwide health threat causing millions of infections and thousands of deaths every year. This pathogen infects an usually broad range of host organisms including human and plants. A better understanding of the mechanisms of communication between Salmonella and its hosts requires identifying the interactions between Salmonella and host proteins. Protein-protein interactions (PPIs) are the fundamental building blocks of communication. Here we utilize the prediction platform BIANA to obtain the putative Salmonella-human and Salmonella-Arabidopsis interactomes based on sequence and domain similarity to known PPIs. A gold standard list of Salmonella-host PPIs served to validate the quality of the human model. 24,726 and 10,926 PPIs comprising interactions between 38 and 33 Salmonella effectors and virulence factors with 9,740 human and 4,676 Arabidopsis proteins, respectively, were predicted. Putative hub proteins could be identified and parallels between the two interactomes were discovered. This approach can provide insight into possible biological functions of so far uncharacterized proteins. The predicted interactions are available via a web interface which allows filtering of the database according to parameters provided by the user to narrow down the list of suspected interactions. The interactions are available via a webinterface at http://sbi.imim.es/web/SHIPREC.php PMID:22589098

  6. 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

  7. Mapping Plant Interactomes Using Literature Curated and Predicted ProteinProtein Interaction Data Sets[W

    PubMed Central

    Lee, KiYoung; Thorneycroft, David; Achuthan, Premanand; Hermjakob, Henning; Ideker, Trey

    2010-01-01

    Most cellular processes are enabled by cohorts of interacting proteins that form dynamic networks within the plant proteome. The study of these networks can provide insight into protein function and provide new avenues for research. This article informs the plant science community of the currently available sources of protein interaction data and discusses how they can be useful to researchers. Using our recently curated IntAct Arabidopsis thaliana proteinprotein interaction data set as an example, we discuss potentials and limitations of the plant interactomes generated to date. In addition, we present our efforts to add value to the interaction data by using them to seed a proteome-wide map of predicted protein subcellular locations. PMID:20371643

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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 ...

  9. Spatiotemporal Patterns and Predictability of Cyberattacks

    PubMed Central

    Chen, Yu-Zhong; Huang, Zi-Gang; Xu, Shouhuai; Lai, Ying-Cheng

    2015-01-01

    A relatively unexplored issue in cybersecurity science and engineering is whether there exist intrinsic patterns of cyberattacks. Conventional wisdom favors absence of such patterns due to the overwhelming complexity of the modern cyberspace. Surprisingly, through a detailed analysis of an extensive data set that records the time-dependent frequencies of attacks over a relatively wide range of consecutive IP addresses, we successfully uncover intrinsic spatiotemporal patterns underlying cyberattacks, where the term “spatio” refers to the IP address space. In particular, we focus on analyzing macroscopic properties of the attack traffic flows and identify two main patterns with distinct spatiotemporal characteristics: deterministic and stochastic. Strikingly, there are very few sets of major attackers committing almost all the attacks, since their attack “fingerprints” and target selection scheme can be unequivocally identified according to the very limited number of unique spatiotemporal characteristics, each of which only exists on a consecutive IP region and differs significantly from the others. We utilize a number of quantitative measures, including the flux-fluctuation law, the Markov state transition probability matrix, and predictability measures, to characterize the attack patterns in a comprehensive manner. A general finding is that the attack patterns possess high degrees of predictability, potentially paving the way to anticipating and, consequently, mitigating or even preventing large-scale cyberattacks using macroscopic approaches. PMID:25992837

  10. Spatiotemporal patterns and predictability of cyberattacks.

    PubMed

    Chen, Yu-Zhong; Huang, Zi-Gang; Xu, Shouhuai; Lai, Ying-Cheng

    2015-01-01

    A relatively unexplored issue in cybersecurity science and engineering is whether there exist intrinsic patterns of cyberattacks. Conventional wisdom favors absence of such patterns due to the overwhelming complexity of the modern cyberspace. Surprisingly, through a detailed analysis of an extensive data set that records the time-dependent frequencies of attacks over a relatively wide range of consecutive IP addresses, we successfully uncover intrinsic spatiotemporal patterns underlying cyberattacks, where the term "spatio" refers to the IP address space. In particular, we focus on analyzing macroscopic properties of the attack traffic flows and identify two main patterns with distinct spatiotemporal characteristics: deterministic and stochastic. Strikingly, there are very few sets of major attackers committing almost all the attacks, since their attack "fingerprints" and target selection scheme can be unequivocally identified according to the very limited number of unique spatiotemporal characteristics, each of which only exists on a consecutive IP region and differs significantly from the others. We utilize a number of quantitative measures, including the flux-fluctuation law, the Markov state transition probability matrix, and predictability measures, to characterize the attack patterns in a comprehensive manner. A general finding is that the attack patterns possess high degrees of predictability, potentially paving the way to anticipating and, consequently, mitigating or even preventing large-scale cyberattacks using macroscopic approaches. PMID:25992837

  11. Predicting interactome network perturbations in human cancer: application to gene fusions in acute lymphoblastic leukemia

    PubMed Central

    Hajingabo, Leon Juvenal; Daakour, Sarah; Martin, Maud; Grausenburger, Reinhard; Panzer-Grümayer, Renate; Dequiedt, Franck; Simonis, Nicolas; Twizere, Jean-Claude

    2014-01-01

    Genomic variations such as point mutations and gene fusions are directly or indirectly associated with human diseases. They are recognized as diagnostic, prognostic markers and therapeutic targets. However, predicting the functional effect of these genetic alterations beyond affected genes and their products is challenging because diseased phenotypes are likely dependent of complex molecular interaction networks. Using as models three different chromosomal translocations—ETV6-RUNX1 (TEL-AML1), BCR-ABL1, and TCF3-PBX1 (E2A-PBX1)—frequently found in precursor-B-cell acute lymphoblastic leukemia (preB-ALL), we develop an approach to extract perturbed molecular interactions from gene expression changes. We show that the MYC and JunD transcriptional circuits are specifically deregulated after ETV6-RUNX1 and TCF3-PBX1 gene fusions, respectively. We also identified the bulk mRNA NXF1-dependent machinery as a direct target for the TCF3-PBX1 fusion protein. Through a novel approach combining gene expression and interactome data analysis, we provide new insight into TCF3-PBX1 and ETV6-RUNX1 acute lymphoblastic leukemia. PMID:25273558

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

    PubMed Central

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

    2014-01-01

    Background For the purpose of diagnosis, psychopathology can be represented as categories of mental disorder, symptom dimensions or symptom networks. Also, psychopathology can be assessed at different levels of temporal resolution (monthly episodes, daily fluctuating symptoms, momentary fluctuating mental states). We tested the diagnostic value, in terms of prediction of treatment needs, of the combination of symptom networks and momentary assessment level. Method Fifty-seven patients with a psychotic disorder participated in an ESM study, capturing psychotic experiences, emotions and circumstances at 10 semi-random moments in the flow of daily life over a period of 6 days. Symptoms were assessed by interview with the Positive and Negative Syndrome Scale (PANSS); treatment needs were assessed using the Camberwell Assessment of Need (CAN). Results Psychotic symptoms assessed with the PANSS (Clinical Psychotic Symptoms) were strongly associated with psychotic experiences assessed with ESM (Momentary Psychotic Experiences). However, the degree to which Momentary Psychotic Experiences manifested as Clinical Psychotic Symptoms was determined by level of momentary negative affect (higher levels increasing probability of Momentary Psychotic Experiences manifesting as Clinical Psychotic Symptoms), momentary positive affect (higher levels decreasing probability of Clinical Psychotic Symptoms), greater persistence of Momentary Psychotic Experiences (persistence predicting increased probability of Clinical Psychotic Symptoms) and momentary environmental stress associated with events and activities (higher levels increasing probability of Clinical Psychotic Symptoms). Similarly, the degree to which momentary visual or auditory hallucinations manifested as Clinical Psychotic Symptoms was strongly contingent on the level of accompanying momentary paranoid delusional ideation. Momentary Psychotic Experiences were associated with CAN unmet treatment needs, over and above PANSS measures of psychopathology, similarly moderated by momentary interactions with emotions and context. Conclusion The results suggest that psychopathology, represented as an interactome at the momentary level of temporal resolution, is informative in diagnosing clinical needs, over and above traditional symptom measures. PMID:24466189

  13. 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

  14. DDI-CPI, a server that predicts drug-drug interactions through implementing the chemical-protein interactome.

    PubMed

    Luo, Heng; Zhang, Ping; Huang, Hui; Huang, Jialiang; Kao, Emily; Shi, Leming; He, Lin; Yang, Lun

    2014-07-01

    Drug-drug interactions (DDIs) may cause serious side-effects that draw great attention from both academia and industry. Since some DDIs are mediated by unexpected drug-human protein interactions, it is reasonable to analyze the chemical-protein interactome (CPI) profiles of the drugs to predict their DDIs. Here we introduce the DDI-CPI server, which can make real-time DDI predictions based only on molecular structure. When the user submits a molecule, the server will dock user's molecule across 611 human proteins, generating a CPI profile that can be used as a feature vector for the pre-constructed prediction model. It can suggest potential DDIs between the user's molecule and our library of 2515 drug molecules. In cross-validation and independent validation, the server achieved an AUC greater than 0.85. Additionally, by investigating the CPI profiles of predicted DDI, users can explore the PK/PD proteins that might be involved in a particular DDI. A 3D visualization of the drug-protein interaction will be provided as well. The DDI-CPI is freely accessible at http://cpi.bio-x.cn/ddi/. PMID:24875476

  15. Prediction and analysis of the protein interactome in Pseudomonas aeruginosa to enable network-based drug target selection.

    PubMed

    Zhang, Minlu; Su, Shengchang; Bhatnagar, Raj K; Hassett, Daniel J; Lu, Long J

    2012-01-01

    Pseudomonas aeruginosa (PA) is a ubiquitous opportunistic pathogen that is capable of causing highly problematic, chronic infections in cystic fibrosis and chronic obstructive pulmonary disease patients. With the increased prevalence of multi-drug resistant PA, the conventional "one gene, one drug, one disease" paradigm is losing effectiveness. Network pharmacology, on the other hand, may hold the promise of discovering new drug targets to treat a variety of PA infections. However, given the urgent need for novel drug target discovery, a PA protein-protein interaction (PPI) network of high accuracy and coverage, has not yet been constructed. In this study, we predicted a genome-scale PPI network of PA by integrating various genomic features of PA proteins/genes by a machine learning-based approach. A total of 54,107 interactions covering 4,181 proteins in PA were predicted. A high-confidence network combining predicted high-confidence interactions, a reference set and verified interactions that consist of 3,343 proteins and 19,416 potential interactions was further assembled and analyzed. The predicted interactome network from this study is the first large-scale PPI network in PA with significant coverage and high accuracy. Subsequent analysis, including validations based on existing small-scale PPI data and the network structure comparison with other model organisms, shows the validity of the predicted PPI network. Potential drug targets were identified and prioritized based on their essentiality and topological importance in the high-confidence network. Host-pathogen protein interactions between human and PA were further extracted and analyzed. In addition, case studies were performed on protein interactions regarding anti-sigma factor MucA, negative periplasmic alginate regulator MucB, and the transcriptional regulator RhlR. A web server to access the predicted PPI dataset is available at http://research.cchmc.org/PPIdatabase/. PMID:22848443

  16. The interactome challenge

    PubMed Central

    2015-01-01

    The properties of living cells are mediated by a huge number of ever-changing interactions of their component macromolecules forming living machines; collectively, these are termed the interactome. Pathogenic alterations in interactomes mechanistically underlie diseases. Therefore, there exists an essential need for much better tools to reveal and dissect interactomes. This need is only now beginning to be met. PMID:26572620

  17. Spatiotemporal Signatures of Lexical-Semantic Prediction.

    PubMed

    Lau, Ellen F; Weber, Kirsten; Gramfort, Alexandre; Hämäläinen, Matti S; Kuperberg, Gina R

    2016-04-01

    Although there is broad agreement that top-down expectations can facilitate lexical-semantic processing, the mechanisms driving these effects are still unclear. In particular, while previous electroencephalography (EEG) research has demonstrated a reduction in the N400 response to words in a supportive context, it is often challenging to dissociate facilitation due to bottom-up spreading activation from facilitation due to top-down expectations. The goal of the current study was to specifically determine the cortical areas associated with facilitation due to top-down prediction, using magnetoencephalography (MEG) recordings supplemented by EEG and functional magnetic resonance imaging (fMRI) in a semantic priming paradigm. In order to modulate expectation processes while holding context constant, we manipulated the proportion of related pairs across 2 blocks (10 and 50% related). Event-related potential results demonstrated a larger N400 reduction when a related word was predicted, and MEG source localization of activity in this time-window (350-450 ms) localized the differential responses to left anterior temporal cortex. fMRI data from the same participants support the MEG localization, showing contextual facilitation in left anterior superior temporal gyrus for the high expectation block only. Together, these results provide strong evidence that facilitatory effects of lexical-semantic prediction on the electrophysiological response 350-450 ms postonset reflect modulation of activity in left anterior temporal cortex. PMID:25316341

  18. In silico prediction of physical protein interactions and characterization of interactome orphans.

    PubMed

    Kotlyar, Max; Pastrello, Chiara; Pivetta, Flavia; Lo Sardo, Alessandra; Cumbaa, Christian; Li, Han; Naranian, Taline; Niu, Yun; Ding, Zhiyong; Vafaee, Fatemeh; Broackes-Carter, Fiona; Petschnigg, Julia; Mills, Gordon B; Jurisicova, Andrea; Stagljar, Igor; Maestro, Roberta; Jurisica, Igor

    2015-01-01

    Protein-protein interactions (PPIs) are useful for understanding signaling cascades, predicting protein function, associating proteins with disease and fathoming drug mechanism of action. Currently, only ∼ 10% of human PPIs may be known, and about one-third of human proteins have no known interactions. We introduce FpClass, a data mining-based method for proteome-wide PPI prediction. At an estimated false discovery rate of 60%, we predicted 250,498 PPIs among 10,531 human proteins; 10,647 PPIs involved 1,089 proteins without known interactions. We experimentally tested 233 high- and medium-confidence predictions and validated 137 interactions, including seven novel putative interactors of the tumor suppressor p53. Compared to previous PPI prediction methods, FpClass achieved better agreement with experimentally detected PPIs. We provide an online database of annotated PPI predictions (http://ophid.utoronto.ca/fpclass/) and the prediction software (http://www.cs.utoronto.ca/~juris/data/fpclass/). PMID:25402006

  19. Combinatorial binding predicts spatio-temporal cis-regulatory activity.

    PubMed

    Zinzen, Robert P; Girardot, Charles; Gagneur, Julien; Braun, Martina; Furlong, Eileen E M

    2009-11-01

    Development requires the establishment of precise patterns of gene expression, which are primarily controlled by transcription factors binding to cis-regulatory modules. Although transcription factor occupancy can now be identified at genome-wide scales, decoding this regulatory landscape remains a daunting challenge. Here we used a novel approach to predict spatio-temporal cis-regulatory activity based only on in vivo transcription factor binding and enhancer activity data. We generated a high-resolution atlas of cis-regulatory modules describing their temporal and combinatorial occupancy during Drosophila mesoderm development. The binding profiles of cis-regulatory modules with characterized expression were used to train support vector machines to predict five spatio-temporal expression patterns. In vivo transgenic reporter assays demonstrate the high accuracy of these predictions and reveal an unanticipated plasticity in transcription factor binding leading to similar expression. This data-driven approach does not require previous knowledge of transcription factor sequence affinity, function or expression, making it widely applicable. PMID:19890324

  20. Prediction of Spatiotemporal Patterns of Neural Activity from Pairwise Correlations

    SciTech Connect

    Marre, O.; El Boustani, S.; Fregnac, Y.; Destexhe, A.

    2009-04-03

    We designed a model-based analysis to predict the occurrence of population patterns in distributed spiking activity. Using a maximum entropy principle with a Markovian assumption, we obtain a model that accounts for both spatial and temporal pairwise correlations among neurons. This model is tested on data generated with a Glauber spin-glass system and is shown to correctly predict the occurrence probabilities of spatiotemporal patterns significantly better than Ising models only based on spatial correlations. This increase of predictability was also observed on experimental data recorded in parietal cortex during slow-wave sleep. This approach can also be used to generate surrogates that reproduce the spatial and temporal correlations of a given data set.

  1. Interactome: gateway into systems biology.

    PubMed

    Cusick, Michael E; Klitgord, Niels; Vidal, Marc; Hill, David E

    2005-10-15

    Protein-protein interactions are fundamental to all biological processes, and a comprehensive determination of all protein-protein interactions that can take place in an organism provides a framework for understanding biology as an integrated system. The availability of genome-scale sets of cloned open reading frames has facilitated systematic efforts at creating proteome-scale data sets of protein-protein interactions, which are represented as complex networks or 'interactome' maps. Protein-protein interaction mapping projects that follow stringent criteria, coupled with experimental validation in orthogonal systems, provide high-confidence data sets immanently useful for interrogating developmental and disease mechanisms at a system level as well as elucidating individual protein function and interactome network topology. Although far from complete, currently available maps provide insight into how biochemical properties of proteins and protein complexes are integrated into biological systems. Such maps are also a useful resource to predict the function(s) of thousands of genes. PMID:16162640

  2. Spatio-temporal prediction and inference by V1 neurons.

    PubMed

    Guo, Kun; Robertson, Robert G; Pulgarin, Maribel; Nevado, Angel; Panzeri, Stefano; Thiele, Alexander; Young, Malcolm P

    2007-08-01

    In normal vision, visual scenes are predictable, as they are both spatially and temporally redundant. Evidence suggests that the visual system may use the spatio-temporal regularities of the external world, available in the retinal signal, to extract information from the visual environment and better reconstruct current and future stimuli. We studied this by recording neuronal responses of primary visual cortex (area V1) in anaesthetized and paralysed macaques during the presentation of dynamic sequences of bars, in which spatio-temporal regularities and local information were independently manipulated. Most V1 neurons were significantly modulated by events prior to and distant from stimulation of their classical receptive fields (CRFs); many were more strongly tuned to prior and distant events than they were to CRFs bars; and several showed tuning to prior information without any CRF stimulation. Hence, V1 neurons do not simply analyse local contours, but impute local features to the visual world, on the basis of prior knowledge of a visual world in which useful information can be distributed widely in space and time. PMID:17714195

  3. Virtual Interactomics of Proteins from Biochemical Standpoint

    PubMed Central

    Kubrycht, Jaroslav; Sigler, Karel; Souček, Pavel

    2012-01-01

    Virtual interactomics represents a rapidly developing scientific area on the boundary line of bioinformatics and interactomics. Protein-related virtual interactomics then comprises instrumental tools for prediction, simulation, and networking of the majority of interactions important for structural and individual reproduction, differentiation, recognition, signaling, regulation, and metabolic pathways of cells and organisms. Here, we describe the main areas of virtual protein interactomics, that is, structurally based comparative analysis and prediction of functionally important interacting sites, mimotope-assisted and combined epitope prediction, molecular (protein) docking studies, and investigation of protein interaction networks. Detailed information about some interesting methodological approaches and online accessible programs or databases is displayed in our tables. Considerable part of the text deals with the searches for common conserved or functionally convergent protein regions and subgraphs of conserved interaction networks, new outstanding trends and clinically interesting results. In agreement with the presented data and relationships, virtual interactomic tools improve our scientific knowledge, help us to formulate working hypotheses, and they frequently also mediate variously important in silico simulations. PMID:22928109

  4. Ozone Concentration Prediction via Spatiotemporal Autoregressive Model With Exogenous Variables

    NASA Astrophysics Data System (ADS)

    Kamoun, W.; Senoussi, R.

    2009-04-01

    Forecast of environmental variables are nowadays of main concern for public health or agricultural management. In this context a large literature is devoted to spatio-temporal modelling of these variables using different statistical approaches. However, most of studies ignored the potential contribution of local (e.g. meteorological and/or geographical) covariables as well as the dynamical characteristics of observations. In this study, we present a spatiotemporal short term forecasting model for ozone concentration based on regularly observed covariables in predefined geographical sites. Our driving system simply combines a multidimensional second order autoregressive structured process with a linear regression model over influent exogenous factors and reads as follows: ?2 ?q j Z (t) = A (&,cedil;D )- [ ?iZ(t- i)]+ B (&,cedil;D )- [ ?jX (t)]+ ?(t) i=1 j=1 Z(t)=(Z1(t),?,Zn(t)) represents the vector of ozone concentration at time t of the n geographical sites, whereas Xj(t)=(X1j(t),?,Xnj(t)) denotes the jth exogenous variable observed over these sites. The nxn matrix functions A and B account for the spatial relationships between sites through the inter site distance matrix D and a vector parameter &.cedil; Multidimensional white noise ? is assumed to be Gaussian and spatially correlated but temporally independent. A covariance structure of Z that takes account of noise spatial dependences is deduced under a stationary hypothesis and then included in the likelihood function. Statistical model and estimation procedure: Contrarily to the widely used choice of a {0,1}-valued neighbour matrix A, we put forward two more natural choices of exponential or power decay. Moreover, the model revealed enough stable to readily accommodate the crude observations without the usual tedious and somewhat arbitrarily variable transformations. Data set and preliminary analysis: In our case, ozone variable represents here the daily maximum ozone concentration recorded in n=42 stations during the year 2005 within a south region in France, covering an area of approximately 10565 km2. Meteorological covariates are the daily maxima of temperature, wind speed, daily maxima of humidity and atmospheric pressure. Actually, the meteorological factors are not recorded in ozone monitoring sites and thus preliminary interpolation techniques were used and compared subsequently (Gaussian conditional simulation, ordinary kriging or kriging with external drift). Concluding remarks: From the statistical point of view, both simulation study and data analysis showed a fairly robust behaviour of estimation procedures. In both cases, the analysis of residuals proved a significant improvement of error prediction within this framework. From the environmental point of view, the ability of accounting for pertinent local and dynamical meteorological covariates clearly provided a useful tool in prediction methods. Bib [1]: Pfeifer.P.E; Deutsh.S.J. (1980) "A Three-Stage Iterative Procedure for Space-Time Modelling." Technometrics 22: 35-47. Bib [2]: Raffaella Giacomini and Cliff W.J.Granger 2002 - 07 "Aggregation of Space-Time Process" Departement of Economics, University of California, San Diego.

  5. SePreSA: a server for the prediction of populations susceptible to serious adverse drug reactions implementing the methodology of a chemical-protein interactome.

    PubMed

    Yang, Lun; Luo, Heng; Chen, Jian; Xing, Qinghe; He, Lin

    2009-07-01

    Serious adverse drug reactions (SADRs) are caused by unexpected drug-human protein interactions, and some polymorphisms within binding pockets make the population carrying these polymorphisms susceptible to SADR. Predicting which populations are likely to be susceptible to SADR will not only strengthen drug safety, but will also assist enterprises to adjust R&D and marketing strategies. Making such predictions has recently been facilitated by the introduction of a web server named SePreSA. The server has a comprehensive collection of the structural models of nearly all the well known SADR targets. Once a drug molecule is submitted, the scale of its potential interaction with multi-SADR targets is calculated using the DOCK program. The server utilizes a 2-directional Z-transformation scoring algorithm, which computes the relative drug-protein interaction strength based on the docking-score matrix of a chemical-protein interactome, thus achieve greater accuracy in prioritizing SADR targets than simply using dock scoring functions. The server also suggests the binding pattern of the lowest docking score through 3D visualization, by highlighting and visualizing amino acid residues involved in the binding on the customer's browser. Polymorphism information for different populations for each of the interactive residues will be displayed, helping users to deduce the population-specific susceptibility of their drug molecule. The server is freely available at http://SePreSA.Bio-X.cn/. PMID:19417066

  6. 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

  7. On spatiotemporal series analysis and its application to predict the regional short term climate process

    NASA Astrophysics Data System (ADS)

    Wang, Geli; Yang, Peicai; Lü, Daren

    2004-04-01

    Based on the theory of reconstructing state space, a technique for spatiotemporal series prediction is presented. By means of this technique and NCEP/NCAR data of the monthly mean geopotential height anomaly of the 500-hPa isobaric surface in the Northern Hemisphere, a regional prediction experiment is also carried out. If using the correlation coefficient R between the observed field and the prediction field to measure the prediction accuracy, the averaged R given by 48 prediction samples reaches 21%, which corresponds to the current prediction level for the short range climate process.

  8. Next Place Prediction Based on Spatiotemporal Pattern Mining of Mobile Device Logs

    PubMed Central

    Lee, Sungjun; Lim, Junseok; Park, Jonghun; Kim, Kwanho

    2016-01-01

    Due to the recent explosive growth of location-aware services based on mobile devices, predicting the next places of a user is of increasing importance to enable proactive information services. In this paper, we introduce a data-driven framework that aims to predict the user’s next places using his/her past visiting patterns analyzed from mobile device logs. Specifically, the notion of the spatiotemporal-periodic (STP) pattern is proposed to capture the visits with spatiotemporal periodicity by focusing on a detail level of location for each individual. Subsequently, we present algorithms that extract the STP patterns from a user’s past visiting behaviors and predict the next places based on the patterns. The experiment results obtained by using a real-world dataset show that the proposed methods are more effective in predicting the user’s next places than the previous approaches considered in most cases. PMID:26805850

  9. Next Place Prediction Based on Spatiotemporal Pattern Mining of Mobile Device Logs.

    PubMed

    Lee, Sungjun; Lim, Junseok; Park, Jonghun; Kim, Kwanho

    2016-01-01

    Due to the recent explosive growth of location-aware services based on mobile devices, predicting the next places of a user is of increasing importance to enable proactive information services. In this paper, we introduce a data-driven framework that aims to predict the user's next places using his/her past visiting patterns analyzed from mobile device logs. Specifically, the notion of the spatiotemporal-periodic (STP) pattern is proposed to capture the visits with spatiotemporal periodicity by focusing on a detail level of location for each individual. Subsequently, we present algorithms that extract the STP patterns from a user's past visiting behaviors and predict the next places based on the patterns. The experiment results obtained by using a real-world dataset show that the proposed methods are more effective in predicting the user's next places than the previous approaches considered in most cases. PMID:26805850

  10. Spatiotemporal prediction of fine particulate matter during the 2008 northern California wildfires using machine learning.

    PubMed

    Reid, Colleen E; Jerrett, Michael; Petersen, Maya L; Pfister, Gabriele G; Morefield, Philip E; Tager, Ira B; Raffuse, Sean M; Balmes, John R

    2015-03-17

    Estimating population exposure to particulate matter during wildfires can be difficult because of insufficient monitoring data to capture the spatiotemporal variability of smoke plumes. Chemical transport models (CTMs) and satellite retrievals provide spatiotemporal data that may be useful in predicting PM2.5 during wildfires. We estimated PM2.5 concentrations during the 2008 northern California wildfires using 10-fold cross-validation (CV) to select an optimal prediction model from a set of 11 statistical algorithms and 29 predictor variables. The variables included CTM output, three measures of satellite aerosol optical depth, distance to the nearest fires, meteorological data, and land use, traffic, spatial location, and temporal characteristics. The generalized boosting model (GBM) with 29 predictor variables had the lowest CV root mean squared error and a CV-R2 of 0.803. The most important predictor variable was the Geostationary Operational Environmental Satellite Aerosol/Smoke Product (GASP) Aerosol Optical Depth (AOD), followed by the CTM output and distance to the nearest fire cluster. Parsimonious models with various combinations of fewer variables also predicted PM2.5 well. Using machine learning algorithms to combine spatiotemporal data from satellites and CTMs can reliably predict PM2.5 concentrations during a major wildfire event. PMID:25648639

  11. A data mining based approach to predict spatiotemporal changes in satellite images

    NASA Astrophysics Data System (ADS)

    Boulila, W.; Farah, I. R.; Ettabaa, K. Saheb; Solaiman, B.; Ghézala, H. Ben

    2011-06-01

    The interpretation of remotely sensed images in a spatiotemporal context is becoming a valuable research topic. However, the constant growth of data volume in remote sensing imaging makes reaching conclusions based on collected data a challenging task. Recently, data mining appears to be a promising research field leading to several interesting discoveries in various areas such as marketing, surveillance, fraud detection and scientific discovery. By integrating data mining and image interpretation techniques, accurate and relevant information (i.e. functional relation between observed parcels and a set of informational contents) can be automatically elicited. This study presents a new approach to predict spatiotemporal changes in satellite image databases. The proposed method exploits fuzzy sets and data mining concepts to build predictions and decisions for several remote sensing fields. It takes into account imperfections related to the spatiotemporal mining process in order to provide more accurate and reliable information about land cover changes in satellite images. The proposed approach is validated using SPOT images representing the Saint-Denis region, capital of Reunion Island. Results show good performances of the proposed framework in predicting change for the urban zone.

  12. Predictive Spatiotemporal Manipulation of Signaling Perturbations Using Optogenetics.

    PubMed

    Valon, Leo; Etoc, Fred; Remorino, Amanda; di Pietro, Florencia; Morin, Xavier; Dahan, Maxime; Coppey, Mathieu

    2015-11-01

    Recently developed optogenetic methods promise to revolutionize cell biology by allowing signaling perturbations to be controlled in space and time with light. However, a quantitative analysis of the relationship between a custom-defined illumination pattern and the resulting signaling perturbation is lacking. Here, we characterize the biophysical processes governing the localized recruitment of the Cryptochrome CRY2 to its membrane-anchored CIBN partner. We develop a quantitative framework and present simple procedures that enable predictive manipulation of protein distributions on the plasma membrane with a spatial resolution of 5 ?m. We show that protein gradients of desired levels can be established in a few tens of seconds and then steadily maintained. These protein gradients can be entirely relocalized in a few minutes. We apply our approach to the control of the Cdc42 Rho GTPase activity. By inducing strong localized signaling perturbation, we are able to monitor the initiation of cell polarity and migration with a remarkable reproducibility despite cell-to-cell variability. PMID:26536256

  13. Proactive Spatiotemporal Resource Allocation and Predictive Visual Analytics for Community Policing and Law Enforcement.

    PubMed

    Malik, Abish; Maciejewski, Ross; Towers, Sherry; McCullough, Sean; Ebert, David S

    2014-12-01

    In this paper, we present a visual analytics approach that provides decision makers with a proactive and predictive environment in order to assist them in making effective resource allocation and deployment decisions. The challenges involved with such predictive analytics processes include end-users' understanding, and the application of the underlying statistical algorithms at the right spatiotemporal granularity levels so that good prediction estimates can be established. In our approach, we provide analysts with a suite of natural scale templates and methods that enable them to focus and drill down to appropriate geospatial and temporal resolution levels. Our forecasting technique is based on the Seasonal Trend decomposition based on Loess (STL) method, which we apply in a spatiotemporal visual analytics context to provide analysts with predicted levels of future activity. We also present a novel kernel density estimation technique we have developed, in which the prediction process is influenced by the spatial correlation of recent incidents at nearby locations. We demonstrate our techniques by applying our methodology to Criminal, Traffic and Civil (CTC) incident datasets. PMID:26356900

  14. Spatiotemporal activity patterns of rat cortical neurons predict responses in a conditioned task

    PubMed Central

    Villa, Alessandro E. P.; Tetko, Igor V.; Hyland, Brian; Najem, Abdellatif

    1999-01-01

    Precise and repeated spike-train timings within and across neurons define spatiotemporal patterns of activity. Although the existence of these patterns in the brain is well established in several species, there has been no direct evidence of their influence on behavioral output. To address this question, up to 15 neurons were recorded simultaneously in the auditory cortex of freely moving rats while animals waited for acoustic cues in a Go/NoGo task. A total of 235 significant patterns were detected during this interval from an analysis of 13 hr of recording involving over 1 million spikes. Of particular interest were 129 (55%) patterns that were significantly associated with the type of response the animal made later, independent of whether the response was that prompted by the cue because the response occurred later and the cue was chosen randomly. Of these behavior-predicting patterns, half (59/129) were associated with an enhanced tendency to go in response to the stimulus, and for 11 patterns of this subset, trials including the pattern were followed by significantly faster reaction time than those lacking the pattern. The remaining behavior-predicting patterns were associated with an enhanced NoGo tendency. Overall mean discharge rates did not vary across trials. Hence, these data demonstrate that particular spatiotemporal patterns predict future behavioral responses. Such presignal activity could form templates for extracting specific sensory information, motor programs prespecifying preference for a particular act, and/or some intermediate, associative brain process. PMID:9927701

  15. Spatio-Temporal Variation and Prediction of Ischemic Heart Disease Hospitalizations in Shenzhen, China

    PubMed Central

    Wang, Yanxia; Du, Qingyun; Ren, Fu; Liang, Shi; Lin, De-nan; Tian, Qin; Chen, Yan; Li, Jia-jia

    2014-01-01

    Ischemic heart disease (IHD) is a leading cause of death worldwide. Urban public health and medical management in Shenzhen, an international city in the developing country of China, is challenged by an increasing burden of IHD. This study analyzed the spatio-temporal variation of IHD hospital admissions from 2003 to 2012 utilizing spatial statistics, spatial analysis, and space-time scan statistics. The spatial statistics and spatial analysis measured the incidence rate (hospital admissions per 1,000 residents) and the standardized rate (the observed cases standardized by the expected cases) of IHD at the district level to determine the spatio-temporal distribution and identify patterns of change. The space-time scan statistics was used to identify spatio-temporal clusters of IHD hospital admissions at the district level. The other objective of this study was to forecast the IHD hospital admissions over the next three years (2013–2015) to predict the IHD incidence rates and the varying burdens of IHD-related medical services among the districts in Shenzhen. The results show that the highest hospital admissions, incidence rates, and standardized rates of IHD are in Futian. From 2003 to 2012, the IHD hospital admissions exhibited similar mean centers and directional distributions, with a slight increase in admissions toward the north in accordance with the movement of the total population. The incidence rates of IHD exhibited a gradual increase from 2003 to 2012 for all districts in Shenzhen, which may be the result of the rapid development of the economy and the increasing traffic pollution. In addition, some neighboring areas exhibited similar temporal change patterns, which were also detected by the spatio-temporal cluster analysis. Futian and Dapeng would have the highest and the lowest hospital admissions, respectively, although these districts have the highest incidence rates among all of the districts from 2013 to 2015 based on the prediction using the GM (1,1). In addition, the combined analysis of the prediction of IHD hospital admissions and the general hospital distributions shows that Pingshan and Longgang might experience the most serious burden of IHD hospital services in the near future, although Futian would still have the greatest number and the highest incidence rate of hospital admissions for IHD. PMID:24806191

  16. Spatio-temporal variation and prediction of ischemic heart disease hospitalizations in Shenzhen, China.

    PubMed

    Wang, Yanxia; Du, Qingyun; Ren, Fu; Liang, Shi; Lin, De-nan; Tian, Qin; Chen, Yan; Li, Jia-jia

    2014-05-01

    Ischemic heart disease (IHD) is a leading cause of death worldwide. Urban public health and medical management in Shenzhen, an international city in the developing country of China, is challenged by an increasing burden of IHD. This study analyzed the spatio-temporal variation of IHD hospital admissions from 2003 to 2012 utilizing spatial statistics, spatial analysis, and space-time scan statistics. The spatial statistics and spatial analysis measured the incidence rate (hospital admissions per 1,000 residents) and the standardized rate (the observed cases standardized by the expected cases) of IHD at the district level to determine the spatio-temporal distribution and identify patterns of change. The space-time scan statistics was used to identify spatio-temporal clusters of IHD hospital admissions at the district level. The other objective of this study was to forecast the IHD hospital admissions over the next three years (2013-2015) to predict the IHD incidence rates and the varying burdens of IHD-related medical services among the districts in Shenzhen. The results show that the highest hospital admissions, incidence rates, and standardized rates of IHD are in Futian. From 2003 to 2012, the IHD hospital admissions exhibited similar mean centers and directional distributions, with a slight increase in admissions toward the north in accordance with the movement of the total population. The incidence rates of IHD exhibited a gradual increase from 2003 to 2012 for all districts in Shenzhen, which may be the result of the rapid development of the economy and the increasing traffic pollution. In addition, some neighboring areas exhibited similar temporal change patterns, which were also detected by the spatio-temporal cluster analysis. Futian and Dapeng would have the highest and the lowest hospital admissions, respectively, although these districts have the highest incidence rates among all of the districts from 2013 to 2015 based on the prediction using the GM (1,1). In addition, the combined analysis of the prediction of IHD hospital admissions and the general hospital distributions shows that Pingshan and Longgang might experience the most serious burden of IHD hospital services in the near future, although Futian would still have the greatest number and the highest incidence rate of hospital admissions for IHD. PMID:24806191

  17. A climate-based spatiotemporal prediction for dengue fever epidemics: a case study in southern Taiwan

    NASA Astrophysics Data System (ADS)

    Yu, H.-L.; Yang, S.-J.; Lin, Y.-C.

    2012-04-01

    Dengue Fever (DF) has been identified by the World Health organization (WHO) as one of the most serious vector-borne infectious diseases in tropical and sub-tropical areas. DF has been one of the most important epidemics in Taiwan which occur annually especially in southern Taiwan during summer and autumn. Most DF studies have focused mainly on temporal DF patterns and its close association with climatic covariates, whereas few studies have investigated the spatial DF patterns (spatial dependence and clustering) and composite space-time effects of the DF epidemics. The present study proposes a spatio-temporal DF prediction approach based on stochastic Bayesian Maximum Entropy (BME) analysis. Core and site-specific knowledge bases are considered, including climate and health datasets under conditions of uncertainty, space-time dependence functions, and a Poisson regression model of climatic variables contributing to DF occurrences in southern Taiwan during 2007, when the highest number of DF cases was recorded in the history of Taiwan epidemics (over 2000). The obtained results show that the DF outbreaks in the study area are highly influenced by climatic conditions. Furthermore, the analysis can provide the required "one-week-ahead" outbreak warnings based on spatio-temporal predictions of DF distributions. Therefore, the proposed analysis can provide the Taiwan Disease Control Agency with a valuable tool to timely identify, control, and even efficiently prevent DF spreading across space-time.

  18. Microclimate Data Improve Predictions of Insect Abundance Models Based on Calibrated Spatiotemporal Temperatures.

    PubMed

    Rebaudo, François; Faye, Emile; Dangles, Olivier

    2016-01-01

    A large body of literature has recently recognized the role of microclimates in controlling the physiology and ecology of species, yet the relevance of fine-scale climatic data for modeling species performance and distribution remains a matter of debate. Using a 6-year monitoring of three potato moth species, major crop pests in the tropical Andes, we asked whether the spatiotemporal resolution of temperature data affect the predictions of models of moth performance and distribution. For this, we used three different climatic data sets: (i) the WorldClim dataset (global dataset), (ii) air temperature recorded using data loggers (weather station dataset), and (iii) air crop canopy temperature (microclimate dataset). We developed a statistical procedure to calibrate all datasets to monthly and yearly variation in temperatures, while keeping both spatial and temporal variances (air monthly temperature at 1 km² for the WorldClim dataset, air hourly temperature for the weather station, and air minute temperature over 250 m radius disks for the microclimate dataset). Then, we computed pest performances based on these three datasets. Results for temperature ranging from 9 to 11°C revealed discrepancies in the simulation outputs in both survival and development rates depending on the spatiotemporal resolution of the temperature dataset. Temperature and simulated pest performances were then combined into multiple linear regression models to compare predicted vs. field data. We used an additional set of study sites to test the ability of the results of our model to be extrapolated over larger scales. Results showed that the model implemented with microclimatic data best predicted observed pest abundances for our study sites, but was less accurate than the global dataset model when performed at larger scales. Our simulations therefore stress the importance to consider different temperature datasets depending on the issue to be solved in order to accurately predict species abundances. In conclusion, keeping in mind that the mismatch between the size of organisms and the scale at which climate data are collected and modeled remains a key issue, temperature dataset selection should be balanced by the desired output spatiotemporal scale for better predicting pest dynamics and developing efficient pest management strategies. PMID:27148077

  19. Microclimate Data Improve Predictions of Insect Abundance Models Based on Calibrated Spatiotemporal Temperatures

    PubMed Central

    Rebaudo, François; Faye, Emile; Dangles, Olivier

    2016-01-01

    A large body of literature has recently recognized the role of microclimates in controlling the physiology and ecology of species, yet the relevance of fine-scale climatic data for modeling species performance and distribution remains a matter of debate. Using a 6-year monitoring of three potato moth species, major crop pests in the tropical Andes, we asked whether the spatiotemporal resolution of temperature data affect the predictions of models of moth performance and distribution. For this, we used three different climatic data sets: (i) the WorldClim dataset (global dataset), (ii) air temperature recorded using data loggers (weather station dataset), and (iii) air crop canopy temperature (microclimate dataset). We developed a statistical procedure to calibrate all datasets to monthly and yearly variation in temperatures, while keeping both spatial and temporal variances (air monthly temperature at 1 km² for the WorldClim dataset, air hourly temperature for the weather station, and air minute temperature over 250 m radius disks for the microclimate dataset). Then, we computed pest performances based on these three datasets. Results for temperature ranging from 9 to 11°C revealed discrepancies in the simulation outputs in both survival and development rates depending on the spatiotemporal resolution of the temperature dataset. Temperature and simulated pest performances were then combined into multiple linear regression models to compare predicted vs. field data. We used an additional set of study sites to test the ability of the results of our model to be extrapolated over larger scales. Results showed that the model implemented with microclimatic data best predicted observed pest abundances for our study sites, but was less accurate than the global dataset model when performed at larger scales. Our simulations therefore stress the importance to consider different temperature datasets depending on the issue to be solved in order to accurately predict species abundances. In conclusion, keeping in mind that the mismatch between the size of organisms and the scale at which climate data are collected and modeled remains a key issue, temperature dataset selection should be balanced by the desired output spatiotemporal scale for better predicting pest dynamics and developing efficient pest management strategies. PMID:27148077

  20. The Effect of Rainfall Measurement Technique and Its Spatiotemporal Resolution on Discharge Predictions in the Netherlands

    NASA Astrophysics Data System (ADS)

    Uijlenhoet, R.; Brauer, C.; Overeem, A.; Sassi, M.; Rios Gaona, M. F.

    2014-12-01

    Several rainfall measurement techniques are available for hydrological applications, each with its own spatial and temporal resolution. We investigated the effect of these spatiotemporal resolutions on discharge simulations in lowland catchments by forcing a novel rainfall-runoff model (WALRUS) with rainfall data from gauges, radars and microwave links. The hydrological model used for this analysis is the recently developed Wageningen Lowland Runoff Simulator (WALRUS). WALRUS is a rainfall-runoff model accounting for hydrological processes relevant to areas with shallow groundwater (e.g. groundwater-surface water feedback). Here, we used WALRUS for case studies in a freely draining lowland catchment and a polder with controlled water levels. We used rain gauge networks with automatic (hourly resolution but low spatial density) and manual gauges (high spatial density but daily resolution). Operational (real-time) and climatological (gauge-adjusted) C-band radar products and country-wide rainfall maps derived from microwave link data from a cellular telecommunication network were also used. Discharges simulated with these different inputs were compared to observations. We also investigated the effect of spatiotemporal resolution with a high-resolution X-band radar data set for catchments with different sizes. Uncertainty in rainfall forcing is a major source of uncertainty in discharge predictions, both with lumped and with distributed models. For lumped rainfall-runoff models, the main source of input uncertainty is associated with the way in which (effective) catchment-average rainfall is estimated. When catchments are divided into sub-catchments, rainfall spatial variability can become more important, especially during convective rainfall events, leading to spatially varying catchment wetness and spatially varying contribution of quick flow routes. Improving rainfall measurements and their spatiotemporal resolution can improve the performance of rainfall-runoff models, indicating their potential for reducing flood damage through real-time control.

  1. Spatiotemporal models for predicting high pollen concentration level of Corylus, Alnus, and Betula.

    PubMed

    Nowosad, Jakub

    2016-06-01

    Corylus, Alnus, and Betula trees are among the most important sources of allergic pollen in the temperate zone of the Northern Hemisphere and have a large impact on the quality of life and productivity of allergy sufferers. Therefore, it is important to predict high pollen concentrations, both in time and space. The aim of this study was to create and evaluate spatiotemporal models for predicting high Corylus, Alnus, and Betula pollen concentration levels, based on gridded meteorological data. Aerobiological monitoring was carried out in 11 cities in Poland and gathered, depending on the site, between 2 and 16 years of measurements. According to the first allergy symptoms during exposure, a high pollen count level was established for each taxon. An optimizing probability threshold technique was used for mitigation of the problem of imbalance in the pollen concentration levels. For each taxon, the model was built using a random forest method. The study revealed the possibility of moderately reliable prediction of Corylus and highly reliable prediction of Alnus and Betula high pollen concentration levels, using preprocessed gridded meteorological data. Cumulative growing degree days and potential evaporation proved to be two of the most important predictor variables in the models. The final models predicted not only for single locations but also for continuous areas. Furthermore, the proposed modeling framework could be used to predict high pollen concentrations of Corylus, Alnus, Betula, and other taxa, and in other countries. PMID:26487352

  2. Spatiotemporal models for predicting high pollen concentration level of Corylus, Alnus, and Betula

    NASA Astrophysics Data System (ADS)

    Nowosad, Jakub

    2015-10-01

    Corylus, Alnus, and Betula trees are among the most important sources of allergic pollen in the temperate zone of the Northern Hemisphere and have a large impact on the quality of life and productivity of allergy sufferers. Therefore, it is important to predict high pollen concentrations, both in time and space. The aim of this study was to create and evaluate spatiotemporal models for predicting high Corylus, Alnus, and Betula pollen concentration levels, based on gridded meteorological data. Aerobiological monitoring was carried out in 11 cities in Poland and gathered, depending on the site, between 2 and 16 years of measurements. According to the first allergy symptoms during exposure, a high pollen count level was established for each taxon. An optimizing probability threshold technique was used for mitigation of the problem of imbalance in the pollen concentration levels. For each taxon, the model was built using a random forest method. The study revealed the possibility of moderately reliable prediction of Corylus and highly reliable prediction of Alnus and Betula high pollen concentration levels, using preprocessed gridded meteorological data. Cumulative growing degree days and potential evaporation proved to be two of the most important predictor variables in the models. The final models predicted not only for single locations but also for continuous areas. Furthermore, the proposed modeling framework could be used to predict high pollen concentrations of Corylus, Alnus, Betula, and other taxa, and in other countries.

  3. A Multi-Scale Modeling Framework for Individualized, Spatiotemporal Prediction of Drug Effects and Toxicological Risk

    PubMed Central

    Diaz Ochoa, Juan G.; Bucher, Joachim; Pry, Alexandre R. R.; Zaldivar Comenges, Jos M.; Niklas, Jens; Mauch, Klaus

    2013-01-01

    In this study, we focus on a novel multi-scale modeling approach for spatiotemporal prediction of the distribution of substances and resulting hepatotoxicity by combining cellular models, a 2D liver model, and whole body model. As a case study, we focused on predicting human hepatotoxicity upon treatment with acetaminophen based on in vitro toxicity data and potential inter-individual variability in gene expression and enzyme activities. By aggregating mechanistic, genome-based in silico cells to a novel 2D liver model and eventually to a whole body model, we predicted pharmacokinetic properties, metabolism, and the onset of hepatotoxicity in an in silico patient. Depending on the concentration of acetaminophen in the liver and the accumulation of toxic metabolites, cell integrity in the liver as a function of space and time as well as changes in the elimination rate of substances were estimated. We show that the variations in elimination rates also influence the distribution of acetaminophen and its metabolites in the whole body. Our results are in agreement with experimental results. What is more, the integrated model also predicted variations in drug toxicity depending on alterations of metabolic enzyme activities. Variations in enzyme activity, in turn, reflect genetic characteristics or diseases of individuals. In conclusion, this framework presents an important basis for efficiently integrating inter-individual variability data into models, paving the way for personalized or stratified predictions of drug toxicity and efficacy. PMID:23346056

  4. Curating the innate immunity interactome

    PubMed Central

    2010-01-01

    Background The innate immune response is the first line of defence against invading pathogens and is regulated by complex signalling and transcriptional networks. Systems biology approaches promise to shed new light on the regulation of innate immunity through the analysis and modelling of these networks. A key initial step in this process is the contextual cataloguing of the components of this system and the molecular interactions that comprise these networks. InnateDB (http://www.innatedb.com) is a molecular interaction and pathway database developed to facilitate systems-level analyses of innate immunity. Results Here, we describe the InnateDB curation project, which is manually annotating the human and mouse innate immunity interactome in rich contextual detail, and present our novel curation software system, which has been developed to ensure interactions are curated in a highly accurate and data-standards compliant manner. To date, over 13,000 interactions (protein, DNA and RNA) have been curated from the biomedical literature. Here, we present data, illustrating how InnateDB curation of the innate immunity interactome has greatly enhanced network and pathway annotation available for systems-level analysis and discuss the challenges that face such curation efforts. Significantly, we provide several lines of evidence that analysis of the innate immunity interactome has the potential to identify novel signalling, transcriptional and post-transcriptional regulators of innate immunity. Additionally, these analyses also provide insight into the cross-talk between innate immunity pathways and other biological processes, such as adaptive immunity, cancer and diabetes, and intriguingly, suggests links to other pathways, which as yet, have not been implicated in the innate immune response. Conclusions In summary, curation of the InnateDB interactome provides a wealth of information to enable systems-level analysis of innate immunity. PMID:20727158

  5. Neurobiological Mechanisms Behind the Spatiotemporal Illusions of Awareness Used for Advocating Prediction or Postdiction

    PubMed Central

    Bachmann, Talis

    2013-01-01

    The fact that it takes time for the brain to process information from the changing environment underlies many experimental phenomena of awareness of spatiotemporal events, including a number of astonishing illusions. These phenomena have been explained from the predictive and postdictive theoretical perspectives. Here I describe the most extensively studied phenomena in order to see how well the two perspectives can explain them. Next, the neurobiological perceptual retouch mechanism of producing stimulation awareness is characterized and its work in causing the listed illusions is described. A perspective on how brain mechanisms of conscious perception produce the phenomena supportive of the postdictive view is presented in this article. At the same time, some of the phenomena cannot be explained by the traditional postdictive account, but can be interpreted from the perceptual retouch theory perspective. PMID:23293625

  6. Predicted spatio-temporal dynamics of radiocesium deposited onto forests following the Fukushima nuclear accident

    PubMed Central

    Hashimoto, Shoji; Matsuura, Toshiya; Nanko, Kazuki; Linkov, Igor; Shaw, George; Kaneko, Shinji

    2013-01-01

    The majority of the area contaminated by the Fukushima Dai-ichi nuclear power plant accident is covered by forest. To facilitate effective countermeasure strategies to mitigate forest contamination, we simulated the spatio-temporal dynamics of radiocesium deposited into Japanese forest ecosystems in 2011 using a model that was developed after the Chernobyl accident in 1986. The simulation revealed that the radiocesium inventories in tree and soil surface organic layer components drop rapidly during the first two years after the fallout. Over a period of one to two years, the radiocesium is predicted to move from the tree and surface organic soil to the mineral soil, which eventually becomes the largest radiocesium reservoir within forest ecosystems. Although the uncertainty of our simulations should be considered, the results provide a basis for understanding and anticipating the future dynamics of radiocesium in Japanese forests following the Fukushima accident. PMID:23995073

  7. An adaptive mode-driven spatiotemporal motion vector prediction for wavelet video coding

    NASA Astrophysics Data System (ADS)

    Zhao, Fan; Liu, Guizhong; Qi, Yong

    2010-07-01

    The three-dimensional subband/wavelet codecs use 5/3 filters rather than Haar filters for the motion compensation temporal filtering (MCTF) to improve the coding gain. In order to curb the increased motion vector rate, an adaptive motion mode driven spatiotemporal motion vector prediction (AMDST-MVP) scheme is proposed. First, by making use of the direction histograms of four motion vector fields resulting from the initial spatial motion vector prediction (SMVP), the motion mode of the current GOP is determined according to whether the fast or complex motion exists in the current GOP. Then the GOP-level MVP scheme is thereby determined by either the S-MVP or the AMDST-MVP, namely, AMDST-MVP is the combination of S-MVP and temporal-MVP (T-MVP). If the latter is adopted, the motion vector difference (MVD) between the neighboring MV fields and the S-MVP resulting MV of the current block is employed to decide whether or not the MV of co-located block in the previous frame is used for prediction the current block. Experimental results show that AMDST-MVP not only can improve the coding efficiency but also reduce the number of computation complexity.

  8. An online spatio-temporal prediction model for dengue fever epidemic in Kaohsiung,Taiwan

    NASA Astrophysics Data System (ADS)

    Cheng, Ming-Hung; Yu, Hwa-Lung; Angulo, Jose; Christakos, George

    2013-04-01

    Dengue Fever (DF) is one of the most serious vector-borne infectious diseases in tropical and subtropical areas. DF epidemics occur in Taiwan annually especially during summer and fall seasons. Kaohsiung city has been one of the major DF hotspots in decades. The emergence and re-emergence of the DF epidemic is complex and can be influenced by various factors including space-time dynamics of human and vector populations and virus serotypes as well as the associated uncertainties. This study integrates a stochastic space-time "Susceptible-Infected-Recovered" model under Bayesian maximum entropy framework (BME-SIR) to perform real-time prediction of disease diffusion across space-time. The proposed model is applied for spatiotemporal prediction of the DF epidemic at Kaohsiung city during 2002 when the historical series of high DF cases was recorded. The online prediction by BME-SIR model updates the parameters of SIR model and infected cases across districts over time. Results show that the proposed model is rigorous to initial guess of unknown model parameters, i.e. transmission and recovery rates, which can depend upon the virus serotypes and various human interventions. This study shows that spatial diffusion can be well characterized by BME-SIR model, especially at the district surrounding the disease outbreak locations. The prediction performance at DF hotspots, i.e. Cianjhen and Sanmin, can be degraded due to the implementation of various disease control strategies during the epidemics. The proposed online disease prediction BME-SIR model can provide the governmental agency with a valuable reference to timely identify, control, and efficiently prevent DF spread across space-time.

  9. Electron Transfer Interactome of Cytochrome c

    PubMed Central

    Volkov, Alexander N.; van Nuland, Nico A. J.

    2012-01-01

    Lying at the heart of many vital cellular processes such as photosynthesis and respiration, biological electron transfer (ET) is mediated by transient interactions among proteins that recognize multiple binding partners. Accurate description of the ET complexes – necessary for a comprehensive understanding of the cellular signaling and metabolism – is compounded by their short lifetimes and pronounced binding promiscuity. Here, we used a computational approach relying solely on the steric properties of the individual proteins to predict the ET properties of protein complexes constituting the functional interactome of the eukaryotic cytochrome c (Cc). Cc is a small, soluble, highly-conserved electron carrier protein that coordinates the electron flow among different redox partners. In eukaryotes, Cc is a key component of the mitochondrial respiratory chain, where it shuttles electrons between its reductase and oxidase, and an essential electron donor or acceptor in a number of other redox systems. Starting from the structures of individual proteins, we performed extensive conformational sampling of the ET-competent binding geometries, which allowed mapping out functional epitopes in the Cc complexes, estimating the upper limit of the ET rate in a given system, assessing ET properties of different binding stoichiometries, and gauging the effect of domain mobility on the intermolecular ET. The resulting picture of the Cc interactome 1) reveals that most ET-competent binding geometries are located in electrostatically favorable regions, 2) indicates that the ET can take place from more than one protein-protein orientation, and 3) suggests that protein dynamics within redox complexes, and not the electron tunneling event itself, is the rate-limiting step in the intermolecular ET. Further, we show that the functional epitope size correlates with the extent of dynamics in the Cc complexes and thus can be used as a diagnostic tool for protein mobility. PMID:23236271

  10. 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

    2016-01-01

    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. PMID:27040163

  11. Geomagnetic imprinting predicts spatio-temporal variation in homing migration of pink and sockeye salmon.

    PubMed

    Putman, Nathan F; Jenkins, Erica S; Michielsens, Catherine G J; Noakes, David L G

    2014-10-01

    Animals navigate using a variety of sensory cues, but how each is weighted during different phases of movement (e.g. dispersal, foraging, homing) is controversial. Here, we examine the geomagnetic and olfactory imprinting hypotheses of natal homing with datasets that recorded variation in the migratory routes of sockeye (Oncorhynchus nerka) and pink (Oncorhynchus gorbuscha) salmon returning from the Pacific Ocean to the Fraser River, British Columbia. Drift of the magnetic field (i.e. geomagnetic imprinting) uniquely accounted for 23.2% and 44.0% of the variation in migration routes for sockeye and pink salmon, respectively. Ocean circulation (i.e. olfactory imprinting) predicted 6.1% and 0.1% of the variation in sockeye and pink migration routes, respectively. Sea surface temperature (a variable influencing salmon distribution but not navigation, directly) accounted for 13.0% of the variation in sockeye migration but was unrelated to pink migration. These findings suggest that geomagnetic navigation plays an important role in long-distance homing in salmon and that consideration of navigation mechanisms can aid in the management of migratory fishes by better predicting movement patterns. Finally, given the diversity of animals that use the Earth's magnetic field for navigation, geomagnetic drift may provide a unifying explanation for spatio-temporal variation in the movement patterns of many species. PMID:25056214

  12. Geomagnetic imprinting predicts spatio-temporal variation in homing migration of pink and sockeye salmon

    PubMed Central

    Putman, Nathan F.; Jenkins, Erica S.; Michielsens, Catherine G. J.; Noakes, David L. G.

    2014-01-01

    Animals navigate using a variety of sensory cues, but how each is weighted during different phases of movement (e.g. dispersal, foraging, homing) is controversial. Here, we examine the geomagnetic and olfactory imprinting hypotheses of natal homing with datasets that recorded variation in the migratory routes of sockeye (Oncorhynchus nerka) and pink (Oncorhynchus gorbuscha) salmon returning from the Pacific Ocean to the Fraser River, British Columbia. Drift of the magnetic field (i.e. geomagnetic imprinting) uniquely accounted for 23.2% and 44.0% of the variation in migration routes for sockeye and pink salmon, respectively. Ocean circulation (i.e. olfactory imprinting) predicted 6.1% and 0.1% of the variation in sockeye and pink migration routes, respectively. Sea surface temperature (a variable influencing salmon distribution but not navigation, directly) accounted for 13.0% of the variation in sockeye migration but was unrelated to pink migration. These findings suggest that geomagnetic navigation plays an important role in long-distance homing in salmon and that consideration of navigation mechanisms can aid in the management of migratory fishes by better predicting movement patterns. Finally, given the diversity of animals that use the Earth's magnetic field for navigation, geomagnetic drift may provide a unifying explanation for spatio-temporal variation in the movement patterns of many species. PMID:25056214

  13. Tumor site prediction using spatiotemporal detection of subclinical hyperemia in experimental photocarcinogenesis

    NASA Astrophysics Data System (ADS)

    Konger, Raymond L.; Xu, Zhengbin; Sahu, Ravi P.; Kim, Young L.

    2014-03-01

    We demonstrate that a spatial and temporal analysis of subclinical hyperemia reliably predicts specific areas at high risk for skin tumor development during photocarcinogenesis. To determine detailed spatiotemporal patterns of inflammatory angiogenesis foci in a relatively large area, we developed a mesoscopic (between microscopic and macroscopic) imaging approach. This method relies on our earlier finding that the combination of a spectral analysis of hemoglobin with diffuse-light-suppressed imaging can increase the image resolution, contrast and penetration depth to visualize microvasculature Hgb content in the large tissue area. In our recent study, SKH1 hairless albino mice were irradiated for 10 weeks with a carcinogen dose of UVB. Using our newly developed mesoscopic imaging methods, we imaged the mice over 20 - 30 weeks after stopping UVB, and excised hyperemic/non-hyperemic areas at several different timepoints. We show that persistent hyperemic foci can predict future tumor formation. In particular, our imaging approach allows us to assess the spatial and temporal extent of subclinical inflammatory foci, which in turn can predict sites of future overlying tumor formation. In addition, although COX-2 inhibitors are known to suppress skin cancer development in humans, it remains unclear whether the chemopreventive activity of COX-2 inhibitors are chiefly attributable to their anti-inflammatory effects. Our study provides evidence that subclinical subepithelial inflammatory foci occur prior to overt tumor formation, and that these areas are highly predictive for future tumor formation, that celecoxib's ability to suppress tumorigenesis is tightly linked to its ability to reduce the area of subclinical inflammatory foci.

  14. Organization of physical interactomes as uncovered by network schemas.

    PubMed

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

    2008-10-01

    Large-scale protein-protein interaction networks provide new opportunities for understanding cellular organization and functioning. We introduce network schemas to elucidate shared mechanisms within interactomes. Network schemas specify descriptions of proteins and the topology of interactions among them. We develop algorithms for systematically uncovering recurring, over-represented schemas in physical interaction networks. We apply our methods to the S. cerevisiae interactome, focusing on schemas consisting of proteins described via sequence motifs and molecular function annotations and interacting with one another in one of four basic network topologies. We identify hundreds of recurring and over-represented network schemas of various complexity, and demonstrate via graph-theoretic representations how more complex schemas are organized in terms of their lower-order constituents. The uncovered schemas span a wide range of cellular activities, with many signaling and transport related higher-order schemas. We establish the functional importance of the schemas by showing that they correspond to functionally cohesive sets of proteins, are enriched in the frequency with which they have instances in the H. sapiens interactome, and are useful for predicting protein function. Our findings suggest that network schemas are a powerful paradigm for organizing, interrogating, and annotating cellular networks. PMID:18949022

  15. Proteomic-Coupled-Network Analysis of T877A-Androgen Receptor Interactomes Can Predict Clinical Prostate Cancer Outcomes between White (Non-Hispanic) and African-American Groups

    PubMed Central

    Zaman, Naif; Giannopoulos, Paresa N.; Chowdhury, Shafinaz; Bonneil, Eric; Thibault, Pierre; Wang, Edwin; Trifiro, Mark; Paliouras, Miltiadis

    2014-01-01

    The androgen receptor (AR) remains an important contributor to the neoplastic evolution of prostate cancer (CaP). CaP progression is linked to several somatic AR mutational changes that endow upon the AR dramatic gain-of-function properties. One of the most common somatic mutations identified is Thr877-to-Ala (T877A), located in the ligand-binding domain, that results in a receptor capable of promiscuous binding and activation by a variety of steroid hormones and ligands including estrogens, progestins, glucocorticoids, and several anti-androgens. In an attempt to further define somatic mutated AR gain-of-function properties, as a consequence of its promiscuous ligand binding, we undertook a proteomic/network analysis approach to characterize the protein interactome of the mutant T877A-AR in LNCaP cells under eight different ligand-specific treatments (dihydrotestosterone, mibolerone, R1881, testosterone, estradiol, progesterone, dexamethasone, and cyproterone acetate). In extending the analysis of our multi-ligand complexes of the mutant T877A-AR we observed significant enrichment of specific complexes between normal and primary prostatic tumors, which were furthermore correlated with known clinical outcomes. Further analysis of certain mutant T877A-AR complexes showed specific population preferences distinguishing primary prostatic disease between white (non-Hispanic) vs. African-American males. Moreover, these cancer-related AR-protein complexes demonstrated predictive survival outcomes specific to CaP, and not for breast, lung, lymphoma or medulloblastoma cancers. Our study, by coupling data generated by our proteomics to network analysis of clinical samples, has helped to define real and novel biological pathways in complicated gain-of-function AR complex systems. PMID:25409505

  16. Modelling the Yeast Interactome

    PubMed Central

    Janjić, Vuk; Sharan, Roded; Pržulj, Nataša

    2014-01-01

    The topology behind biological interaction networks has been studied for over a decade. Yet, there is no definite agreement on the theoretical models which best describe protein-protein interaction (PPI) networks. Such models are critical to quantifying the significance of any empirical observation regarding those networks. Here, we perform a comprehensive analysis of yeast PPI networks in order to gain insights into their topology and its dependency on interaction-screening technology. We find that: (1) interaction-detection technology has little effect on the topology of PPI networks; (2) topology of these interaction networks differs in organisms with different cellular complexity (human and yeast); (3) clear topological difference is present between PPI networks, their functional sub-modules, and their inter-functional “linkers”; (4) high confidence PPI networks have more “geometrical” topology compared to predicted, incomplete, or noisy PPI networks; and (5) inter-functional “linker” proteins serve as mediators in signal transduction, transport, regulation and organisational cellular processes. PMID:24589662

  17. Virus-human cell interactomes.

    PubMed

    Tafforeau, Lionel; Rabourdin-Combe, Chantal; Lotteau, Vincent

    2012-01-01

    Using global approaches and high-throughput technologies in virology brings a new vision of the infections physiology and allows the identification of cellular factors, mandatory for viral life cycle, that could be targeted by original therapeutic agents. It opens perspectives for the treatment of viral infections by acting on cellular pathways that the virus must use for its own replication. Combining these new molecules with classical antiviral drugs and immunomodulators diversifies and enlarges the antiviral arsenal and contributes to fight drug resistance. Our laboratory and others are constructing virus-human interactomes to propose a comprehensive analysis of viral infection at the cellular level. Studying these infection maps, where the viral infection can be visualized as perturbation of the human protein-protein interaction network, and identifying the biological functions that are impaired by these perturbations may lead to discovery of new therapeutic targets. These virus-human interaction maps are constructed in a stringent yeast two-hybrid system by screening human cDNA libraries with viral proteins as bait and integrating interactions mined from literature and public databases. PMID:22218856

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

    PubMed Central

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

    2016-01-01

    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. PMID:26655848

  19. 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. PMID:26655848

  20. Serial interactome capture of the human cell nucleus

    PubMed Central

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

    2016-01-01

    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. PMID:27040163

  1. CircInteractome: A web tool for exploring circular RNAs and their interacting proteins and microRNAs.

    PubMed

    Dudekula, Dawood B; Panda, Amaresh C; Grammatikakis, Ioannis; De, Supriyo; Abdelmohsen, Kotb; Gorospe, Myriam

    2016-01-01

    Circular RNAs (circRNAs) are widely expressed in animal cells, but their biogenesis and functions are poorly understood. CircRNAs have been shown to act as sponges for miRNAs and may also potentially sponge RNA-binding proteins (RBPs) and are thus predicted to function as robust posttranscriptional regulators of gene expression. The joint analysis of large-scale transcriptome data coupled with computational analyses represents a powerful approach to elucidate possible biological roles of ribonucleoprotein (RNP) complexes. Here, we present a new web tool, CircInteractome (circRNA interactome), for mapping RBP- and miRNA-binding sites on human circRNAs. CircInteractome searches public circRNA, miRNA, and RBP databases to provide bioinformatic analyses of binding sites on circRNAs and additionally analyzes miRNA and RBP sites on junction and junction-flanking sequences. CircInteractome also allows the user the ability to (1) identify potential circRNAs which can act as RBP sponges, (2) design junction-spanning primers for specific detection of circRNAs of interest, (3) design siRNAs for circRNA silencing, and (4) identify potential internal ribosomal entry sites (IRES). In sum, the web tool CircInteractome, freely accessible at http://circinteractome.nia.nih.gov , facilitates the analysis of circRNAs and circRNP biology. PMID:26669964

  2. 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

  3. Air temperature suitability for Plasmodium falciparum malaria transmission in Africa 2000-2012: a high-resolution spatiotemporal prediction

    PubMed Central

    2014-01-01

    Background Temperature suitability for malaria transmission is a useful predictor variable for spatial models of malaria infection prevalence. Existing continental or global models, however, are synoptic in nature and so do not characterize inter-annual variability in seasonal patterns of temperature suitability, reducing their utility for predicting malaria risk. Methods A malaria Temperature Suitability Index (TSI) was created by first modeling minimum and maximum air temperature with an eight-day temporal resolution from gap-filled MODerate Resolution Imaging Spectroradiometer (MODIS) daytime and night-time Land Surface Temperature (LST) datasets. An improved version of an existing biological model for malaria temperature suitability was then applied to the resulting temperature information for a 13-year data series. The mechanism underlying this biological model is simulation of emergent mosquito cohorts on a two-hour time-step and tracking of each cohort throughout its life to quantify the impact air temperature has on both mosquito survival and sporozoite development. Results The results of this research consist of 154 monthly raster surfaces that characterize spatiotemporal patterns in TSI across Africa from April 2000 through December 2012 at a 1 km spatial resolution. Generalized TSI patterns were as expected, with consistently high values in equatorial rain forests, seasonally variable values in tropical savannas (wet and dry) and montane areas, and low values in arid, subtropical regions. Comparisons with synoptic approaches demonstrated the additional information available within the dynamic TSI dataset that is lost in equivalent synoptic products derived from long-term monthly averages. Conclusions The dynamic TSI dataset presented here provides a new product with far richer spatial and temporal information than any other presently available for Africa. As spatiotemporal malaria modeling endeavors evolve, dynamic predictor variables such as the malaria temperature suitability data developed here will be essential for the rational assessment of changing patterns of malaria risk. PMID:24886586

  4. Predicting the spatiotemporal expression of local and referred acute muscle pain in individual subjects.

    PubMed

    Rubin, Troy K; Lake, Sally; van der Kooi, Saskia; Lucas, Nicholas P; Mahns, David A; Henderson, Luke A; Macefield, Vaughan G

    2012-11-01

    While current data suggest that all referred pain derives from common mechanisms of central sensitisation, there is a paucity of data directly comparing referral in different limbs. Does a common mechanism result in similar precepts of referral from similar stimuli in different limbs? We tested the hypothesis that, in a given subject, the incidence, intensity and spatiotemporal expression of referred pain are similar during the muscle pain induced by bolus intramuscular injection of hypertonic saline into flexor carpi radialis (FCR) and tibialis anterior (TA). We also tested the hypothesis that an increase in stimulus intensity causes a parallel increase in the incidence and intensity of local and referred pain, by comparing the responses to 5 and 10 % hypertonic saline in two groups of subjects. 29 subjects mapped areas of local and referred pain, rating intensities on a visual analogue scale every 30 s until the cessation of pain. Following an injection of 5 % hypertonic saline into TA, 86 % of subjects who had previously reported referred pain (or its absence) in the hand during FCR pain reported referred pain (or its absence) in the foot. Following an injection of the 10 % solution, 67 % of subjects reported a pattern in the lower limb that was the same as that seen in the upper limb. We conclude that the expression of referred pain is largely consistent in widely separated limb segments in individual subjects and is largely dependent on inter-subject differences. This may have implications for the development of chronic pain following an acute episode of pain. PMID:22926156

  5. Spatiotemporal Context Awareness for Urban Traffic Modeling and Prediction: Sparse Representation Based Variable Selection

    PubMed Central

    Yang, Su; Shi, Shixiong; Hu, Xiaobing; Wang, Minjie

    2015-01-01

    Spatial-temporal correlations among the data play an important role in traffic flow prediction. Correspondingly, traffic modeling and prediction based on big data analytics emerges due to the city-scale interactions among traffic flows. A new methodology based on sparse representation is proposed to reveal the spatial-temporal dependencies among traffic flows so as to simplify the correlations among traffic data for the prediction task at a given sensor. Three important findings are observed in the experiments: (1) Only traffic flows immediately prior to the present time affect the formation of current traffic flows, which implies the possibility to reduce the traditional high-order predictors into an 1-order model. (2) The spatial context relevant to a given prediction task is more complex than what is assumed to exist locally and can spread out to the whole city. (3) The spatial context varies with the target sensor undergoing prediction and enlarges with the increment of time lag for prediction. Because the scope of human mobility is subject to travel time, identifying the varying spatial context against time lag is crucial for prediction. Since sparse representation can capture the varying spatial context to adapt to the prediction task, it outperforms the traditional methods the inputs of which are confined as the data from a fixed number of nearby sensors. As the spatial-temporal context for any prediction task is fully detected from the traffic data in an automated manner, where no additional information regarding network topology is needed, it has good scalability to be applicable to large-scale networks. PMID:26496370

  6. Spatiotemporal Context Awareness for Urban Traffic Modeling and Prediction: Sparse Representation Based Variable Selection.

    PubMed

    Yang, Su; Shi, Shixiong; Hu, Xiaobing; Wang, Minjie

    2015-01-01

    Spatial-temporal correlations among the data play an important role in traffic flow prediction. Correspondingly, traffic modeling and prediction based on big data analytics emerges due to the city-scale interactions among traffic flows. A new methodology based on sparse representation is proposed to reveal the spatial-temporal dependencies among traffic flows so as to simplify the correlations among traffic data for the prediction task at a given sensor. Three important findings are observed in the experiments: (1) Only traffic flows immediately prior to the present time affect the formation of current traffic flows, which implies the possibility to reduce the traditional high-order predictors into an 1-order model. (2) The spatial context relevant to a given prediction task is more complex than what is assumed to exist locally and can spread out to the whole city. (3) The spatial context varies with the target sensor undergoing prediction and enlarges with the increment of time lag for prediction. Because the scope of human mobility is subject to travel time, identifying the varying spatial context against time lag is crucial for prediction. Since sparse representation can capture the varying spatial context to adapt to the prediction task, it outperforms the traditional methods the inputs of which are confined as the data from a fixed number of nearby sensors. As the spatial-temporal context for any prediction task is fully detected from the traffic data in an automated manner, where no additional information regarding network topology is needed, it has good scalability to be applicable to large-scale networks. PMID:26496370

  7. Using Optimality Principles to Predict Spatio-Temporal Patterns of Vegetation-Atmosphere Fluxes at Leaf to Global Scales

    NASA Astrophysics Data System (ADS)

    Tu, K. P.

    2008-12-01

    A predictive understanding of biological variation in space and time -- from spatial gradients of light within plant canopies, seasonal fluctuations in temperature and water availability during a growing season, to geographic variation in climate and soil nutrient availability across the land surface -- is a central but challenging goal in biospheric sciences. Functional attributes of vegetation, such as the capacities to exchange carbon, water and energy with the atmosphere, can be assessed based on thermodynamic and aerodynamic properties of the canopy-atmosphere system, however many of these properties cannot be directly measured at the global scale. In lieu of direct measurement, optimization methods based on simplifying theories of the underlying processes, including Maximum Entropy Production (MEP) and economic theories of plant carbon and water relations, are needed to provide sufficient constraint to estimate the required parameters. Using theories of functional coordination in which it is assumed that plants maintain a balance between the supply and demand of a variable (e.g. absorbed radiation, CO2, water) consistent with MEP in complex source-sink physiological systems, it is possible to predict spatial patterns of leaf photosynthetic capacity within plant canopies as well as their temporal variation throughout the growing season. When combined with satellite remote sensing observations of canopy light absorptance (fAPAR), these same theories can be used to predict seasonal variations in leaf and canopy photosynthesis and transpiration, and global spatio-temporal patterns of productivity and evapotranspiration. Predictions using this approach are consistent with observations at leaf to landscape scales based on leaf gas exchange and eddy covariance measurements in arctic to tropical ecosystems.

  8. An online spatiotemporal prediction model for dengue fever epidemic in Kaohsiung (Taiwan).

    PubMed

    Yu, Hwa-Lung; Angulo, José M; Cheng, Ming-Hung; Wu, Jiaping; Christakos, George

    2014-05-01

    The emergence and re-emergence of disease epidemics is a complex question that may be influenced by diverse factors, including the space-time dynamics of human populations, environmental conditions, and associated uncertainties. This study proposes a stochastic framework to integrate space-time dynamics in the form of a Susceptible-Infected-Recovered (SIR) model, together with uncertain disease observations, into a Bayesian maximum entropy (BME) framework. The resulting model (BME-SIR) can be used to predict space-time disease spread. Specifically, it was applied to obtain a space-time prediction of the dengue fever (DF) epidemic that took place in Kaohsiung City (Taiwan) during 2002. In implementing the model, the SIR parameters were continually updated and information on new cases of infection was incorporated. The results obtained show that the proposed model is rigorous to user-specified initial values of unknown model parameters, that is, transmission and recovery rates. In general, this model provides a good characterization of the spatial diffusion of the DF epidemic, especially in the city districts proximal to the location of the outbreak. Prediction performance may be affected by various factors, such as virus serotypes and human intervention, which can change the space-time dynamics of disease diffusion. The proposed BME-SIR disease prediction model can provide government agencies with a valuable reference for the timely identification, control, and prevention of DF spread in space and time. PMID:24615833

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

    PubMed Central

    Guo, Xianwu; Rodrguez-Prez, 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

  10. Toward the dynamic interactome: it's about time

    PubMed Central

    Singh, Mona; Slonim, Donna K.

    2010-01-01

    Dynamic molecular interactions play a central role in regulating the functioning of cells and organisms. The availability of experimentally determined large-scale cellular networks, along with other high-throughput experimental data sets that provide snapshots of biological systems at different times and conditions, is increasingly helpful in elucidating interaction dynamics. Here we review the beginnings of a new subfield within computational biology, one focused on the global inference and analysis of the dynamic interactome. This burgeoning research area, which entails a shift from static to dynamic network analysis, promises to be a major step forward in our ability to model and reason about cellular function and behavior. PMID:20061351

  11. Spatiotemporal variability and predictability of Normalized Difference Vegetation Index (NDVI) in Alberta, Canada

    NASA Astrophysics Data System (ADS)

    Jiang, Rengui; Xie, Jiancang; He, Hailong; Kuo, Chun-Chao; Zhu, Jiwei; Yang, Mingxiang

    2016-01-01

    As one of the most popular vegetation indices to monitor terrestrial vegetation productivity, Normalized Difference Vegetation Index (NDVI) has been widely used to study the plant growth and vegetation productivity around the world, especially the dynamic response of vegetation to climate change in terms of precipitation and temperature. Alberta is the most important agricultural and forestry province and with the best climatic observation systems in Canada. However, few studies pertaining to climate change and vegetation productivity are found. The objectives of this paper therefore were to better understand impacts of climate change on vegetation productivity in Alberta using the NDVI and provide reference for policy makers and stakeholders. We investigated the following: (1) the variations of Alberta's smoothed NDVI (sNDVI, eliminated noise compared to NDVI) and two climatic variables (precipitation and temperature) using non-parametric Mann-Kendall monotonic test and Thiel-Sen's slope; (2) the relationships between sNDVI and climatic variables, and the potential predictability of sNDVI using climatic variables as predictors based on two predicted models; and (3) the use of a linear regression model and an artificial neural network calibrated by the genetic algorithm (ANN-GA) to estimate Alberta's sNDVI using precipitation and temperature as predictors. The results showed that (1) the monthly sNDVI has increased during the past 30 years and a lengthened growing season was detected; (2) vegetation productivity in northern Alberta was mainly temperature driven and the vegetation in southern Alberta was predominantly precipitation driven for the period of 1982-2011; and (3) better performances of the sNDVI-climate relationships were obtained by nonlinear model (ANN-GA) than using linear (regression) model. Similar results detected in both monthly and summer sNDVI prediction using climatic variables as predictors revealed the applicability of two models for different period of year ecologists might focus on.

  12. 5D Modelling: An Efficient Approach for Creating Spatiotemporal Predictive 3D Maps of Large-Scale Cultural Resources

    NASA Astrophysics Data System (ADS)

    Doulamis, A.; Doulamis, N.; Ioannidis, C.; Chrysouli, C.; Grammalidis, N.; Dimitropoulos, K.; Potsiou, C.; Stathopoulou, E.-K.; Ioannides, M.

    2015-08-01

    Outdoor large-scale cultural sites are mostly sensitive to environmental, natural and human made factors, implying an imminent need for a spatio-temporal assessment to identify regions of potential cultural interest (material degradation, structuring, conservation). On the other hand, in Cultural Heritage research quite different actors are involved (archaeologists, curators, conservators, simple users) each of diverse needs. All these statements advocate that a 5D modelling (3D geometry plus time plus levels of details) is ideally required for preservation and assessment of outdoor large scale cultural sites, which is currently implemented as a simple aggregation of 3D digital models at different time and levels of details. The main bottleneck of such an approach is its complexity, making 5D modelling impossible to be validated in real life conditions. In this paper, a cost effective and affordable framework for 5D modelling is proposed based on a spatial-temporal dependent aggregation of 3D digital models, by incorporating a predictive assessment procedure to indicate which regions (surfaces) of an object should be reconstructed at higher levels of details at next time instances and which at lower ones. In this way, dynamic change history maps are created, indicating spatial probabilities of regions needed further 3D modelling at forthcoming instances. Using these maps, predictive assessment can be made, that is, to localize surfaces within the objects where a high accuracy reconstruction process needs to be activated at the forthcoming time instances. The proposed 5D Digital Cultural Heritage Model (5D-DCHM) is implemented using open interoperable standards based on the CityGML framework, which also allows the description of additional semantic metadata information. Visualization aspects are also supported to allow easy manipulation, interaction and representation of the 5D-DCHM geometry and the respective semantic information. The open source 3DCityDB incorporating a PostgreSQL geo-database is used to manage and manipulate 3D data and their semantics.

  13. Computational analysis of the LRRK2 interactome

    PubMed Central

    Denny, Paul; Lovering, Ruth C.; Lewis, Patrick A.

    2015-01-01

    LRRK2 was identified in 2004 as the causative protein product of the Parkinson’s disease locus designated PARK8. In the decade since then, genetic studies have revealed at least 6 dominant mutations in LRRK2 linked to Parkinson’s disease, alongside one associated with cancer. It is now well established that coding changes in LRRK2 are one of the most common causes of Parkinson’s. Genome-wide association studies (GWAs) have, more recently, reported single nucleotide polymorphisms (SNPs) around the LRRK2 locus to be associated with risk of developing sporadic Parkinson’s disease and inflammatory bowel disorder. The functional research that has followed these genetic breakthroughs has generated an extensive literature regarding LRRK2 pathophysiology; however, there is still no consensus as to the biological function of LRRK2. To provide insight into the aspects of cell biology that are consistently related to LRRK2 activity, we analysed the plethora of candidate LRRK2 interactors available through the BioGRID and IntAct data repositories. We then performed GO terms enrichment for the LRRK2 interactome. We found that, in two different enrichment portals, the LRRK2 interactome was associated with terms referring to transport, cellular organization, vesicles and the cytoskeleton. We also verified that 21 of the LRRK2 interactors are genetically linked to risk for Parkinson’s disease or inflammatory bowel disorder. The implications of these findings are discussed, with particular regard to potential novel areas of investigation. PMID:25737818

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

    PubMed Central

    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. PMID:26442112

  15. AIM: a comprehensive Arabidopsis interactome module database and related interologs in plants

    PubMed Central

    Wang, Yi; Thilmony, Roger; Zhao, Yunjun; Chen, Guoping; Gu, Yong Q.

    2014-01-01

    Systems biology analysis of protein modules is important for understanding the functional relationships between proteins in the interactome. Here, we present a comprehensive database named AIM for Arabidopsis (Arabidopsis thaliana) interactome modules. The database contains almost 250?000 modules that were generated using multiple analysis methods and integration of microarray expression data. All the modules in AIM are well annotated using multiple gene function knowledge databases. AIM provides a user-friendly interface for different types of searches and offers a powerful graphical viewer for displaying module networks linked to the enrichment annotation terms. Both interactive Venn diagram and power graph viewer are integrated into the database for easy comparison of modules. In addition, predicted interologs from other plant species (homologous proteins from different species that share a conserved interaction module) are available for each Arabidopsis module. AIM is a powerful systems biology platform for obtaining valuable insights into the function of proteins in Arabidopsis and other plants using the modules of the Arabidopsis interactome. Database URL: http://probes.pw.usda.gov/AIM PMID:25480687

  16. Two-dimensional transient model for prediction of arteriolar NO/O2 modulation by spatiotemporal variations in cell-free layer width.

    PubMed

    Ng, Yan Cheng; Namgung, Bumseok; Kim, Sangho

    2015-01-01

    Despite the significant roles of the cell-free layer (CFL) in balancing nitric oxide (NO) and oxygen (O2) bioavailability in arteriolar tissue, many previous numerical approaches have relied on a one-dimensional (1-D) steady-state model for simplicity. However, these models are unable to demonstrate the influence of spatiotemporal variations in the CFL on the NO/O2 transport under dynamic flow conditions. Therefore, the present study proposes a new two-dimensional (2-D) transient model capable of predicting NO/O2 transport modulated by the spatiotemporal variations in the CFL width. Our model predicted that NO bioavailability was inversely related to the CFL width as expected. The enhancement of NO production by greater wall shear stress with a thinner CFL could dominate the diffusion barrier role of the CFL. In addition, NO/O2 availability along the vascular wall was inhomogeneous and highly regulated by dynamic changes of local CFL width variation. The spatial variations of CFL widths on opposite sides of the arteriole exhibited a significant inverse relation. This asymmetric formation of CFL resulted in a significantly imbalanced NO/O2 bioavailability on opposite sides of the arteriole. The novel integrative methodology presented here substantially highlighted the significance of spatiotemporal variations of the CFL in regulating the bioavailability of NO/O2, and provided further insight about the opposing effects of the CFL on arteriolar NO production. PMID:25312045

  17. Toward high-resolution flash flood prediction in large urban areas - Analysis of sensitivity to spatiotemporal resolution of rainfall input and hydrologic modeling

    NASA Astrophysics Data System (ADS)

    Rafieeinasab, Arezoo; Norouzi, Amir; Kim, Sunghee; Habibi, Hamideh; Nazari, Behzad; Seo, Dong-Jun; Lee, Haksu; Cosgrove, Brian; Cui, Zhengtao

    2015-12-01

    Urban flash flooding is a serious problem in large, highly populated areas such as the Dallas-Fort Worth Metroplex (DFW). Being able to monitor and predict flash flooding at a high spatiotemporal resolution is critical to providing location-specific early warnings and cost-effective emergency management in such areas. Under the idealized conditions of perfect models and precipitation input, one may expect that spatiotemporal specificity and accuracy of the model output improve as the resolution of the models and precipitation input increases. In reality, however, due to the errors in the precipitation input, and in the structures, parameters and states of the models, there are practical limits to the model resolution. In this work, we assess the sensitivity of streamflow simulation in urban catchments to the spatiotemporal resolution of precipitation input and hydrologic modeling to identify the resolution at which the simulation errors may be at minimum given the quality of the precipitation input and hydrologic models used, and the response time of the catchment. The hydrologic modeling system used in this work is the National Weather Service (NWS) Hydrology Laboratory's Research Distributed Hydrologic Model (HLRDHM) applied at spatiotemporal resolutions ranging from 250 m to 2 km and from 1 min to 1 h applied over the Cities of Fort Worth, Arlington and Grand Prairie in DFW. The high-resolution precipitation input is from the DFW Demonstration Network of the Collaborative Adaptive Sensing of the Atmosphere (CASA) radars. For comparison, the NWS Multisensor Precipitation Estimator (MPE) product, which is available at a 4-km 1-h resolution, was also used. The streamflow simulation results are evaluated for 5 urban catchments ranging in size from 3.4 to 54.6 km2 and from about 45 min to 3 h in time-to-peak in the Cities of Fort Worth, Arlington and Grand Prairie. The streamflow observations used in evaluation were obtained from water level measurements via rating curves derived from 1-D steady-state non-uniform hydraulic modeling. The results indicate that a spatiotemporal resolution of 500 m and 15 min or higher is a good choice for streamflow prediction using HLRDHM and CASA QPE in the study area, but that, due to the nonlinear accretion of random errors in QPE and imperfect model dynamics, there are trade-offs to consider among resolution, timeliness of prediction and prediction accuracy.

  18. Comparative protein interactomics of neuroglobin and myoglobin

    PubMed Central

    Haines, Bryan A.; Davis, Darcy A.; Zykovich, Artem; Peng, Botao; Rao, Rammohan; Mooney, Sean D.; Jin, Kunlin; Greenberg, David A.

    2012-01-01

    Neuroglobin is a hypoxia-inducible O2-binding protein with neuroprotective effects in cell and animal models of stroke and Alzheimer’s disease. The mechanism underlying neuroglobin’s cytoprotective action is unknown, although several possibilities have been proposed, including antioxidative and antiapoptotic effects. We used affinity purification-mass spectrometry methods to identify neuroglobin-interacting proteins in normoxic and hypoxic murine neuronal (HN33) cell lysates, and to compare these interactions with those of a structurally and functionally related protein, myoglobin. We report that the protein interactomes of neuroglobin and myoglobin overlap substantially and are modified by hypoxia. In addition, neuroglobin-interacting proteins include partners consistent with both antioxidative and antiapoptotic functions, as well as with a relationship to several neurodegenerative diseases. PMID:22816983

  19. A Unified Spatiotemporal Modeling Approach for Predicting Concentrations of Multiple Air Pollutants in the Multi-Ethnic Study of Atherosclerosis and Air Pollution

    PubMed Central

    Olives, Casey; Kim, Sun-Young; Sheppard, Lianne; Sampson, Paul D.; Szpiro, Adam A.; Oron, Assaf P.; Lindström, Johan; Vedal, Sverre; Kaufman, Joel D.

    2014-01-01

    Background: Cohort studies of the relationship between air pollution exposure and chronic health effects require predictions of exposure over long periods of time. Objectives: We developed a unified modeling approach for predicting fine particulate matter, nitrogen dioxide, oxides of nitrogen, and black carbon (as measured by light absorption coefficient) in six U.S. metropolitan regions from 1999 through early 2012 as part of the Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air). Methods: We obtained monitoring data from regulatory networks and supplemented those data with study-specific measurements collected from MESA Air community locations and participants’ homes. In each region, we applied a spatiotemporal model that included a long-term spatial mean, time trends with spatially varying coefficients, and a spatiotemporal residual. The mean structure was derived from a large set of geographic covariates that was reduced using partial least-squares regression. We estimated time trends from observed time series and used spatial smoothing methods to borrow strength between observations. Results: Prediction accuracy was high for most models, with cross-validation R2 (R2CV) > 0.80 at regulatory and fixed sites for most regions and pollutants. At home sites, overall R2CV ranged from 0.45 to 0.92, and temporally adjusted R2CV ranged from 0.23 to 0.92. Conclusions: This novel spatiotemporal modeling approach provides accurate fine-scale predictions in multiple regions for four pollutants. We have generated participant-specific predictions for MESA Air to investigate health effects of long-term air pollution exposures. These successes highlight modeling advances that can be adopted more widely in modern cohort studies. Citation: Keller JP, Olives C, Kim SY, Sheppard L, Sampson PD, Szpiro AA, Oron AP, Lindström J, Vedal S, Kaufman JD. 2015. A unified spatiotemporal modeling approach for predicting concentrations of multiple air pollutants in the Multi-Ethnic Study of Atherosclerosis and Air Pollution. Environ Health Perspect 123:301–309; http://dx.doi.org/10.1289/ehp.1408145 PMID:25398188

  20. A process-level evaluation of the spatiotemporal variability of CO2 fluxes predicted by terrestrial biosphere models using atmospheric data

    NASA Astrophysics Data System (ADS)

    Fang, Y.; Michalak, A. M.; Shiga, Y. P.; Yadav, V.

    2013-12-01

    Terrestrial biosphere models (TBMs) are used to extrapolate local observations and process-level understanding of land-atmosphere carbon exchange to larger regions, and can serve as a predictive tool for examining carbon-climate interactions and global change. Understanding and improving the performance of TBMs is thus crucial to the carbon cycle research community. In this work, we evaluate the spatiotemporal patterns of net ecosystem exchange (NEE) simulated by TBMs using atmospheric CO2 observations and a Geostatistical Inverse Modeling (GIM) framework. The evaluation methodology is based on the ability (or inability) of the spatiotemporal patterns in NEE estimates to explain the variability observed in atmospheric CO2 distribution. More simply, we examine whether the spatiotemporal patterns of NEE simulated by TBMs (including CASA-GFED, ORCHIDEE, VEGAS2 and SiB3) are consistent with the variations observed in the atmosphere. A similar GIM methodology is also applied using environmental variables (such as water availability, temperature, radiation, etc.) rather than TBMs, to explore the environmental processes associated with the variability of NEE, and determine which processes are associated with good/poor performance in TBMs. We find that NEE simulated by TBMs is consistent with that seen by atmospheric measurements more often during growing season months (Apr-Sept) than during the non-growing season. Over Temperate Broadleaf and Mixed Forests, Temperate Coniferous Forests and Temperate Grasslands, Savannas and Shrublands, atmospheric measurements are sufficiently sensitive to NEE fluxes to constrain the evaluation of model performance during the majority of the year (about 7-8 months in a year, mostly in growing season). For these regions and months, at least one of the TBMs is found to be able to reproduce the observed variability, but the most representative TBM varies by region and month. For the remaining months, none of the TBMs are able to reproduce the observed variability, whereas a linear combination of environmental variables is able to do so. By further comparing environmental processes associated with the spatiotemporal variability of NEE from the observations and from each TBM, we find that TBMs perform well when radiation-related processes are dominant; however, TBMs perform less well when water-availability (and temperature) are more important. It thus appears that the representation of water availability and its impact on fluxes within TBMs are areas of opportunity for improving TBM predictions, for example, in the seasonal transition. Further exploration of the processes associated with water availability in state-of-the-art TBMs, such as soil respiration, could therefore lead to improvements in their ability to represent the spatiotemporal variability of fluxes during the dormant season and their ability to represent phenology and carbon exchange during transition months.

  1. The topology of the growing human interactome data.

    PubMed

    Janjić, Vuk; Pržulj, Nataša

    2014-01-01

    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. PMID:24953453

  2. 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

  3. Geomapping generalized eigenvalue frequency distributions for predicting prolific Aedes albopictus and Culex quinquefasciatus habitats based on spatiotemporal field-sampled count data.

    PubMed

    Jacob, Benjamin G; Morris, Joel A; Caamano, Erick X; Griffith, Daniel A; Novak, Robert J

    2011-02-01

    Marked spatiotemporal variabilities in mosquito infection of arboviruses require adaptive strategies for determining optimal field-sampling timeframes, pool screening, and data analyses. In particular, the error distribution and aggregation patterns of adult arboviral mosquitoes can vary significantly by species, which can statistically bias analyses of spatiotemporal-sampled predictor variables generating misinterpretation of prolific habitat surveillance locations. Currently, there is a lack of reliable and consistent measures of risk exposure based on field-sampled georeferenced explanatory covariates which can compromise quantitative predictions generated from arboviral mosquito surveillance models for implementing larval control strategies targeting productive habitats. In this research we used spatial statistics and QuickBird visible and near-infra-red data for determining trapping sites that were related to Culex quinquefasciatus and Aedes albopictus species abundance and distribution in Birmingham, Alabama. Initially, a Land Use Land Cover (LULC) model was constructed from multiple spatiotemporal-sampled georeferenced predictors and the QuickBird data. A Poisson regression model with a non-homogenous, gamma-distributed mean then decomposed the data into positive and negative spatial filter eigenvectors. An autoregressive process in the error term then was used to derive the sample distribution of the Moran's I statistic for determining latent autocorrelation components in the model. Spatial filter algorithms established means, variances, distributional functions, and pairwise correlations for the predictor variables. In doing so, the eigenfunction spatial filter quantified the residual autocorrelation error in the mean response term of the model as a linear combination of various distinct Cx. quinquefasciatus and Ae. albopictus habitat map patterns. The analyses revealed 18-27% redundant information in the data. Prolific habitats of Cx. quinquefasciatus and Ae. albopictus can be accurately spatially targeted based on georeferenced field-sampled count data using QuickBird data, LULC explanatory covariates, robust negative binomial regression estimates and space-time eigenfunctions. PMID:20969828

  4. 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

  5. Intrinsic Disorder in the BK Channel and Its Interactome

    PubMed Central

    Peng, Zhenling; Sakai, Yoshihisa; Kurgan, Lukasz; Sokolowski, Bernd; Uversky, Vladimir

    2014-01-01

    The large-conductance Ca2+-activated K+ (BK) channel is broadly expressed in various mammalian cells and tissues such as neurons, skeletal and smooth muscles, exocrine cells, and sensory cells of the inner ear. Previous studies suggest that BK channels are promiscuous binders involved in a multitude of protein-protein interactions. To gain a better understanding of the potential mechanisms underlying BK interactions, we analyzed the abundance, distribution, and potential mechanisms of intrinsic disorder in 27 BK channel variants from mouse cochlea, 104 previously reported BK-associated proteins (BKAPS) from cytoplasmic and membrane/cytoskeletal regions, plus BK β- and γ-subunits. Disorder was evaluated using the MFDp algorithm, which is a consensus-based predictor that provides a strong and competitive predictive quality and PONDR, which can determine long intrinsically disordered regions (IDRs). Disorder-based binding sites or molecular recognition features (MoRFs) were found using MoRFpred and ANCHOR. BKAP functions were categorized based on Gene Ontology (GO) terms. The analyses revealed that the BK variants contain a number of IDRs. Intrinsic disorder is also common in BKAPs, of which ∼5% are completely disordered. However, intrinsic disorder is very differently distributed within BK and its partners. Approximately 65% of the disordered segments in BK channels are long (IDRs) (>50 residues), whereas >60% of the disordered segments in BKAPs are short IDRs that range in length from 4 to 30 residues. Both α and γ subunits showed various amounts of disorder as did hub proteins of the BK interactome. Our analyses suggest that intrinsic disorder is important for the function of BK and its BKAPs. Long IDRs in BK are engaged in protein-protein and protein-ligand interactions, contain multiple post-translational modification sites, and are subjected to alternative splicing. The disordered structure of BK and its BKAPs suggests one of the underlying mechanisms of their interaction. PMID:24727949

  6. Evidence for network evolution in an arabidopsis interactome map

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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...

  7. Dynamic Zebrafish Interactome Reveals Transcriptional Mechanisms of Dioxin Toxicity

    PubMed Central

    Alexeyenko, Andrey; Wassenberg, Deena M.; Lobenhofer, Edward K.; Yen, Jerry; Linney, Elwood; Sonnhammer, Erik L. L.; Meyer, Joel N.

    2010-01-01

    Background In order to generate hypotheses regarding the mechanisms by which 2,3,7,8-tetrachlorodibenzo-p-dioxin (dioxin) causes toxicity, we analyzed global gene expression changes in developing zebrafish embryos exposed to this potent toxicant in the context of a dynamic gene network. For this purpose, we also computationally inferred a zebrafish (Danio rerio) interactome based on orthologs and interaction data from other eukaryotes. Methodology/Principal Findings Using novel computational tools to analyze this interactome, we distinguished between dioxin-dependent and dioxin-independent interactions between proteins, and tracked the temporal propagation of dioxin-dependent transcriptional changes from a few genes that were altered initially, to large groups of biologically coherent genes at later times. The most notable processes altered at later developmental stages were calcium and iron metabolism, embryonic morphogenesis including neuronal and retinal development, a variety of mitochondria-related functions, and generalized stress response (not including induction of antioxidant genes). Within the interactome, many of these responses were connected to cytochrome P4501A (cyp1a) as well as other genes that were dioxin-regulated one day after exposure. This suggests that cyp1a may play a key role initiating the toxic dysregulation of those processes, rather than serving simply as a passive marker of dioxin exposure, as suggested by earlier research. Conclusions/Significance Thus, a powerful microarray experiment coupled with a flexible interactome and multi-pronged interactome tools (which are now made publicly available for microarray analysis and related work) suggest the hypothesis that dioxin, best known in fish as a potent cardioteratogen, has many other targets. Many of these types of toxicity have been observed in mammalian species and are potentially caused by alterations to cyp1a. PMID:20463971

  8. 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. PMID:26552673

  9. Improved Microarray-Based Decision Support with Graph Encoded Interactome Data

    PubMed Central

    Daemen, Anneleen; Signoretto, Marco; Gevaert, Olivier; Suykens, Johan A. K.; De Moor, Bart

    2010-01-01

    In the past, microarray studies have been criticized due to noise and the limited overlap between gene signatures. Prior biological knowledge should therefore be incorporated as side information in models based on gene expression data to improve the accuracy of diagnosis and prognosis in cancer. As prior knowledge, we investigated interaction and pathway information from the human interactome on different aspects of biological systems. By exploiting the properties of kernel methods, relations between genes with similar functions but active in alternative pathways could be incorporated in a support vector machine classifier based on spectral graph theory. Using 10 microarray data sets, we first reduced the number of data sources relevant for multiple cancer types and outcomes. Three sources on metabolic pathway information (KEGG), protein-protein interactions (OPHID) and miRNA-gene targeting (microRNA.org) outperformed the other sources with regard to the considered class of models. Both fixed and adaptive approaches were subsequently considered to combine the three corresponding classifiers. Averaging the predictions of these classifiers performed best and was significantly better than the model based on microarray data only. These results were confirmed on 6 validation microarray sets, with a significantly improved performance in 4 of them. Integrating interactome data thus improves classification of cancer outcome for the investigated microarray technologies and cancer types. Moreover, this strategy can be incorporated in any kernel method or non-linear version of a non-kernel method. PMID:20419106

  10. 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

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

    SciTech Connect

    Klopffleisch, Karsten; Phan, Nguyen; Chen, Jay; Panstruga, Ralph; Uhrig, Joachim; Jones, Alan M

    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, 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.

  12. A human skeletal muscle interactome centered on proteins involved in muscular dystrophies: LGMD interactome

    PubMed Central

    2013-01-01

    Background The complexity of the skeletal muscle and the identification of numerous human disease-causing mutations in its constitutive proteins make it an interesting tissue for proteomic studies aimed at understanding functional relationships of interacting proteins in both health and diseases. Method We undertook a large-scale study using two-hybrid screens and a human skeletal-muscle cDNA library to establish a proteome-scale map of protein-protein interactions centered on proteins involved in limb-girdle muscular dystrophies (LGMD). LGMD is a group of more than 20 different neuromuscular disorders that principally affect the proximal pelvic and shoulder girdle muscles. Results and conclusion The interaction network we unraveled incorporates 1018 proteins connected by 1492 direct binary interactions and includes 1420 novel protein-protein interactions. Computational, experimental and literature-based analyses were performed to assess the overall quality of this network. Interestingly, LGMD proteins were shown to be highly interconnected, in particular indirectly through sarcomeric proteins. In-depth mining of the LGMD-centered interactome identified new candidate genes for orphan LGMDs and other neuromuscular disorders. The data also suggest the existence of functional links between LGMD2B/dysferlin and gene regulation, between LGMD2C/γ-sarcoglycan and energy control and between LGMD2G/telethonin and maintenance of genome integrity. This dataset represents a valuable resource for future functional investigations. PMID:23414517

  13. PINA v2.0: mining interactome modules.

    PubMed

    Cowley, Mark J; Pinese, Mark; Kassahn, Karin S; Waddell, Nic; Pearson, John V; Grimmond, Sean M; Biankin, Andrew V; Hautaniemi, Sampsa; Wu, Jianmin

    2012-01-01

    The Protein Interaction Network Analysis (PINA) platform is a comprehensive web resource, which includes a database of unified protein-protein interaction data integrated from six manually curated public databases, and a set of built-in tools for network construction, filtering, analysis and visualization. The second version of PINA enhances its utility for studies of protein interactions at a network level, by including multiple collections of interaction modules identified by different clustering approaches from the whole network of protein interactions ('interactome') for six model organisms. All identified modules are fully annotated by enriched Gene Ontology terms, KEGG pathways, Pfam domains and the chemical and genetic perturbations collection from MSigDB. Moreover, a new tool is provided for module enrichment analysis in addition to simple query function. The interactome data are also available on the web site for further bioinformatics analysis. PINA is freely accessible at http://cbg.garvan.unsw.edu.au/pina/. PMID:22067443

  14. Spatio-temporal prediction of leaf area index of rubber plantation using HJ-1A/1B CCD images and recurrent neural network

    NASA Astrophysics Data System (ADS)

    Chen, Bangqian; Wu, Zhixiang; Wang, Jikun; Dong, Jinwei; Guan, Liming; Chen, Junming; Yang, Kai; Xie, Guishui

    2015-04-01

    Rubber (Hevea brasiliensis) plantations are one of the most important economic forest in tropical area. Retrieving leaf area index (LAI) and its dynamics by remote sensing is of great significance in ecological study and production management, such as yield prediction and post-hurricane damage evaluation. Thirteen HJ-1A/1B CCD images, which possess the spatial advantage of Landsat TM/ETM+ and 2-days temporal resolution of MODIS, were introduced to predict the spatial-temporal LAI of rubber plantation on Hainan Island by Nonlinear AutoRegressive networks with eXogenous inputs (NARX) model. Monthly measured LAIs at 30 stands by LAI-2000 between 2012 and 2013 were used to explore the LAI dynamics and their relationship with spectral bands and seven vegetation indices, and to develop and validate model. The NARX model, which was built base on input variables of day of year (DOY), four spectral bands and weight difference vegetation index (WDVI), possessed good accuracies during the model building for the data set of training (N = 202, R2 = 0.98, RMSE = 0.13), validation (N = 43, R2 = 0.93, RMSE = 0.24) and testing (N = 43, R2 = 0.87, RMSE = 0.31), respectively. The model performed well during field validation (N = 24, R2 = 0.88, RMSE = 0.24) and most of its mapping results showed better agreement (R2 = 0.54-0.58, RMSE = 0.47-0.71) with the field data than the results of corresponding stepwise regression models (R2 = 0.43-0.51, RMSE = 0.52-0.82). Besides, the LAI statistical values from the spatio-temporal LAI maps and their dynamics, which increased dramatically from late March (2.36 ± 0.59) to early May (3.22 ± 0.64) and then gradually slow down until reached the maximum value in early October (4.21 ± 0.87), were quite consistent with the statistical results of the field data. The study demonstrates the feasibility and reliability of retrieving spatio-temporal LAI of rubber plantations by an artificial neural network (ANN) approach, and provides some insight on the application of HJ-1A/1B CCD images, and data and methods for productivity study of rubber plantation in future.

  15. Proteomic data on the nuclear interactome of human MCM9

    PubMed Central

    Hutchins, James R.A.; Traver, Sabine; Coulombe, Philippe; Peiffer, Isabelle; Kitzmann, Magali; Latreille, Daniel; Méchali, Marcel

    2015-01-01

    We present data relating to the interactome of MCM9 from the nuclei of human cells. MCM9 belongs to the AAA+ superfamily, and contains an MCM domain and motifs that may confer DNA helicase activity. MCM9 has been shown to bind MCM8, and has been implicated in DNA replication and homologous recombination. However, the mechanistic basis of MCM9’s role in DNA repair is poorly understood, and proteins with which it interacts were hitherto unknown. We performed tandem affinity purification of MCM9 and its interacting proteins from nuclear extracts of human cells, followed by proteomic analysis, thereby generating a set of mass spectrometry data corresponding to the MCM9 interactome [1]. The proteomic data set comprises 29 mass spectrometry RAW files, deposited to the ProteomeXchange Consortium, and freely available from the PRIDE partner repository with the data set identifier PXD000212. A set of 22 interacting proteins identified from the proteomic data was used to create an MCM9-centered interactive network diagram, using the Cytoscape program. These data allow the scientific community to access, mine and explore the human nuclear MCM9 interactome. PMID:26870752

  16. Charting the NF-κB Pathway Interactome Map

    PubMed Central

    Tieri, Paolo; Termanini, Alberto; Bellavista, Elena; Salvioli, Stefano; Capri, Miriam; Franceschi, Claudio

    2012-01-01

    Inflammation is part of a complex physiological response to harmful stimuli and pathogenic stress. The five components of the Nuclear Factor κB (NF-κB) family are prominent mediators of inflammation, acting as key transcriptional regulators of hundreds of genes. Several signaling pathways activated by diverse stimuli converge on NF-κB activation, resulting in a regulatory system characterized by high complexity. It is increasingly recognized that the number of components that impinges upon phenotypic outcomes of signal transduction pathways may be higher than those taken into consideration from canonical pathway representations. Scope of the present analysis is to provide a wider, systemic picture of the NF-κB signaling system. Data from different sources such as literature, functional enrichment web resources, protein-protein interaction and pathway databases have been gathered, curated, integrated and analyzed in order to reconstruct a single, comprehensive picture of the proteins that interact with, and participate to the NF-κB activation system. Such a reconstruction shows that the NF-κB interactome is substantially different in quantity and quality of components with respect to canonical representations. The analysis highlights that several neglected but topologically central proteins may play a role in the activation of NF-κB mediated responses. Moreover the interactome structure fits with the characteristics of a bow tie architecture. This interactome is intended as an open network resource available for further development, refinement and analysis. PMID:22403694

  17. Charting the NF-κB pathway interactome map.

    PubMed

    Tieri, Paolo; Termanini, Alberto; Bellavista, Elena; Salvioli, Stefano; Capri, Miriam; Franceschi, Claudio

    2012-01-01

    Inflammation is part of a complex physiological response to harmful stimuli and pathogenic stress. The five components of the Nuclear Factor κB (NF-κB) family are prominent mediators of inflammation, acting as key transcriptional regulators of hundreds of genes. Several signaling pathways activated by diverse stimuli converge on NF-κB activation, resulting in a regulatory system characterized by high complexity. It is increasingly recognized that the number of components that impinges upon phenotypic outcomes of signal transduction pathways may be higher than those taken into consideration from canonical pathway representations. Scope of the present analysis is to provide a wider, systemic picture of the NF-κB signaling system. Data from different sources such as literature, functional enrichment web resources, protein-protein interaction and pathway databases have been gathered, curated, integrated and analyzed in order to reconstruct a single, comprehensive picture of the proteins that interact with, and participate to the NF-κB activation system. Such a reconstruction shows that the NF-κB interactome is substantially different in quantity and quality of components with respect to canonical representations. The analysis highlights that several neglected but topologically central proteins may play a role in the activation of NF-κB mediated responses. Moreover the interactome structure fits with the characteristics of a bow tie architecture. This interactome is intended as an open network resource available for further development, refinement and analysis. PMID:22403694

  18. Analysis of the interactome of ribosomal protein S19 mutants.

    PubMed

    Caterino, Marianna; Aspesi, Anna; Pavesi, Elisa; Imperlini, Esther; Pagnozzi, Daniela; Ingenito, Laura; Santoro, Claudio; Dianzani, Irma; Ruoppolo, Margherita

    2014-10-01

    Diamond-Blackfan anemia, characterized by defective erythroid progenitor maturation, is caused in one-fourth of cases by mutations of ribosomal protein S19 (RPS19), which is a component of the ribosomal 40S subunit. Our previous work described proteins interacting with RPS19 with the aim to determine its functions. Here, two RPS19 mutants, R62W and R101H, have been selected to compare their interactomes versus the wild-type protein one, using the same functional proteomic approach that we employed to characterize RPS19 interactome. Mutations R62W and R101H impair RPS19 ability to associate with the ribosome. Results presented in this paper highlight the striking differences between the interactomes of wild-type and mutant RPS19 proteins. In particular, mutations abolish interactions with proteins having splicing, translational and helicase activity, thus confirming the role of RPS19 in RNA processing/metabolism and translational control. The data have been deposited to the ProteomeXchange with identifier PXD000640 (http://proteomecentral.proteomexchange.org/dataset/PXD000640). PMID:25069755

  19. Proteomic data on the nuclear interactome of human MCM9.

    PubMed

    Hutchins, James R A; Traver, Sabine; Coulombe, Philippe; Peiffer, Isabelle; Kitzmann, Magali; Latreille, Daniel; Méchali, Marcel

    2016-03-01

    We present data relating to the interactome of MCM9 from the nuclei of human cells. MCM9 belongs to the AAA+ superfamily, and contains an MCM domain and motifs that may confer DNA helicase activity. MCM9 has been shown to bind MCM8, and has been implicated in DNA replication and homologous recombination. However, the mechanistic basis of MCM9's role in DNA repair is poorly understood, and proteins with which it interacts were hitherto unknown. We performed tandem affinity purification of MCM9 and its interacting proteins from nuclear extracts of human cells, followed by proteomic analysis, thereby generating a set of mass spectrometry data corresponding to the MCM9 interactome [1]. The proteomic data set comprises 29 mass spectrometry RAW files, deposited to the ProteomeXchange Consortium, and freely available from the PRIDE partner repository with the data set identifier PXD000212. A set of 22 interacting proteins identified from the proteomic data was used to create an MCM9-centered interactive network diagram, using the Cytoscape program. These data allow the scientific community to access, mine and explore the human nuclear MCM9 interactome. PMID:26870752

  20. Hierarchical modularity and the evolution of genetic interactomes across species

    PubMed Central

    Ryan, Colm J.; Roguev, Assen; Patrick, Kristin; Xu, Jiewei; Jahari, Harlizawati; Tong, Zongtian; Beltrao, Pedro; Shales, Michael; Qu, Hong; Collins, Sean R.; Kliegman, Joseph I.; Jiang, Lingli; Kuo, Dwight; Tosti, Elena; Kim, Hyun-Soo; Edelmann, Winfried; Keogh, Michael-Christopher; Greene, Derek; Tang, Chao; Cunningham, Pádraig; Shokat, Kevan M.; Cagney, Gerard; Svensson, J. Peter; Guthrie, Christine; Espenshade, Peter J.; Ideker, Trey; Krogan, Nevan J.

    2012-01-01

    To date, cross-species comparisons of genetic interactomes have been restricted to small or functionally related gene sets, limiting our ability to infer evolutionary trends. To facilitate a more comprehensive analysis, we constructed a genome-scale epistasis map (E-MAP) for the fission yeast Schizosaccharomyces pombe, providing phenotypic signatures for ~60% of the non-essential genome. Using these signatures, we generated a catalogue of 297 functional modules, and assigned function to 144 previously uncharacterised genes, including mRNA splicing and DNA damage checkpoint factors. Comparison with an integrated genetic interactome from the budding yeast Saccharomyces cerevisiae revealed a hierarchical model for the evolution of genetic interactions, with conservation highest within protein complexes, lower within biological processes, and lowest between distinct biological processes. Despite the large evolutionary distance and extensive rewiring of individual interactions, both networks retain conserved features and display similar levels of functional cross-talk between biological processes, suggesting general design principles of genetic interactomes. PMID:22681890

  1. Cancer networks and beyond: interpreting mutations using the human interactome and protein structure.

    PubMed

    Gulati, Sakshi; Cheng, Tammy M K; Bates, Paul A

    2013-08-01

    Over recent years, with the advances in next-generation sequencing, a large number of cancer mutations have been identified and accumulated in public repositories. Coupled to this is our increased ability to generate detailed interactome maps that help to enrich our knowledge of the biological implications of cancer mutations. As a result, network analysis approaches have become an invaluable tool to predict and interpret mutations that are associated with tumour survival and progression. Our understanding of cancer mechanisms is further enhanced by mapping protein structure information to such networks. Here we review the current methodologies for annotating the functional impacts of cancer mutations, which range from analysis of protein structures to protein-protein interaction network studies. PMID:23680723

  2. 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. PMID:26721628

  3. AIM: A comprehensive Arabidopsis Interactome Module database and related interologs in plants

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Systems biology analysis of protein modules is important for understanding the functional relationships between proteins in the interactome. Here, we present a comprehensive database named AIM for Arabidopsis (Arabidopsis thaliana) interactome modules. The database contains almost 250,000 modules th...

  4. Predicted spatio-temporal dynamics of radiocesium deposited on forests following the Fukushima Dai-ichi nuclear power plant accident

    NASA Astrophysics Data System (ADS)

    Hashimoto, Shoji; Matsuura, Toshiya; Nanko, Kazuki; Linkov, Igor; Shaw, George; Kaneko, Shinji

    2013-04-01

    Radiocesium (134Cs and 137Cs) released from the Fukushima Dai-ichi nuclear power plant to the atmosphere contaminated a large area of Japan's land surface, the majority of which is covered by forest. Here we simulated the dynamics of radiocesium deposited on Japanese forest ecosystems in 2011 using a model that was developed for tracking radionuclides in forest ecosystems after the Chernobyl accident in 1986. The fate of the radiocesium was simulated using the initial conditions observed following the Fukushima accident. In addition, the simulation results were incorporated with a spatial distribution map of deposited radionuclides that was based on an air-borne survey. The simulation demonstrated that in the first two years after initial deposition radiocesium is retained primarily in the soil surface organic layer. Over a period of five to ten years radiocesium is predicted to move from the surface organic soil to the deeper mineral soil, which will eventually become the largest reservoir of radiocesium within forest ecosystems. Spatial analysis clearly shows the reduction in the extent of contaminated areas which will occur as a result of natural decay of radiocesium, as well as the spatial distribution of radiocesium in each forest component. Considering the heavier rainfall and warmer conditions in Japan than in the countries contaminated by the Chernobyl accident, migration of radiocesium from organic to mineral soil may be faster than predicted. Although the uncertainty of our simulations should be taken into account, they provide a basis for understanding and anticipating the future dynamics of radiocesium in Japanese forests following the Fukushima accident.

  5. 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

  6. Summer rains and dry seasons in the upper Blue Nile Basin: the predictability of half a century of past and future spatiotemporal patterns.

    PubMed

    Mellander, Per-Erik; Gebrehiwot, Solomon G; Gärdenäs, Annemieke I; Bewket, Woldeamlak; Bishop, Kevin

    2013-01-01

    During the last 100 years the Ethiopian upper Blue Nile Basin (BNB) has undergone major changes in land use, and is now potentially facing changes in climate. Rainfall over BNB supplies over two-thirds of the water to the Nile and supports a large local population living mainly on subsistence agriculture. Regional food security is sensitive to both the amount and timing of rain and is already an important political challenge that will be further complicated if scenarios of climate change are realized. In this study a simple spatial model of the timing and duration of summer rains (Kiremt) and dry season (Bega), and annual rain over the upper BNB was established from observed data between 1952 and 2004. The model was used to explore potential impacts of climate change on these rains, using a down-scaled ECHAM5/MP1-OM scenario between 2050 and 2100. Over the observed period the amount, onset and duration of Kiremt rains and rain-free Bega days have exhibited a consistent spatial pattern. The spatially averaged annual rainfall was 1490 mm of which 93% was Kiremt rain. The average Kiremt rain and number of rainy days was higher in the southwest (322 days) and decreased towards the north (136 days). Under the 2050-2100 scenario, the annual mean rainfall is predicted to increase by 6% and maintain the same spatial pattern as in the past. A larger change in annual rainfall is expected in the southwest (ca. +130 mm) with a gradually smaller change towards the north (ca. +70 mm). Results highlight the need to account for the characteristic spatiotemporal zonation when planning water management and climate adaptation within the upper BNB. The presented simple spatial resolved models of the presence of Kiremt and annual total rainfall could be used as a baseline for such long-term planning. PMID:23869219

  7. Summer Rains and Dry Seasons in the Upper Blue Nile Basin: The Predictability of Half a Century of Past and Future Spatiotemporal Patterns

    PubMed Central

    Mellander, Per-Erik; Gebrehiwot, Solomon G.; Gärdenäs, Annemieke I.; Bewket, Woldeamlak; Bishop, Kevin

    2013-01-01

    During the last 100 years the Ethiopian upper Blue Nile Basin (BNB) has undergone major changes in land use, and is now potentially facing changes in climate. Rainfall over BNB supplies over two-thirds of the water to the Nile and supports a large local population living mainly on subsistence agriculture. Regional food security is sensitive to both the amount and timing of rain and is already an important political challenge that will be further complicated if scenarios of climate change are realized. In this study a simple spatial model of the timing and duration of summer rains (Kiremt) and dry season (Bega), and annual rain over the upper BNB was established from observed data between 1952 and 2004. The model was used to explore potential impacts of climate change on these rains, using a down-scaled ECHAM5/MP1-OM scenario between 2050 and 2100. Over the observed period the amount, onset and duration of Kiremt rains and rain-free Bega days have exhibited a consistent spatial pattern. The spatially averaged annual rainfall was 1490 mm of which 93% was Kiremt rain. The average Kiremt rain and number of rainy days was higher in the southwest (322 days) and decreased towards the north (136 days). Under the 2050–2100 scenario, the annual mean rainfall is predicted to increase by 6% and maintain the same spatial pattern as in the past. A larger change in annual rainfall is expected in the southwest (ca. +130 mm) with a gradually smaller change towards the north (ca. +70 mm). Results highlight the need to account for the characteristic spatiotemporal zonation when planning water management and climate adaptation within the upper BNB. The presented simple spatial resolved models of the presence of Kiremt and annual total rainfall could be used as a baseline for such long-term planning. PMID:23869219

  8. Nuclear Functions of Nucleolin through Global Proteomics and Interactomic Approaches.

    PubMed

    Salvetti, Anna; Couté, Yohann; Epstein, Alberto; Arata, Loredana; Kraut, Alexandra; Navratil, Vincent; Bouvet, Philippe; Greco, Anna

    2016-05-01

    Nucleolin (NCL) is a major component of the cell nucleolus, which has the ability to rapidly shuttle to several other cells' compartments. NCL plays important roles in a variety of essential functions, among which are ribosome biogenesis, gene expression, and cell growth. However, the precise mechanisms underlying NCL functions are still unclear. Our study aimed to provide new information on NCL functions via the identification of its nuclear interacting partners. Using an interactomics approach, we identified 140 proteins co-purified with NCL, among which 100 of them were specifically found to be associated with NCL after RNase digestion. The functional classification of these proteins confirmed the prominent role of NCL in ribosome biogenesis and additionally revealed the possible involvement of nuclear NCL in several pre-mRNA processing pathways through its interaction with RNA helicases and proteins participating in pre-mRNA splicing, transport, or stability. NCL knockdown experiments revealed that NCL regulates the localization of EXOSC10 and the amount of ZC3HAV1, two components of the RNA exosome, further suggesting its involvement in the control of mRNA stability. Altogether, this study describes the first nuclear interactome of human NCL and provides the basis for further understanding the mechanisms underlying the essential functions of this nucleolar protein. PMID:27049334

  9. Dissecting noncoding and pathogen RNA–protein interactomes

    PubMed Central

    Flynn, Ryan A.; Martin, Lance; Spitale, Robert C.; Do, Brian T.; Sagan, Selena M.; Zarnegar, Brian; Qu, Kun; Khavari, Paul A.; Quake, Stephen R.; Sarnow, Peter

    2015-01-01

    RNA–protein interactions are central to biological regulation. Cross-linking immunoprecipitation (CLIP)-seq is a powerful tool for genome-wide interrogation of RNA–protein interactomes, but current CLIP methods are limited by challenging biochemical steps and fail to detect many classes of noncoding and nonhuman RNAs. Here we present FAST-iCLIP, an integrated pipeline with improved CLIP biochemistry and an automated informatic pipeline for comprehensive analysis across protein coding, noncoding, repetitive, retroviral, and nonhuman transcriptomes. FAST-iCLIP of Poly-C binding protein 2 (PCBP2) showed that PCBP2-bound CU-rich motifs in different topologies to recognize mRNAs and noncoding RNAs with distinct biological functions. FAST-iCLIP of PCBP2 in hepatitis C virus-infected cells enabled a joint analysis of the PCBP2 interactome with host and viral RNAs and their interplay. These results show that FAST-iCLIP can be used to rapidly discover and decipher mechanisms of RNA–protein recognition across the diversity of human and pathogen RNAs. PMID:25411354

  10. STPMiner: A Highperformance Spatiotemporal Pattern Mining Toolbox

    SciTech Connect

    Vatsavai, Raju

    2011-01-01

    The volume of spatiotemporal data being generated from scientific simulations and observations from sensors is growing at an astronomical rate. This data explosion is going to pose three challenges to the existing data mining infrastructure: algorithmic, computational, and I/O. Over the years we have implemented several spatiotemporal data mining algorithms including: outliers/anomalies, colocation patterns, change patterns, clustering, classification, and prediction algorithms. In this paper we briefly discuss the core spatiotemporal pattern mining algorithms along with some of the computational and I/O challenges associated with the big data.

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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...

  12. The extended pluripotency protein interactome and its links to reprogramming

    PubMed Central

    Huang, Xin; Wang, Jianlong

    2014-01-01

    A pluripotent state of embryonic stem cells (ESCs) and induced pluripotent stem cells (iPSCs) is maintained through the combinatorial activity of core transcriptional factors (TFs) such as Oct4, Sox2, and Nanog in conjunction with many other factors including epigenetic regulators. Proteins rarely act alone, and knowledge of protein-protein interaction network (interactome) provides an extraordinary resource about how pluripotency TFs collaborate and crosstalk with epigenetic regulators in ESCs. Recent advances in affinity purification coupled with mass spectrometry (AP-MS) allow for efficient, high-throughput identification of hundreds of interacting protein partners, which can be used to map the pluripotency landscape. Here we review recent publications employing AP-MS to investigate protein interaction networks in ESCs, discuss how protein-protein connections reveal novel pluripotency regulatory circuits and new factors for efficient reprogramming of somatic cells. PMID:25173149

  13. Chemical-protein interactome and its application in off-target identification.

    PubMed

    Yang, Lun; Wang, Ke-Jian; Wang, Li-Shan; Jegga, Anil G; Qin, Sheng-Ying; He, Guang; Chen, Jian; Xiao, Yue; He, Lin

    2011-03-01

    Drugs exert their therapeutic and adverse effects by interacting with molecular targets. Although designed to interact with specific targets in a desirable manner, drug molecules often bind to unexpected proteins (off-targets). By activating or inhibiting off-targets and the associated biological processes and pathways, the resulting chemical-protein interactions can influence drug reaction directly or indirectly. Exploring the relationship between drug and off-targets and the downstream drug reaction can help understand the polypharmacology of the drug, hence significantly advance the drug repositioning pipeline and the application of personalized medicine in understanding and preventing adverse drug reaction. This review summarizes works on predicting off-targets via chemical-protein interactome (CPI), an interaction strength matrix of drugs across multiple human proteins aiming at exploring the unexpected drug-protein interactions, with a variety of computational strategies, including docking, chemical structure comparison and text-mining etc. Effective recall on previous knowledge, de novo prediction and subsequent experimental validation conferred us strong confidence in these methods. Such studies present prospect of large scale in silico methodologies for off-target discovery with low cost and high efficiency. PMID:21369884

  14. Uncover disease genes by maximizing information flow in the phenome–interactome network

    PubMed Central

    Chen, Yong; Jiang, Tao; Jiang, Rui

    2011-01-01

    Motivation: Pinpointing genes that underlie human inherited diseases among candidate genes in susceptibility genetic regions is the primary step towards the understanding of pathogenesis of diseases. Although several probabilistic models have been proposed to prioritize candidate genes using phenotype similarities and protein–protein interactions, no combinatorial approaches have been proposed in the literature. Results: We propose the first combinatorial approach for prioritizing candidate genes. We first construct a phenome–interactome network by integrating the given phenotype similarity profile, protein–protein interaction network and associations between diseases and genes. Then, we introduce a computational method called MAXIF to maximize the information flow in this network for uncovering genes that underlie diseases. We demonstrate the effectiveness of this method in prioritizing candidate genes through a series of cross-validation experiments, and we show the possibility of using this method to identify diseases with which a query gene may be associated. We demonstrate the competitive performance of our method through a comparison with two existing state-of-the-art methods, and we analyze the robustness of our method with respect to the parameters involved. As an example application, we apply our method to predict driver genes in 50 copy number aberration regions of melanoma. Our method is not only able to identify several driver genes that have been reported in the literature, it also shed some new biological insights on the understanding of the modular property and transcriptional regulation scheme of these driver genes. Contact: ruijiang@tsinghua.edu.cn PMID:21685067

  15. The Membrane- and Soluble-Protein Helix-Helix Interactome: Similar Geometry via Different Interactions

    PubMed Central

    Zhang, Shao-Qing; Kulp, Daniel W.; Schramm, Chaim A.; Mravic, Marco; Samish, Ilan; DeGrado, William F.

    2015-01-01

    Summary Alpha-helices are a basic unit of protein secondary structure and therefore the interaction between helices is crucial to understanding tertiary and higher-order folds. Comparing subtle variations in the structural and sequence motifs between membrane and soluble proteins sheds light on the different constraints faced by each environment and elucidates the complex puzzle of membrane protein folding. Here, we demonstrate that membrane and water-soluble helix pairs share a small number of similar folds with various interhelical distances. The composition of the residues that pack at the interface between corresponding motifs shows that hydrophobic residues tend to be more enriched in the water-soluble class of structures and small residues in the transmembrane class. The latter group facilitates packing via sidechain- and backbone-mediated hydrogen bonds within the low-dielectric membrane milieu. The helix-helix interactome space, with its associated sequence preferences and accompanied hydrogen-bonding patterns, should be useful for protein structure engineering, prediction and design. PMID:25703378

  16. Calciomics: integrative studies of Ca2+-binding proteins and their interactomes in biological systems

    PubMed Central

    Zhou, Yubin; Xue, Shenghui; Yang, Jenny J.

    2013-01-01

    Calcium ion (Ca2+), the fifth most common chemical element in the earth’s crust, represents the most abundant mineral in the human body. By binding to a myriad of proteins distributed in different cellular organelles, Ca2+ impacts nearly every aspect of cellular life. In prokaryotes, Ca2+ plays an important role in bacterial movement, chemotaxis, survival reactions and sporulation. In eukaryotes, Ca2+ has been chosen through evolution to function as a universal and versatile intracellular signal. Viruses, as obligate intracellular parasites, also develop smart strategies to manipulate the host Ca2+ signaling machinery to benefit their own life cycles. This review focuses on recent advances in applying both bioinformatic and experimental approaches to predict and validate Ca2+-binding proteins and their interactomes in biological systems on genome-wide scale (termed “calciomics”). Calmodulin is used as an example of Ca2+-binding protein (CaBP) to demonstrate the role of CaBPs on the regulation of biological functions. This review is anticipated to rekindle interest in investigating Ca2+-binding proteins and Ca2+-modulated functions at the systems level in the post-genomic era. PMID:23235533

  17. Exploring Bacterial Organelle Interactomes: A Model of the Protein-Protein Interaction Network in the Pdu Microcompartment

    PubMed Central

    Jorda, Julien; Liu, Yu; Bobik, Thomas A.; Yeates, Todd O.

    2015-01-01

    Bacterial microcompartments (MCPs) are protein-bound organelles that carry out diverse metabolic pathways in a wide range of bacteria. These supramolecular assemblies consist of a thin outer protein shell, reminiscent of a viral capsid, which encapsulates sequentially acting enzymes. The most complex MCP elucidated so far is the propanediol utilizing (Pdu) microcompartment. It contains the reactions for degrading 1,2-propanediol. While several experimental studies on the Pdu system have provided hints about its organization, a clear picture of how all the individual components interact has not emerged yet. Here we use co-evolution-based methods, involving pairwise comparisons of protein phylogenetic trees, to predict the protein-protein interaction (PPI) network governing the assembly of the Pdu MCP. We propose a model of the Pdu interactome, from which selected PPIs are further inspected via computational docking simulations. We find that shell protein PduA is able to serve as a “universal hub” for targeting an array of enzymes presenting special N-terminal extensions, namely PduC, D, E, L and P. The varied N-terminal peptides are predicted to bind in the same cleft on the presumptive luminal face of the PduA hexamer. We also propose that PduV, a protein of unknown function with remote homology to the Ras-like GTPase superfamily, is likely to localize outside the MCP, interacting with the protruding β-barrel of the hexameric PduU shell protein. Preliminary experiments involving a bacterial two-hybrid assay are presented that corroborate the existence of a PduU-PduV interaction. This first systematic computational study aimed at characterizing the interactome of a bacterial microcompartment provides fresh insight into the organization of the Pdu MCP. PMID:25646976

  18. Interactome Analysis Reveals Ezrin Can Adopt Multiple Conformational States*

    PubMed Central

    Viswanatha, Raghuvir; Wayt, Jessica; Ohouo, Patrice Y.; Smolka, Marcus B.; Bretscher, Anthony

    2013-01-01

    Ezrin, a member of the ezrin-radixin-moesin family (ERM), is an essential regulator of the structure of microvilli on the apical aspect of epithelial cells. Ezrin provides a linkage between membrane-associated proteins and F-actin, oscillating between active/open and inactive/closed states, and is regulated in part by phosphorylation of a C-terminal threonine. In the open state, ezrin can bind a number of ligands, but in the closed state the ligand-binding sites are inaccessible. In vitro analysis has proposed that there may be a third hyperactivated form of ezrin. To gain a better understanding of ezrin, we conducted an unbiased proteomic analysis of ezrin-binding proteins in an epithelial cell line, Jeg-3. We refined our list of interactors by comparing the interactomes using quantitative mass spectrometry between wild-type ezrin, closed ezrin, open ezrin, and hyperactivated ezrin. The analysis reveals several novel interactors confirmed by their localization to microvilli, as well as a significant class of proteins that bind closed ezrin. Taken together, the data indicate that ezrin can exist in three different conformational states, and different ligands “perceive” ezrin conformational states differently. PMID:24151071

  19. Current Approaches Toward Quantitative Mapping of the Interactome

    PubMed Central

    Buntru, Alexander; Trepte, Philipp; Klockmeier, Konrad; Schnoegl, Sigrid; Wanker, Erich E.

    2016-01-01

    Protein–protein interactions (PPIs) play a key role in many, if not all, cellular processes. Disease is often caused by perturbation of PPIs, as recently indicated by studies of missense mutations. To understand the associations of proteins and to unravel the global picture of PPIs in the cell, different experimental detection techniques for PPIs have been established. Genetic and biochemical methods such as the yeast two-hybrid system or affinity purification-based approaches are well suited to high-throughput, proteome-wide screening and are mainly used to obtain qualitative results. However, they have been criticized for not reflecting the cellular situation or the dynamic nature of PPIs. In this review, we provide an overview of various genetic methods that go beyond qualitative detection and allow quantitative measuring of PPIs in mammalian cells, such as dual luminescence-based co-immunoprecipitation, Förster resonance energy transfer or luminescence-based mammalian interactome mapping with bait control. We discuss the strengths and weaknesses of different techniques and their potential applications in biomedical research. PMID:27200083

  20. SInCRe-structural interactome computational resource for Mycobacterium tuberculosis.

    PubMed

    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. PMID:26130660

  1. 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

  2. Transcriptional atlas of cardiogenesis maps congenital heart disease interactome

    PubMed Central

    Li, Xing; Martinez-Fernandez, Almudena; Hartjes, Katherine A.; Kocher, Jean-Pierre A.; Olson, Timothy M.; Terzic, Andre

    2014-01-01

    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. PMID:24803680

  3. Identifying Unexpected Therapeutic Targets via Chemical-Protein Interactome

    PubMed Central

    Yang, Lun; Chen, Jian; Shi, Leming; Hudock, Michael P.; Wang, Kejian; He, Lin

    2010-01-01

    Drug medications inevitably affect not only their intended protein targets but also other proteins as well. In this study we examined the hypothesis that drugs that share the same therapeutic effect also share a common therapeutic mechanism by targeting not only known drug targets, but also by interacting unexpectedly on the same cryptic targets. By constructing and mining an Alzheimer's disease (AD) drug-oriented chemical-protein interactome (CPI) using a matrix of 10 drug molecules known to treat AD towards 401 human protein pockets, we found that such cryptic targets exist. We recovered from CPI the only validated therapeutic target of AD, acetylcholinesterase (ACHE), and highlighted several other putative targets. For example, we discovered that estrogen receptor (ER) and histone deacetylase (HDAC), which have recently been identified as two new therapeutic targets of AD, might already have been targeted by the marketed AD drugs. We further established that the CPI profile of a drug can reflect its interacting character towards multi-protein sets, and that drugs with the same therapeutic attribute will share a similar interacting profile. These findings indicate that the CPI could represent the landscape of chemical-protein interactions and uncover behind-the-scenes aspects of the therapeutic mechanisms of existing drugs, providing testable hypotheses of the key nodes for network pharmacology or brand new drug targets for one-target pharmacology paradigm. PMID:20221449

  4. CTCF-Mediated Functional Chromatin Interactome in Pluripotent Cells

    PubMed Central

    Handoko, Lusy; Xu, Han; Li, Guoliang; Ngan, Chew Yee; Chew, Elaine; Schnapp, Marie; Lee, Charlie Wah Heng; Ye, Chaopeng; Ping, Joanne Lim Hui; Mulawadi, Fabianus; Wong, Eleanor; Sheng, Jianpeng; Zhang, Yubo; Poh, Thompson; Chan, Chee Seng; Kunarso, Galih; Shahab, Atif; Bourque, Guillaume; Cacheux-Rataboul, Valere; Sung, Wing-Kin; Ruan, Yijun; Wei, Chia-Lin

    2011-01-01

    Mammalian genomes are viewed as functional organizations that orchestrate spatial and temporal gene regulation. CTCF, the most characterized insulator-binding protein, has been implicated as a key genome organizer. Yet, little is known about CTCF-associated higher order chromatin structures at a global scale. Here, we applied Chromatin Interaction Analysis by Paired-End-Tag sequencing to elucidate the CTCF-chromatin interactome in pluripotent cells. From this analysis, 1,480 cis and 336 trans interacting loci were identified with high reproducibility and precision. Associating these chromatin interaction loci with their underlying epigenetic states, promoter activities, enhancer binding and nuclear lamina occupancy, we uncovered five distinct chromatin domains that suggest potential new models of CTCF function in chromatin organization and transcriptional control. Specifically, CTCF interactions demarcate chromatin-nuclear membrane attachments and influence proper gene expression through extensive crosstalk between promoters and regulatory elements. This highly complex nuclear organization offers insights towards the unifying principles governing genome plasticity and function. PMID:21685913

  5. Interactomic and Pharmacological Insights on Human Sirt-1

    PubMed Central

    Sharma, Ankush; Gautam, Vasu; Costantini, Susan; Paladino, Antonella; Colonna, Giovanni

    2012-01-01

    Sirt-1 is defined as a nuclear protein involved in the molecular mechanisms of inflammation and neurodegeneration through the de-acetylation of many different substrates even if experimental data in mouse suggest both its cytoplasmatic presence and nucleo-cytoplasmic shuttling upon oxidative stress. Since the experimental structure of human Sirt-1 has not yet been reported, we have modeled its 3D structure, highlighted that it is composed by four different structural regions: N-terminal region, allosteric site, catalytic core and C-terminal region, and underlined that the two terminal regions have high intrinsic disorder propensity and numerous putative phosphorylation sites. Many different papers report experimental studies related to its functional activators because Sirt-1 is implicated in various diseases and cancers. The aim of this article is (i) to present interactomic studies based human Sirt-1 to understand its most important functional relationships in the light of the gene–protein interactions that control major metabolic pathways and (ii) to show by docking studies how this protein binds some activator molecules in order to evidence structural determinants, physico-chemical features and those residues involved in the formation of complexes. PMID:22470339

  6. Neurodevelopmental disorders: mechanisms and boundary definitions from genomes, interactomes and proteomes

    PubMed Central

    Mullin, A P; Gokhale, A; Moreno-De-Luca, A; Sanyal, S; Waddington, J L; Faundez, V

    2013-01-01

    Neurodevelopmental disorders such as intellectual disability, autism spectrum disorder and schizophrenia lack precise boundaries in their clinical definitions, epidemiology, genetics and protein–protein interactomes. This calls into question the appropriateness of current categorical disease concepts. Recently, there has been a rising tide to reformulate neurodevelopmental nosological entities from biology upward. To facilitate this developing trend, we propose that identification of unique proteomic signatures that can be strongly associated with patient's risk alleles and proteome-interactome-guided exploration of patient genomes could define biological mechanisms necessary to reformulate disorder definitions. PMID:24301647

  7. Forward Individualized Medicine from Personal Genomes to Interactomes

    PubMed Central

    Zhang, Xiang; Kuivenhoven, Jan A.; Groen, Albert K.

    2015-01-01

    When considering the variation in the genome, transcriptome, proteome and metabolome, and their interaction with the environment, every individual can be rightfully considered as a unique biological entity. Individualized medicine promises to take this uniqueness into account to optimize disease treatment and thereby improve health benefits for every patient. The success of individualized medicine relies on a precise understanding of the genotype-phenotype relationship. Although omics technologies advance rapidly, there are several challenges that need to be overcome: Next generation sequencing can efficiently decipher genomic sequences, epigenetic changes, and transcriptomic variation in patients, but it does not automatically indicate how or whether the identified variation will cause pathological changes. This is likely due to the inability to account for (1) the consequences of gene-gene and gene-environment interactions, and (2) (post)transcriptional as well as (post)translational processes that eventually determine the concentration of key metabolites. The technologies to accurately measure changes in these latter layers are still under development, and such measurements in humans are also mainly restricted to blood and circulating cells. Despite these challenges, it is already possible to track dynamic changes in the human interactome in healthy and diseased states by using the integration of multi-omics data. In this review, we evaluate the potential value of current major bioinformatics and systems biology-based approaches, including genome wide association studies, epigenetics, gene regulatory and protein-protein interaction networks, and genome-scale metabolic modeling. Moreover, we address the question whether integrative analysis of personal multi-omics data will help understanding of personal genotype-phenotype relationships. PMID:26696898

  8. Forward Individualized Medicine from Personal Genomes to Interactomes.

    PubMed

    Zhang, Xiang; Kuivenhoven, Jan A; Groen, Albert K

    2015-01-01

    When considering the variation in the genome, transcriptome, proteome and metabolome, and their interaction with the environment, every individual can be rightfully considered as a unique biological entity. Individualized medicine promises to take this uniqueness into account to optimize disease treatment and thereby improve health benefits for every patient. The success of individualized medicine relies on a precise understanding of the genotype-phenotype relationship. Although omics technologies advance rapidly, there are several challenges that need to be overcome: Next generation sequencing can efficiently decipher genomic sequences, epigenetic changes, and transcriptomic variation in patients, but it does not automatically indicate how or whether the identified variation will cause pathological changes. This is likely due to the inability to account for (1) the consequences of gene-gene and gene-environment interactions, and (2) (post)transcriptional as well as (post)translational processes that eventually determine the concentration of key metabolites. The technologies to accurately measure changes in these latter layers are still under development, and such measurements in humans are also mainly restricted to blood and circulating cells. Despite these challenges, it is already possible to track dynamic changes in the human interactome in healthy and diseased states by using the integration of multi-omics data. In this review, we evaluate the potential value of current major bioinformatics and systems biology-based approaches, including genome wide association studies, epigenetics, gene regulatory and protein-protein interaction networks, and genome-scale metabolic modeling. Moreover, we address the question whether integrative analysis of personal multi-omics data will help understanding of personal genotype-phenotype relationships. PMID:26696898

  9. Exploring a Structural Protein-Drug Interactome for New Therapeutics in Lung Cancer

    PubMed Central

    Peng, Xiaodong; Wang, Fang; Li, Liwei; Bum-Erdene, Khuchtumur; Xu, David; Wang, Bo; Sinn, Tony; Pollok, Karen; Sandusky, George; Li, Lang; Turchi, John; Jalal, Shadia I.; Meroueh, Samy

    2014-01-01

    The pharmacology of drugs is often defined by more than one protein target. This property can be exploited to use approved drugs to uncover new targets and signaling pathways in cancer. Towards enabling a rational approach to uncover new targets, we expand a structural protein-ligand interactome (http://www.biodrugscreen.org) by scoring the interaction among 1,000 FDA-approved drugs docked to 2,500 pockets on protein structures of the human genome. This afforded a drug-target network whose properties compared favorably with previous networks constructed with experimental data. Among drugs with highest degree and betweenness two are cancer drugs and one is currently used for treatment of lung cancer. Comparison of predicted cancer and non-cancer targets reveals that the most cancer-specific compounds were also the most selective compounds. Analysis of compound flexibility, hydrophobicity, and size showed that the most selective compounds were low molecular weight fragment-like heterocycles. We use a previously-developed screening approach using the cancer drug erlotinib as a template to screen other approved drugs that mimic its properties. Among the top 12 ranking candidates, four are cancer drugs, two of them kinase inhibitors (like erlotinib). Cellular studies using non-small cell lung cancer (NSCLC) cells revealed that several drugs inhibited lung cancer cell proliferation. We mined patient records at the Regenstrief Medical Record System to explore possible association of exposure to three of these drugs with occurrence of lung cancer. Preliminary in vivo studies using non-small cell lung cancer (NCLSC) xenograft model showed that losartan- and astemizole-treated mice had tumors that weighed 50 (p < 0.01) and 15 (p < 0.01) percent less than vehicle. These results set the stage for further exploration of these drugs and to uncover new drugs for lung cancer. PMID:24402119

  10. 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.

  11. 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

    2015-01-01

    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

  12. ΔF508 CFTR interactome remodeling promotes rescue of Cystic Fibrosis

    PubMed Central

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

    2015-01-01

    Summary Deletion of phenylalanine 508 of the Cystic Fibrosis Transmembrane Conductance Regulator (CFTR) is the major cause of Cystic Fibrosis (CF), 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 CF patients. Low temperature or inhibition of histone deacetylases (HDACi) can partially rescue ΔF508 CFTR cellular processing defects and function. A favorable change of ΔF508 CFTR protein-protein interactions was proposed as mechanism of rescue, however CFTR interactome dynamics during temperature-shift and HDACi rescue are unknown. Here, we report the first comprehensive analysis of the wt and ΔF508 CFTR interactome and its dynamics during temperature shift and HDACi. By using a novel deep proteomic analysis method (CoPIT), we identified 638 individual high-confidence CFTR interactors and discovered a mutation-specific interactome, which is extensively remodeled upon rescue. Detailed analysis of the interactome remodeling identified key novel interactors, whose loss promoted enhanced CFTR channel function in primary CF epithelia or which were critical for normal CFTR biogenesis. Our results demonstrate that global remodeling of ΔF508 CFTR interactions is crucial for rescue, and provide comprehensive insight into the molecular disease mechanisms of CF caused by deletion of F508. PMID:26618866

  13. 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. PMID:26426291

  14. 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

  15. 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

  16. ∆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. PMID:26618866

  17. 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. PMID:23696811

  18. Human transcriptional interactome of chromatin contribute to gene co-expression

    PubMed Central

    2010-01-01

    Background Transcriptional interactome of chromatin is one of the important mechanisms in gene transcription regulation. By chromatin conformation capture and 3D FISH experiments, several chromatin interactions cases among sequence-distant genes or even inter-chromatin genes were reported. However, on genomics level, there is still little evidence to support these mechanisms. Recently based on Hi-C experiment, a genome-wide picture of chromatin interactions in human cells was presented. It provides a useful material for analysing whether the mechanism of transcriptional interactome is common. Results The main work here is to demonstrate whether the effects of transcriptional interactome on gene co-expression exist on genomic level. While controlling the effects of transcription factors control similarities (TCS), we tested the correlation between Hi-C interaction and the mutual ranks of gene co-expression rates (provided by COXPRESdb) of intra-chromatin gene pairs. We used 6,084 genes with both TF annotation and co-expression information, and matched them into 273,458 pairs with similar Hi-C interaction ranks in different cell types. The results illustrate that co-expression is strongly associated with chromatin interaction. Further analysis using GO annotation reveals potential correlation between gene function similarity, Hi-C interaction and their co-expression. Conclusions According to the results in this research, the intra-chromatin interactome may have relation to gene function and associate with co-expression. This study provides evidence for illustrating the effect of transcriptional interactome on transcription regulation. PMID:21156067

  19. Integrating the interactome and the transcriptome of Drosophila

    PubMed Central

    2014-01-01

    Background Networks of interacting genes and gene products mediate most cellular and developmental processes. High throughput screening methods combined with literature curation are identifying many of the protein-protein interactions (PPI) and protein-DNA interactions (PDI) that constitute these networks. Most of the detection methods, however, fail to identify the in vivo spatial or temporal context of the interactions. Thus, the interaction data are a composite of the individual networks that may operate in specific tissues or developmental stages. Genome-wide expression data may be useful for filtering interaction data to identify the subnetworks that operate in specific spatial or temporal contexts. Here we take advantage of the extensive interaction and expression data available for Drosophila to analyze how interaction networks may be unique to specific tissues and developmental stages. Results We ranked genes on a scale from ubiquitously expressed to tissue or stage specific and examined their interaction patterns. Interestingly, ubiquitously expressed genes have many more interactions among themselves than do non-ubiquitously expressed genes both in PPI and PDI networks. While the PDI network is enriched for interactions between tissue-specific transcription factors and their tissue-specific targets, a preponderance of the PDI interactions are between ubiquitous and non-ubiquitously expressed genes and proteins. In contrast to PDI, PPI networks are depleted for interactions among tissue- or stage- specific proteins, which instead interact primarily with widely expressed proteins. In light of these findings, we present an approach to filter interaction data based on gene expression levels normalized across tissues or developmental stages. We show that this filter (the percent maximum or pmax filter) can be used to identify subnetworks that function within individual tissues or developmental stages. Conclusions These observations suggest that protein networks are frequently organized into hubs of widely expressed proteins to which are attached various tissue- or stage-specific proteins. This is consistent with earlier analyses of human PPI data and suggests a similar organization of interaction networks across species. This organization implies that tissue or stage specific networks can be best identified from interactome data by using filters designed to include both ubiquitously expressed and specifically expressed genes and proteins. PMID:24913703

  20. An integrative network algorithm identifies age-associated differential methylation interactome hotspots targeting stem-cell differentiation pathways

    PubMed Central

    West, James; Beck, Stephan; Wang, Xiangdong; Teschendorff, Andrew E.

    2013-01-01

    Epigenetic changes have been associated with ageing and cancer. Identifying and interpreting epigenetic changes associated with such phenotypes may benefit from integration with protein interactome models. We here develop and validate a novel integrative epigenome-interactome approach to identify differential methylation interactome hotspots associated with a phenotype of interest. We apply the algorithm to cancer and ageing, demonstrating the existence of hotspots associated with these phenotypes. Importantly, we discover tissue independent age-associated hotspots targeting stem-cell differentiation pathways, which we validate in independent DNA methylation data sets, encompassing over 1000 samples from different tissue types. We further show that these pathways would not have been discovered had we used a non-network based approach and that the use of the protein interaction network improves the overall robustness of the inference procedure. The proposed algorithm will be useful to any study seeking to identify interactome hotspots associated with common phenotypes. PMID:23568264

  1. Spatio-temporal variability in Ebro river basin (NE Spain): Global SST as potential source of predictability on decadal time scales

    NASA Astrophysics Data System (ADS)

    Gámiz-Fortis, S. R.; Hidalgo-Muñoz, J. M.; Argüeso, D.; Esteban-Parra, M. J.; Castro-Díez, Y.

    2011-11-01

    SummaryThis paper investigates the spatial and temporal variability of streamflow in the Ebro river basin and its potential predictability. Principal Component Analysis applied to monthly streamflow series from 83 gauging stations distributed through the basin, reveals three homogeneous regions: Basque-Cantabrian, Pyrenees and Southern Mediterranean. Attending to this classification the main characteristic time scales of the maximum monthly streamflows are studied by Singular Spectral Analysis (SSA). Decadal variations in streamflow make particularly large contributions to year-to-year streamflow variance in stations placed in the Basque-Cantabrian and Southern Mediterranean regions, while for the Pyrenees flows the interannual contribution is more important. The predictability of the Ebro flow anomalies has been investigated using a combined methodology: at decadal time scales SST anomalies from several regions provide a significant source of predictability for the Ebro flow, while at interannual time scales autoregressive-moving-average modelling, applied to the time series previously filtered by SSA, is able to provide potential skill in forecasting. For gauging stations associated to the Basque-Cantabrian region significant correlations between the maximum monthly streamflow anomalies and a tripole-like pattern in the North Atlantic SSTs during the previous spring are found. This association is found maximum and stable for the tropical part of the pattern (approximately 0-20°N). For the gauging stations placed to the southeast of basin some influence from the Pacific Decadal Oscillation (PDO) is found. This method allows evaluating, independently, the decadal and interannual predictability of the streamflow series. In addition, the combination of both modelling techniques gives as result a methodology that has the capacity to provide basin-specific hydroclimatic predictions which vary (for the 1990-2003 validation period) between 62% for the Basque-Cantabrian region, 76% for the Southern Mediterranean and 81% for the Pyrenees. In summary, this work shows the existence of a valuable decadal and interannual predictability of the Ebro streamflow, a result which may be useful to water resources management.

  2. Computer vision profiling of neurite outgrowth dynamics reveals spatiotemporal modularity of Rho GTPase signaling.

    PubMed

    Fusco, Ludovico; Lefort, Riwal; Smith, Kevin; Benmansour, Fethallah; Gonzalez, German; Barillari, Caterina; Rinn, Bernd; Fleuret, Francois; Fua, Pascal; Pertz, Olivier

    2016-01-01

    Rho guanosine triphosphatases (GTPases) control the cytoskeletal dynamics that power neurite outgrowth. This process consists of dynamic neurite initiation, elongation, retraction, and branching cycles that are likely to be regulated by specific spatiotemporal signaling networks, which cannot be resolved with static, steady-state assays. We present NeuriteTracker, a computer-vision approach to automatically segment and track neuronal morphodynamics in time-lapse datasets. Feature extraction then quantifies dynamic neurite outgrowth phenotypes. We identify a set of stereotypic neurite outgrowth morphodynamic behaviors in a cultured neuronal cell system. Systematic RNA interference perturbation of a Rho GTPase interactome consisting of 219 proteins reveals a limited set of morphodynamic phenotypes. As proof of concept, we show that loss of function of two distinct RhoA-specific GTPase-activating proteins (GAPs) leads to opposite neurite outgrowth phenotypes. Imaging of RhoA activation dynamics indicates that both GAPs regulate different spatiotemporal Rho GTPase pools, with distinct functions. Our results provide a starting point to dissect spatiotemporal Rho GTPase signaling networks that regulate neurite outgrowth. PMID:26728857

  3. Proteomics, metabolomics, and protein interactomics in the characterization of the molecular features of major depressive disorder

    PubMed Central

    Martins-de-Souza, Daniel

    2014-01-01

    Omics technologies emerged as complementary strategies to genomics in the attempt to understand human illnesses. In general, proteomics technologies emerged earlier than those of metabolomics for major depressive disorder (MDD) research, but both are driven by the identification of proteins and/or metabolites that can delineate a comprehensive characterization of MDD's molecular mechanisms, as well as lead to the identification of biomarker candidates of all types—prognosis, diagnosis, treatment, and patient stratification. Also, one can explore protein and metabolite interactomes in order to pinpoint additional molecules associated with the disease that had not been picked up initially. Here, results and methodological aspects of MDD research using proteomics, metabolomics, and protein interactomics are reviewed, focusing on human samples. PMID:24733971

  4. Integrating Genomic, Transcriptomic, and Interactome Data to Improve Peptide and Protein Identification in Shotgun Proteomics

    PubMed Central

    2015-01-01

    Mass spectrometry (MS)-based shotgun proteomics is an effective technology for global proteome profiling. The ultimate goal is to assign tandem MS spectra to peptides and subsequently infer proteins and their abundance. In addition to database searching and protein assembly algorithms, computational approaches have been developed to integrate genomic, transcriptomic, and interactome information to improve peptide and protein identification. Earlier efforts focus primarily on making databases more comprehensive using publicly available genomic and transcriptomic data. More recently, with the increasing affordability of the Next Generation Sequencing (NGS) technologies, personalized protein databases derived from sample-specific genomic and transcriptomic data have emerged as an attractive strategy. In addition, incorporating interactome data not only improves protein identification but also puts identified proteins into their functional context and thus facilitates data interpretation. In this paper, we survey the major integrative bioinformatics approaches that have been developed during the past decade and discuss their merits and demerits. PMID:24792918

  5. Spatiotemporal multipartite entanglement

    SciTech Connect

    Kolobov, Mikhail I.; Patera, Giuseppe

    2011-05-15

    In this Rapid Communication, we propose, following the spirit of quantum imaging, to generalize the theory of multipartite entanglement for the continuous-variable Gaussian states by considering, instead of the global covariance matrix, the local correlation matrix at two different spatiotemporal points ({rho}-vector,t) and ({rho}-vector{sup '},t{sup '}), with {rho}-vector being the transverse coordinate. Our approach makes it possible to introduce the characteristic spatial length and the characteristic time of the multipartite entanglement, which in general depend on the number of 'parties' in the system. As an example, we consider tripartite entanglement in spontaneous parametric down-conversion with a spatially structured pump. We investigate spatiotemporal properties of such entanglement and calculate its characteristic spatial length and time.

  6. A Flexible Spatio-Temporal Model for Air Pollution with Spatial and Spatio-Temporal Covariates

    PubMed Central

    Lindström, Johan; Szpiro, Adam A; Sampson, Paul D; Oron, Assaf P; Richards, Mark; Larson, Tim V; Sheppard, Lianne

    2013-01-01

    The development of models that provide accurate spatio-temporal predictions of ambient air pollution at small spatial scales is of great importance for the assessment of potential health effects of air pollution. Here we present a spatio-temporal framework that predicts ambient air pollution by combining data from several different monitoring networks and deterministic air pollution model(s) with geographic information system (GIS) covariates. The model presented in this paper has been implemented in an R package, SpatioTemporal, available on CRAN. The model is used by the EPA funded Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air) to produce estimates of ambient air pollution; MESA Air uses the estimates to investigate the relationship between chronic exposure to air pollution and cardiovascular disease. In this paper we use the model to predict long-term average concentrations of NOx in the Los Angeles area during a ten year period. Predictions are based on measurements from the EPA Air Quality System, MESA Air specific monitoring, and output from a source dispersion model for traffic related air pollution (Caline3QHCR). Accuracy in predicting long-term average concentrations is evaluated using an elaborate cross-validation setup that accounts for a sparse spatio-temporal sampling pattern in the data, and adjusts for temporal effects. The predictive ability of the model is good with cross-validated R2 of approximately 0.7 at subject sites. Replacing four geographic covariate indicators of traffic density with the Caline3QHCR dispersion model output resulted in very similar prediction accuracy from a more parsimonious and more interpretable model. Adding traffic-related geographic covariates to the model that included Caline3QHCR did not further improve the prediction accuracy. PMID:25264424

  7. A Flexible Spatio-Temporal Model for Air Pollution with Spatial and Spatio-Temporal Covariates.

    PubMed

    Lindström, Johan; Szpiro, Adam A; Sampson, Paul D; Oron, Assaf P; Richards, Mark; Larson, Tim V; Sheppard, Lianne

    2014-09-01

    The development of models that provide accurate spatio-temporal predictions of ambient air pollution at small spatial scales is of great importance for the assessment of potential health effects of air pollution. Here we present a spatio-temporal framework that predicts ambient air pollution by combining data from several different monitoring networks and deterministic air pollution model(s) with geographic information system (GIS) covariates. The model presented in this paper has been implemented in an R package, SpatioTemporal, available on CRAN. The model is used by the EPA funded Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air) to produce estimates of ambient air pollution; MESA Air uses the estimates to investigate the relationship between chronic exposure to air pollution and cardiovascular disease. In this paper we use the model to predict long-term average concentrations of NOx in the Los Angeles area during a ten year period. Predictions are based on measurements from the EPA Air Quality System, MESA Air specific monitoring, and output from a source dispersion model for traffic related air pollution (Caline3QHCR). Accuracy in predicting long-term average concentrations is evaluated using an elaborate cross-validation setup that accounts for a sparse spatio-temporal sampling pattern in the data, and adjusts for temporal effects. The predictive ability of the model is good with cross-validated R (2) of approximately 0.7 at subject sites. Replacing four geographic covariate indicators of traffic density with the Caline3QHCR dispersion model output resulted in very similar prediction accuracy from a more parsimonious and more interpretable model. Adding traffic-related geographic covariates to the model that included Caline3QHCR did not further improve the prediction accuracy. PMID:25264424

  8. Hubba: hub objects analyzer--a framework of interactome hubs identification for network biology.

    PubMed

    Lin, Chung-Yen; Chin, Chia-Hao; Wu, Hsin-Hung; Chen, Shu-Hwa; Ho, Chin-Wen; Ko, Ming-Tat

    2008-07-01

    One major task in the post-genome era is to reconstruct proteomic and genomic interacting networks using high-throughput experiment data. To identify essential nodes/hubs in these interactomes is a way to decipher the critical keys inside biochemical pathways or complex networks. These essential nodes/hubs may serve as potential drug-targets for developing novel therapy of human diseases, such as cancer or infectious disease caused by emerging pathogens. Hub Objects Analyzer (Hubba) is a web-based service for exploring important nodes in an interactome network generated from specific small- or large-scale experimental methods based on graph theory. Two characteristic analysis algorithms, Maximum Neighborhood Component (MNC) and Density of Maximum Neighborhood Component (DMNC) are developed for exploring and identifying hubs/essential nodes from interactome networks. Users can submit their own interaction data in PSI format (Proteomics Standards Initiative, version 2.5 and 1.0), tab format and tab with weight values. User will get an email notification of the calculation complete in minutes or hours, depending on the size of submitted dataset. Hubba result includes a rank given by a composite index, a manifest graph of network to show the relationship amid these hubs, and links for retrieving output files. This proposed method (DMNC || MNC) can be applied to discover some unrecognized hubs from previous dataset. For example, most of the Hubba high-ranked hubs (80% in top 10 hub list, and >70% in top 40 hub list) from the yeast protein interactome data (Y2H experiment) are reported as essential proteins. Since the analysis methods of Hubba are based on topology, it can also be used on other kinds of networks to explore the essential nodes, like networks in yeast, rat, mouse and human. The website of Hubba is freely available at http://hub.iis.sinica.edu.tw/Hubba. PMID:18503085

  9. Spatiotemporal instability of a confined capillary jet.

    PubMed

    Herrada, M A; Gañán-Calvo, A M; Guillot, P

    2008-10-01

    Recent experimental studies on the instability of capillary jets have revealed the suitability of a linear spatiotemporal instability analysis to ascertain the parametrical conditions for specific flow regimes such as steady jetting or dripping. In this work, an extensive analytical, numerical, and experimental description of confined capillary jets is provided, leading to an integrated picture both in terms of data and interpretation. We propose an extended, accurate analytic model in the low Reynolds number limit, and introduce a numerical scheme to predict the system response when the liquid inertia is not negligible. Theoretical predictions show remarkable accuracy when compared with the extensive experimental mapping. PMID:18999531

  10. Impaired autophagy and APP processing in Alzheimer's disease: The potential role of Beclin 1 interactome.

    PubMed

    Salminen, Antero; Kaarniranta, Kai; Kauppinen, Anu; Ojala, Johanna; Haapasalo, Annakaisa; Soininen, Hilkka; Hiltunen, Mikko

    2013-01-01

    The accumulation of amyloid-β-containing neuritic plaques and intracellular tau protein tangles are key histopathological hallmarks of Alzheimer's disease (AD). This type of pathology clearly indicates that the mechanisms of neuronal housekeeping and protein quality control are compromised in AD. There is mounting evidence that the autophagosome-lysosomal degradation is impaired, which could disturb the processing of APP and provoke AD pathology. Beclin 1 is a molecular platform assembling an interactome with stimulating and suppressive components which regulate the initiation of the autophagosome formation. Recent studies have indicated that the expression Beclin 1 is reduced in AD brain. Moreover, the deficiency of Beclin 1 in cultured neurons and transgenic mice provokes the deposition of amyloid-β peptides whereas its overexpression reduces the accumulation of amyloid-β. There are several potential mechanisms, which could inhibit the function of Beclin 1 interactome and thus impair autophagy and promote AD pathology. The mechanisms include (i) reduction of Beclin 1 expression or its increased proteolytic cleavage by caspases, (ii) sequestration of Beclin 1 to non-functional locations, such as tau tangles, (iii) formation of inhibitory complexes between Beclin 1 and antiapoptotic Bcl-2 proteins or inflammasomes, (iv) interaction of Beclin 1 with inhibitory neurovirulent proteins, e.g. herpex simplex ICP34.5, or (v) inhibition of the Beclin 1/Vps34 complex through the activation of CDK1 and CDK5. We will shortly introduce the function of Beclin 1 interactome in autophagy and phagocytosis, review the recent evidence indicating that Beclin 1 regulates autophagy and APP processing in AD, and finally examine the potential mechanisms through which Beclin 1 dysfunction could be involved in the pathogenesis of AD. PMID:23827971

  11. Indeterminacy of Spatiotemporal Cardiac Alternans

    PubMed Central

    Zhao, Xiaopeng

    2008-01-01

    Cardiac alternans, a beat-to-beat alternation in action potential duration (at the cellular level) or in ECG morphology (at the whole heart level), is a marker of ventricular fibrillation, a fatal heart rhythm that kills hundreds of thousands of people in the US each year. Investigating cardiac alternans may lead to a better understanding of the mechanisms of cardiac arrhythmias and eventually better algorithms for the prediction and prevention of such dreadful diseases. In paced cardiac tissue, alternans develops under increasingly shorter pacing period. Existing experimental and theoretical studies adopt the assumption that alternans in homogeneous cardiac tissue is exclusively determined by the pacing period. In contrast, we find that, when calcium-driven alternans develops in cardiac fibers, it may take different spatiotemporal patterns depending on the pacing history. Because there coexist multiple alternans solutions for a given pacing period, the alternans pattern on a fiber becomes unpredictable. Using numerical simulation and theoretical analysis, we show that the coexistence of multiple alternans patterns is induced by the interaction between electrotonic coupling and an instability in calcium cycling. PMID:18763977

  12. Feature Selection, Flaring Size and Time-to-Flare Prediction Using Support Vector Regression, and Automated Prediction of Flaring Behavior Based on Spatio-Temporal Measures Using Hidden Markov Models

    NASA Astrophysics Data System (ADS)

    Al-Ghraibah, Amani

    Solar flares release stored magnetic energy in the form of radiation and can have significant detrimental effects on earth including damage to technological infrastructure. Recent work has considered methods to predict future flare activity on the basis of quantitative measures of the solar magnetic field. Accurate advanced warning of solar flare occurrence is an area of increasing concern and much research is ongoing in this area. Our previous work 111] utilized standard pattern recognition and classification techniques to determine (classify) whether a region is expected to flare within a predictive time window, using a Relevance Vector Machine (RVM) classification method. We extracted 38 features which describing the complexity of the photospheric magnetic field, the result classification metrics will provide the baseline against which we compare our new work. We find a true positive rate (TPR) of 0.8, true negative rate (TNR) of 0.7, and true skill score (TSS) of 0.49. This dissertation proposes three basic topics; the first topic is an extension to our previous work [111, where we consider a feature selection method to determine an appropriate feature subset with cross validation classification based on a histogram analysis of selected features. Classification using the top five features resulting from this analysis yield better classification accuracies across a large unbalanced dataset. In particular, the feature subsets provide better discrimination of the many regions that flare where we find a TPR of 0.85, a TNR of 0.65 sightly lower than our previous work, and a TSS of 0.5 which has an improvement comparing with our previous work. In the second topic, we study the prediction of solar flare size and time-to-flare using support vector regression (SVR). When we consider flaring regions only, we find an average error in estimating flare size of approximately half a GOES class. When we additionally consider non-flaring regions, we find an increased average error of approximately 3/4 a GOES class. We also consider thresholding the regressed flare size for the experiment containing both flaring and non-flaring regions and find a TPR. of 0.69 and a TNR of 0.86 for flare prediction, consistent with our previous studies of flare prediction using the same magnetic complexity features. The results for both of these size regression experiments are consistent across a wide range of predictive time windows, indicating that the magnetic complexity features may be persistent in appearance long before flare activity. This conjecture is supported by our larger error rates of some 40 hours in the time-to-flare regression problem. The magnetic complexity features considered here appear to have discriminative potential for flare size, but their persistence in time makes them less discriminative for the time-to-flare problem. We also study the prediction of solar flare size and time-to-flare using two temporal features, namely the ▵- and ▵-▵-features, the same average size and time-to-flare regression error are found when these temporal features are used in size and time-to-flare prediction. In the third topic, we study the temporal evolution of active region magnetic fields using Hidden Markov Models (HMMs) which is one of the efficient temporal analyses found in literature. We extracted 38 features which describing the complexity of the photospheric magnetic field. These features are converted into a sequence of symbols using k-nearest neighbor search method. We study many parameters before prediction; like the length of the training window Wtrain which denotes to the number of history images use to train the flare and non-flare HMMs, and number of hidden states Q. In training phase, the model parameters of the HMM of each category are optimized so as to best describe the training symbol sequences. In testing phase, we use the best flare and non-flare models to predict/classify active regions as a flaring or non-flaring region using a sliding window method. The best prediction result is found where the length of the history training images are 15 images (i.e., Wtrain= 15) and the length of the sliding testing window is less than or equal to W train, the best result give a TPR of 0.79 consistent with previous flare prediction work, TNR of 0.87 arid TSS of 0.66, where both are higher than our previous flare prediction work. We find that the best number of hidden states which can describe the temporal evolution of the solar ARs is equal to five states, at the same time, a close resultant metrics are found using different number of states.

  13. Spatiotemporal characteristics of pandemic influenza

    PubMed Central

    2014-01-01

    Background Prediction of timing for the onset and peak of an influenza pandemic is of vital importance for preventive measures. In order to identify common spatiotemporal patterns and climate influences for pandemics in Sweden we have studied the propagation in space and time of A(H1N1)pdm09 (10,000 laboratory verified cases), the Asian Influenza 1957–1958 (275,000 cases of influenza-like illness (ILI), reported by local physicians) and the Russian Influenza 1889–1890 (32,600 ILI cases reported by physicians shortly after the end of the outbreak). Methods All cases were geocoded and analysed in space and time. Animated video sequences, showing weekly incidence per municipality and its geographically weighted mean (GWM), were created to depict and compare the spread of the pandemics. Daily data from 1957–1958 on temperature and precipitation from 39 weather stations were collected and analysed with the case data to examine possible climatological effects on the influenza dissemination. Results The epidemic period lasted 11 weeks for the Russian Influenza, 10 weeks for the Asian Influenza and 9 weeks for the A(H1N1)pdm09. The Russian Influenza arrived in Sweden during the winter and was immediately disseminated, while both the Asian Influenza and the A(H1N1)pdm09 arrived during the spring. They were seeded over the country during the summer, but did not peak until October-November. The weekly GWM of the incidence moved along a line from southwest to northeast for the Russian and Asian Influenza but northeast to southwest for the A(H1N1)pdm09. The local epidemic periods of the Asian Influenza were preceded by falling temperature in all but one of the locations analysed. Conclusions The power of spatiotemporal analysis and modeling for pandemic spread was clearly demonstrated. The epidemic period lasted approximately 10 weeks for all pandemics. None of the pandemics had its epidemic period before late autumn. The epidemic period of the Asian Influenza was preceded by falling temperatures. Climate influences on pandemic spread seem important and should be further investigated. PMID:25011543

  14. Spatial and Spatiotemporal Data Mining: Recent Advances

    SciTech Connect

    Shekhar, Shashi; Vatsavai, Raju; Celik, Mete

    2008-01-01

    Explosive growth in geospatial data and the emergence of new spatial technologies emphasize the need for automated discovery of spatial knowledge. Spatial data mining is the process of discovering interesting and previously unknown, but potentially useful patterns from large spatial databases. The complexity of spatial data and intrinsic spatial relationships limits the usefulness of conventional data mining techniques for extracting spatial patterns. In this chapter we explore the emerging field of spatial data mining, focusing on four major topics: prediction and classification, outlier detection, co-location mining, and clustering. Spatiotemporal data mining is also briefly discussed.

  15. Spatiotemporal chaos from bursting dynamics

    NASA Astrophysics Data System (ADS)

    Berenstein, Igal; De Decker, Yannick

    2015-08-01

    In this paper, we study the emergence of spatiotemporal chaos from mixed-mode oscillations, by using an extended Oregonator model. We show that bursting dynamics consisting of fast/slow mixed mode oscillations along a single attractor can lead to spatiotemporal chaotic dynamics, although the spatially homogeneous solution is itself non-chaotic. This behavior is observed far from the Hopf bifurcation and takes the form of a spatiotemporal intermittency where the system locally alternates between the fast and the slow phases of the mixed mode oscillations. We expect this form of spatiotemporal chaos to be generic for models in which one or several slow variables are coupled to activator-inhibitor type of oscillators.

  16. Controlling chaos for spatiotemporal intermittency.

    PubMed

    Oikawa, Noriko; Hidaka, Yoshiki; Kai, Shoichi

    2008-03-01

    This paper reports the control of spatiotemporal intermittency in an electroconvective system in a nematic liquid crystal. In the spatiotemporal intermittency, an ordered structure [the defect lattice (DL)] coexists with turbulence. Control of the spatiotemporal intermittency, in which the turbulent state changes to a DL, is achieved by a few percent amplitude modulation of the applied ac voltage. The optimal control frequency is equal to the intrinsic oscillation frequency of the DL. The transition from the turbulent state to a DL occurs not by nucleation of the DL domain, but by penetration of the DL domain into the turbulent one. Control of the spatiotemporal intermittency is achieved through a resonance of the DL oscillation with respect to the modulation frequency that leads to spatial entrainment. PMID:18517452

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

    PubMed

    Wang, Jiabin; Yang, Jian; 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

  18. 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

  19. Spatiotemporal Patterns Produced by Bacteria

    NASA Astrophysics Data System (ADS)

    Shimada, Yuji; Nakahara, Akio; Matsushita, Mitsugu; Matsuyama, Tohey

    1995-06-01

    Spatiotemporal patterns formed by a bacterial colony of Proteus mirabilis on an agar plate were observed. About half or one hour after the colony spread over the entire surface of the agar medium in a petridish, various patterns including target and spiral patterns appeared. They are very similar to those seen in other dissipative systems, such as chemical oscillations and electrohydrodynamic convective systems. Microscopic observations revealed that the collective motion of bacterial cells is responsible for the formation of these spatiotemporal patterns.

  20. Targeted cross-linking-mass spectrometry determines vicinal interactomes within heterogeneous RNP complexes

    PubMed Central

    Trahan, Christian; Oeffinger, Marlene

    2016-01-01

    Proteomic and RNomic approaches have identified many components of different ribonucleoprotein particles (RNPs), yet still little is known about the organization and protein proximities within these heterogeneous and highly dynamic complexes. Here we describe a targeted cross-linking approach, which combines cross-linking from a known anchor site with affinity purification and mass spectrometry (MS) to identify the changing vicinity interactomes along RNP maturation pathways. Our method confines the reaction radius of a heterobifunctional cross-linker to a specific interaction surface, increasing the probability to capture low abundance conformations and transient vicinal interactors too infrequent for identification by traditional cross-linking-MS approaches, and determine protein proximities within RNPs. Applying the method to two conserved RNA-associated complexes in Saccharomyces cerevisae, the mRNA export receptor Mex67:Mtr2 and the pre-ribosomal Nop7 subcomplex, we identified dynamic vicinal interactomes within those complexes and along their changing pathway milieu. Our results therefore show that this method provides a new tool to study the changing spatial organization of heterogeneous dynamic RNP complexes. PMID:26657640

  1. A core of kinase-regulated interactomes defines the neoplastic MDSC lineage

    PubMed Central

    Zudaire, Isabel; Liechtenstein, Therese; Arasanz, Hugo; Lozano, Teresa; Casares, Noelia; Chaikuad, Apirat; Knapp, Stefan; Guerrero-Setas, David; Escors, David; Kochan, Grazyna; Santamaría, Enrique

    2015-01-01

    Myeloid-derived suppressor cells (MDSCs) differentiate from bone marrow precursors, expand in cancer-bearing hosts and accelerate tumor progression. MDSCs have become attractive therapeutic targets, as their elimination strongly enhances anti-neoplastic treatments. Here, immature myeloid dendritic cells (DCs), MDSCs modeling tumor-infiltrating subsets or modeling non-cancerous (NC)-MDSCs were compared by in-depth quantitative proteomics. We found that neoplastic MDSCs differentially expressed a core of kinases which controlled lineage-specific (PI3K-AKT and SRC kinases) and cancer-induced (ERK and PKC kinases) protein interaction networks (interactomes). These kinases contributed to some extent to myeloid differentiation. However, only AKT and ERK specifically drove MDSC differentiation from myeloid precursors. Interfering with AKT and ERK with selective small molecule inhibitors or shRNAs selectively hampered MDSC differentiation and viability. Thus, we provide compelling evidence that MDSCs constitute a distinct myeloid lineage distinguished by a “kinase signature” and well-defined interactomes. Our results define new opportunities for the development of anti-cancer treatments targeting these tumor-promoting immune cells. PMID:26320174

  2. The Liver Connexin32 Interactome Is a Novel Plasma Membrane-Mitochondrial Signaling Nexus

    PubMed Central

    2013-01-01

    Connexins are the structural subunits of gap junctions and act as protein platforms for signaling complexes. Little is known about tissue-specific connexin signaling nexuses, given significant challenges associated with affinity-purifying endogenous channel complexes to the level required for interaction analyses. Here, we used multiple subcellular fractionation techniques to isolate connexin32-enriched membrane microdomains from murine liver. We show, for the first time, that connexin32 localizes to both the plasma membrane and inner mitochondrial membrane of hepatocytes. Using a combination of immunoprecipitation-high throughput mass spectrometry, reciprocal co-IP, and subcellular fractionation methodologies, we report a novel interactome validated using null mutant controls. Eighteen connexin32 interacting proteins were identified. The majority represent resident mitochondrial proteins, a minority represent plasma membrane, endoplasmic reticulum, or cytoplasmic partners. In particular, connexin32 interacts with connexin26 and the mitochondrial protein, sideroflexin-1, at the plasma membrane. Connexin32 interaction enhances connexin26 stability. Converging bioinformatic, biochemical, and confocal analyses support a role for connexin32 in transiently tethering mitochondria to connexin32-enriched plasma membrane microdomains through interaction with proteins in the outer mitochondrial membrane, including sideroflexin-1. Complex formation increases the pool of sideroflexin-1 that is present at the plasma membrane. Together, these data identify a novel plasma membrane/mitochondrial signaling nexus in the connexin32 interactome. PMID:23590695

  3. 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. PMID:26771498

  4. Interactome Mapping Reveals the Evolutionary History of the Nuclear Pore Complex.

    PubMed

    Obado, Samson O; Brillantes, Marc; Uryu, Kunihiro; Zhang, Wenzhu; Ketaren, Natalia E; Chait, Brian T; Field, Mark C; Rout, Michael P

    2016-02-01

    The nuclear pore complex (NPC) is responsible for nucleocytoplasmic transport and constitutes a hub for control of gene expression. The components of NPCs from several eukaryotic lineages have been determined, but only the yeast and vertebrate NPCs have been extensively characterized at the quaternary level. Significantly, recent evidence indicates that compositional similarity does not necessarily correspond to homologous architecture between NPCs from different taxa. To address this, we describe the interactome of the trypanosome NPC, a representative, highly divergent eukaryote. We identify numerous new NPC components and report an exhaustive interactome, allowing assignment of trypanosome nucleoporins to discrete NPC substructures. Remarkably, despite retaining similar protein composition, there are exceptional architectural dissimilarities between opisthokont (yeast and vertebrates) and excavate (trypanosomes) NPCs. Whilst elements of the inner core are conserved, numerous peripheral structures are highly divergent, perhaps reflecting requirements to interface with divergent nuclear and cytoplasmic functions. Moreover, the trypanosome NPC has almost complete nucleocytoplasmic symmetry, in contrast to the opisthokont NPC; this may reflect divergence in RNA export processes at the NPC cytoplasmic face, as we find evidence supporting Ran-dependent mRNA export in trypanosomes, similar to protein transport. We propose a model of stepwise acquisition of nucleocytoplasmic mechanistic complexity and demonstrate that detailed dissection of macromolecular complexes provides fuller understanding of evolutionary processes. PMID:26891179

  5. 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

  6. Systematic interactome mapping and genetic perturbation analysis of a C. elegans TGF-beta signaling network.

    PubMed

    Tewari, Muneesh; Hu, Patrick J; Ahn, Jin Sook; Ayivi-Guedehoussou, Nono; Vidalain, Pierre-Olivier; Li, Siming; Milstein, Stuart; Armstrong, Chris M; Boxem, Mike; Butler, Maurice D; Busiguina, Svetlana; Rual, Jean-Franois; Ibarrola, Nieves; Chaklos, Sabrina T; Bertin, Nicolas; Vaglio, Philippe; Edgley, Mark L; King, Kevin V; Albert, Patrice S; Vandenhaute, Jean; Pandey, Akhilesh; Riddle, Donald L; Ruvkun, Gary; Vidal, Marc

    2004-02-27

    To initiate a system-level analysis of C. elegans DAF-7/TGF-beta signaling, we combined interactome mapping with single and double genetic perturbations. Yeast two-hybrid (Y2H) screens starting with known DAF-7/TGF-beta pathway components defined a network of 71 interactions among 59 proteins. Coaffinity purification (co-AP) assays in mammalian cells confirmed the overall quality of this network. Systematic perturbations of the network using RNAi, both in wild-type and daf-7/TGF-beta pathway mutant animals, identified nine DAF-7/TGF-beta signaling modifiers, seven of which are conserved in humans. We show that one of these has functional homology to human SNO/SKI oncoproteins and that mutations at the corresponding genetic locus daf-5 confer defects in DAF-7/TGF-beta signaling. Our results reveal substantial molecular complexity in DAF-7/TGF-beta signal transduction. Integrating interactome maps with systematic genetic perturbations may be useful for developing a systems biology approach to this and other signaling modules. PMID:14992718

  7. Interactome Mapping Reveals the Evolutionary History of the Nuclear Pore Complex

    PubMed Central

    Obado, Samson O.; Brillantes, Marc; Uryu, Kunihiro; Zhang, Wenzhu; Ketaren, Natalia E.; Chait, Brian T.; Field, Mark C.; Rout, Michael P.

    2016-01-01

    The nuclear pore complex (NPC) is responsible for nucleocytoplasmic transport and constitutes a hub for control of gene expression. The components of NPCs from several eukaryotic lineages have been determined, but only the yeast and vertebrate NPCs have been extensively characterized at the quaternary level. Significantly, recent evidence indicates that compositional similarity does not necessarily correspond to homologous architecture between NPCs from different taxa. To address this, we describe the interactome of the trypanosome NPC, a representative, highly divergent eukaryote. We identify numerous new NPC components and report an exhaustive interactome, allowing assignment of trypanosome nucleoporins to discrete NPC substructures. Remarkably, despite retaining similar protein composition, there are exceptional architectural dissimilarities between opisthokont (yeast and vertebrates) and excavate (trypanosomes) NPCs. Whilst elements of the inner core are conserved, numerous peripheral structures are highly divergent, perhaps reflecting requirements to interface with divergent nuclear and cytoplasmic functions. Moreover, the trypanosome NPC has almost complete nucleocytoplasmic symmetry, in contrast to the opisthokont NPC; this may reflect divergence in RNA export processes at the NPC cytoplasmic face, as we find evidence supporting Ran-dependent mRNA export in trypanosomes, similar to protein transport. We propose a model of stepwise acquisition of nucleocytoplasmic mechanistic complexity and demonstrate that detailed dissection of macromolecular complexes provides fuller understanding of evolutionary processes. PMID:26891179

  8. Oxidative status interactome map: towards novel approaches in experiment planning, data analysis, diagnostics and therapy.

    PubMed

    Zolotukhin, Peter; Kozlova, Yulia; Dovzhik, Anastasiya; Kovalenko, Konstantin; Kutsyn, Kseniya; Aleksandrova, Anzhela; Shkurat, Tatyana

    2013-08-01

    Experimental evidence suggests an immense variety of processes associated with and aimed at producing reactive oxygen and/or nitrogen species. Clinical studies implicate an enormous range of pathologies associated with reactive oxygen/nitrogen species metabolism deregulation, particularly oxidative stress. Recent advances in biochemistry, proteomics and molecular biology/biophysics of cells suggest oxidative stress to be an endpoint of complex dysregulation events of conjugated pathways consolidated under the term, proposed here, "oxidative status". The oxidative status concept, in order to allow for novel diagnostic and therapeutic approaches, requires elaboration of a new logic system comprehending all the features, versatility and complexity of cellular pro- and antioxidative components of different nature. We have developed a curated and regularly updated interactive interactome map of human cellular-level oxidative status allowing for systematization of the related most up-to-date experimental data. A total of more than 600 papers were selected for the initial creation of the map. The map comprises more than 300 individual factors with respective interactions, all subdivided hierarchically for logical analysis purposes. The pilot application of the interactome map suggested several points for further development of oxidative status-based technologies. PMID:23698602

  9. Targeted cross-linking-mass spectrometry determines vicinal interactomes within heterogeneous RNP complexes.

    PubMed

    Trahan, Christian; Oeffinger, Marlene

    2016-02-18

    Proteomic and RNomic approaches have identified many components of different ribonucleoprotein particles (RNPs), yet still little is known about the organization and protein proximities within these heterogeneous and highly dynamic complexes. Here we describe a targeted cross-linking approach, which combines cross-linking from a known anchor site with affinity purification and mass spectrometry (MS) to identify the changing vicinity interactomes along RNP maturation pathways. Our method confines the reaction radius of a heterobifunctional cross-linker to a specific interaction surface, increasing the probability to capture low abundance conformations and transient vicinal interactors too infrequent for identification by traditional cross-linking-MS approaches, and determine protein proximities within RNPs. Applying the method to two conserved RNA-associated complexes in Saccharomyces cerevisae, the mRNA export receptor Mex67:Mtr2 and the pre-ribosomal Nop7 subcomplex, we identified dynamic vicinal interactomes within those complexes and along their changing pathway milieu. Our results therefore show that this method provides a new tool to study the changing spatial organization of heterogeneous dynamic RNP complexes. PMID:26657640

  10. Time-space Kriging to address the spatiotemporal misalignment in the large datasets.

    PubMed

    Liang, Dong; Kumar, Naresh

    2013-06-01

    This paper presents a Bayesian hierarchical spatiotemporal method of interpolation, termed as Markov Cube Kriging (MCK). The classical Kriging methods become computationally prohibitive, especially for large datasets due to the O(n(3)) matrix decomposition. MCK offers novel and computationally efficient solutions to address spatiotemporal misalignment, mismatch in the spatiotemporal scales and missing values across space and time in large spatiotemporal datasets. MCK is flexible in that it allows for non-separable spatiotemporal structure and nonstationary covariance at the hierarchical spatiotemporal scales. Employing MCK we developed estimates of daily concentration of fine particulates matter ≤2.5 μm in aerodynamic diameter (PM2.5) at 2.5 km spatial grid for the Cleveland Metropolitan Statistical Area, 2000 to 2009. Our validation and cross-validation suggest that MCK achieved robust prediction of spatiotemporal random effects and underlying hierarchical and nonstationary spatiotemporal structure in air pollution data. MCK has important implications for environmental epidemiology and environmental sciences for exposure quantification and collocation of data from different sources, available at different spatiotemporal scales. PMID:24039539

  11. Time-space Kriging to address the spatiotemporal misalignment in the large datasets

    PubMed Central

    Liang, Dong; Kumar, Naresh

    2013-01-01

    This paper presents a Bayesian hierarchical spatiotemporal method of interpolation, termed as Markov Cube Kriging (MCK). The classical Kriging methods become computationally prohibitive, especially for large datasets due to the O(n3) matrix decomposition. MCK offers novel and computationally efficient solutions to address spatiotemporal misalignment, mismatch in the spatiotemporal scales and missing values across space and time in large spatiotemporal datasets. MCK is flexible in that it allows for non-separable spatiotemporal structure and nonstationary covariance at the hierarchical spatiotemporal scales. Employing MCK we developed estimates of daily concentration of fine particulates matter ≤2.5 μm in aerodynamic diameter (PM2.5) at 2.5 km spatial grid for the Cleveland Metropolitan Statistical Area, 2000 to 2009. Our validation and cross-validation suggest that MCK achieved robust prediction of spatiotemporal random effects and underlying hierarchical and nonstationary spatiotemporal structure in air pollution data. MCK has important implications for environmental epidemiology and environmental sciences for exposure quantification and collocation of data from different sources, available at different spatiotemporal scales. PMID:24039539

  12. Contrast Adaptation Implies Two Spatiotemporal Channels but Three Adapting Processes

    ERIC Educational Resources Information Center

    Langley, Keith; Bex, Peter J.

    2007-01-01

    The contrast gain control model of adaptation predicts that the effects of contrast adaptation correlate with contrast sensitivity. This article reports that the effects of high contrast spatiotemporal adaptors are maximum when adapting around 19 Hz, which is a factor of two or more greater than the peak in contrast sensitivity. To explain the

  13. Contrast Adaptation Implies Two Spatiotemporal Channels but Three Adapting Processes

    ERIC Educational Resources Information Center

    Langley, Keith; Bex, Peter J.

    2007-01-01

    The contrast gain control model of adaptation predicts that the effects of contrast adaptation correlate with contrast sensitivity. This article reports that the effects of high contrast spatiotemporal adaptors are maximum when adapting around 19 Hz, which is a factor of two or more greater than the peak in contrast sensitivity. To explain the…

  14. Spatiotemporal dynamics of HIV infection

    NASA Astrophysics Data System (ADS)

    Strain, Matthew Carl

    Mathematical models of the dynamics of infection with the human immunodeficiency virus (HIV) have contributed to tremendous advances over the past 20 years. This thesis extends this previous work by exploring the importance of spatial heterogeneity in HIV infection both in vitro and in vivo in patients treated with highly-active antiretroviral therapy. Viral infections propagate locally in space, yet HIV infection has been widely regarded as equilibrated over the entire body of an infected patient. This dissertation constructs and explores a cellular automata model of viral spread at the cellular level. Coupling the automata to a blood compartment represented by a differential equation leads to a whole-body model of HIV infection that explicitly includes spatial effects at both the cellular and tissue levels. These models are tested by comparison with experimental data. A central prediction of the spatial model is that, due to competition between Brownian motion and viral lability, HIV infectivity increases with target cell density. This production is verified in a series of in vitro experiments in cell culture. The predicted independence of inhibitory concentrations of antiretoviral agents is verified for nevirapine, but azidothymidine inhibits HIV replication less efficiently in more dense cultures. These in vitro results suggest that systems allowing cell concentrations closer to tissue densities would better reflect virus replication kinetics, although standard measures of relative drug susceptibility may accurately reflect in vivo conditions. The coupled spatial model of in vivo dynamics is compared with novel mathematical analysis of experiments in HIV-infected patients. These analyses indicate that HIV DNA provides a useful marker of the size of long-lived cellular reservoirs of HIV. Levels of HIV DNA in peripheral blood are predictive of the average rate of residual virus production after years of treatment, regardless of whether patients initiate therapy during the primary or chronic stages of HIV infection. The nonlinear clearance of HIV DNA therefore predicts lifelong virus production, even in treated patients. Collectively, these results demonstrate that important features of the spatiotemporal dynamics of HIV infection both in vitro and in vivo are best explained with explicit spatial models.

  15. Recent advances in large-scale protein interactome mapping

    PubMed Central

    Mehta, Virja; Trinkle-Mulcahy, Laura

    2016-01-01

    Protein-protein interactions (PPIs) underlie most, if not all, cellular functions. The comprehensive mapping of these complex networks of stable and transient associations thus remains a key goal, both for systems biology-based initiatives (where it can be combined with other ‘omics’ data to gain a better understanding of functional pathways and networks) and for focused biological studies. Despite the significant challenges of such an undertaking, major strides have been made over the past few years. They include improvements in the computation prediction of PPIs and the literature curation of low-throughput studies of specific protein complexes, but also an increase in the deposition of high-quality data from non-biased high-throughput experimental PPI mapping strategies into publicly available databases. PMID:27158474

  16. Spatiotemporal exploratory models for broad-scale survey data.

    PubMed

    Fink, Daniel; Hochachka, Wesley M; Zuckerberg, Benjamin; Winkler, David W; Shaby, Ben; Munson, M Arthur; Hooker, Giles; Riedewald, Mirek; Sheldon, Daniel; Kelling, Steve

    2010-12-01

    The distributions of animal populations change and evolve through time. Migratory species exploit different habitats at different times of the year. Biotic and abiotic features that determine where a species lives vary due to natural and anthropogenic factors. This spatiotemporal variation needs to be accounted for in any modeling of species' distributions. In this paper we introduce a semiparametric model that provides a flexible framework for analyzing dynamic patterns of species occurrence and abundance from broad-scale survey data. The spatiotemporal exploratory model (STEM) adds essential spatiotemporal structure to existing techniques for developing species distribution models through a simple parametric structure without requiring a detailed understanding of the underlying dynamic processes. STEMs use a multi-scale strategy to differentiate between local and global-scale spatiotemporal structure. A user-specified species distribution model accounts for spatial and temporal patterning at the local level. These local patterns are then allowed to "scale up" via ensemble averaging to larger scales. This makes STEMs especially well suited for exploring distributional dynamics arising from a variety of processes. Using data from eBird, an online citizen science bird-monitoring project, we demonstrate that monthly changes in distribution of a migratory species, the Tree Swallow (Tachycineta bicolor), can be more accurately described with a STEM than a conventional bagged decision tree model in which spatiotemporal structure has not been imposed. We also demonstrate that there is no loss of model predictive power when a STEM is used to describe a spatiotemporal distribution with very little spatiotemporal variation; the distribution of a nonmigratory species, the Northern Cardinal (Cardinalis cardinalis). PMID:21265447

  17. Optical Kerr Spatiotemporal Dark-Lump Dynamics of Hydrodynamic Origin

    NASA Astrophysics Data System (ADS)

    Baronio, Fabio; Wabnitz, Stefan; Kodama, Yuji

    2016-04-01

    There is considerable fundamental and applicative interest in obtaining nondiffractive and nondispersive spatiotemporal localized wave packets propagating in optical cubic nonlinear or Kerr media. Here, we analytically predict the existence of a novel family of spatiotemporal dark lump solitary wave solutions of the (2 +1 )D nonlinear Schrödinger equation. Dark lumps represent multidimensional holes of light on a continuous wave background. We analytically derive the dark lumps from the hydrodynamic exact soliton solutions of the (2 +1 )D shallow water Kadomtsev-Petviashvili model, inheriting their complex interaction properties. This finding opens a novel path for the excitation and control of optical spatiotemporal waveforms of hydrodynamic footprint and multidimensional optical extreme wave phenomena.

  18. Optical Kerr Spatiotemporal Dark-Lump Dynamics of Hydrodynamic Origin.

    PubMed

    Baronio, Fabio; Wabnitz, Stefan; Kodama, Yuji

    2016-04-29

    There is considerable fundamental and applicative interest in obtaining nondiffractive and nondispersive spatiotemporal localized wave packets propagating in optical cubic nonlinear or Kerr media. Here, we analytically predict the existence of a novel family of spatiotemporal dark lump solitary wave solutions of the (2+1)D nonlinear Schrödinger equation. Dark lumps represent multidimensional holes of light on a continuous wave background. We analytically derive the dark lumps from the hydrodynamic exact soliton solutions of the (2+1)D shallow water Kadomtsev-Petviashvili model, inheriting their complex interaction properties. This finding opens a novel path for the excitation and control of optical spatiotemporal waveforms of hydrodynamic footprint and multidimensional optical extreme wave phenomena. PMID:27176522

  19. The TOPLESS interactome: a framework for gene repression in Arabidopsis.

    PubMed

    Causier, Barry; Ashworth, Mary; Guo, Wenjia; Davies, Brendan

    2012-01-01

    Transcription factors activate or repress target gene expression or switch between activation and repression. In animals and yeast, Groucho/Tup1 corepressor proteins are recruited by diverse transcription factors to induce context-specific transcriptional repression. Two groups of Groucho/Tup1-like corepressors have been described in plants. LEUNIG and LEUNIG_HOMOLOG constitute one group and TOPLESS (TPL) and the four TPL-related (TPR) corepressors form the other. To discover the processes in which TPL and the TPR corepressors operate, high-throughput yeast two-hybrid approaches were used to identify interacting proteins. We found that TPL/TPR corepressors predominantly interact directly with specific transcription factors, many of which were previously implicated in transcriptional repression. The interacting transcription factors reveal that the TPL/TPR family has been coopted multiple times to modulate gene expression in diverse processes, including hormone signaling, stress responses, and the control of flowering time, for which we also show biological validation. The interaction data suggest novel mechanisms for the involvement of TPL/TPR corepressors in auxin and jasmonic acid signaling. A number of short repression domain (RD) sequences have previously been identified in Arabidopsis (Arabidopsis thaliana) transcription factors. All known RD sequences were enriched among the TPL/TPR interactors, and novel TPL-RD interactions were identified. We show that the presence of RD sequences is essential for TPL/TPR recruitment. These data provide a framework for TPL/TPR-dependent transcriptional repression. They allow for predictions about new repressive transcription factors, corepressor interactions, and repression mechanisms and identify a wide range of plant processes that utilize TPL/TPR-mediated gene repression. PMID:22065421

  20. 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. PMID:25999517

  1. Chromosomes. A comprehensive Xist interactome reveals cohesin repulsion and an RNA-directed chromosome conformation.

    PubMed

    Minajigi, Anand; Froberg, John E; Wei, Chunyao; Sunwoo, Hongjae; Kesner, Barry; Colognori, David; Lessing, Derek; Payer, Bernhard; Boukhali, Myriam; Haas, Wilhelm; Lee, Jeannie T

    2015-07-17

    The inactive X chromosome (Xi) serves as a model to understand gene silencing on a global scale. Here, we perform "identification of direct RNA interacting proteins" (iDRiP) to isolate a comprehensive protein interactome for Xist, an RNA required for Xi silencing. We discover multiple classes of interactors-including cohesins, condensins, topoisomerases, RNA helicases, chromatin remodelers, and modifiers-that synergistically repress Xi transcription. Inhibiting two or three interactors destabilizes silencing. Although Xist attracts some interactors, it repels architectural factors. Xist evicts cohesins from the Xi and directs an Xi-specific chromosome conformation. Upon deleting Xist, the Xi acquires the cohesin-binding and chromosomal architecture of the active X. Our study unveils many layers of Xi repression and demonstrates a central role for RNA in the topological organization of mammalian chromosomes. PMID:26089354

  2. The Cardiac TBX5 Interactome Reveals a Chromatin Remodeling Network Essential for Cardiac Septation.

    PubMed

    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

    2016-02-01

    Human mutations in the cardiac transcription factor gene TBX5 cause congenital heart disease (CHD), although 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 mis-sense 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

  3. A human interactome in three quantitative dimensions organized by stoichiometries and abundances.

    PubMed

    Hein, Marco Y; Hubner, Nina C; Poser, Ina; Cox, Jürgen; Nagaraj, Nagarjuna; Toyoda, Yusuke; Gak, Igor A; Weisswange, Ina; Mansfeld, Jörg; Buchholz, Frank; Hyman, Anthony A; Mann, Matthias

    2015-10-22

    The organization of a cell emerges from the interactions in protein networks. The interactome is critically dependent on the strengths of interactions and the cellular abundances of the connected proteins, both of which span orders of magnitude. However, these aspects have not yet been analyzed globally. Here, we have generated a library of HeLa cell lines expressing 1,125 GFP-tagged proteins under near-endogenous control, which we used as input for a next-generation interaction survey. Using quantitative proteomics, we detect specific interactions, estimate interaction stoichiometries, and measure cellular abundances of interacting proteins. These three quantitative dimensions reveal that the protein network is dominated by weak, substoichiometric interactions that play a pivotal role in defining network topology. The minority of stable complexes can be identified by their unique stoichiometry signature. This study provides a rich interaction dataset connecting thousands of proteins and introduces a framework for quantitative network analysis. PMID:26496610

  4. Genome Annotation and Intraviral Interactome for the Streptococcus pneumoniae Virulent Phage Dp-1▿ ¶

    PubMed Central

    Sabri, Mourad; Häuser, Roman; Ouellette, Marc; Liu, Jing; Dehbi, Mohammed; Moeck, Greg; García, Ernesto; Titz, Björn; Uetz, Peter; Moineau, Sylvain

    2011-01-01

    Streptococcus pneumoniae causes several diseases, including pneumonia, septicemia, and meningitis. Phage Dp-1 is one of the very few isolated virulent S. pneumoniae bacteriophages, but only a partial characterization is currently available. Here, we confirmed that Dp-1 belongs to the family Siphoviridae. Then, we determined its complete genomic sequence of 56,506 bp. It encodes 72 open reading frames, of which 44 have been assigned a function. We have identified putative promoters, Rho-independent terminators, and several genomic clusters. We provide evidence that Dp-1 may be using a novel DNA replication system as well as redirecting host protein synthesis through queuosine-containing tRNAs. Liquid chromatography-mass spectrometry analysis of purified phage Dp-1 particles identified at least eight structural proteins. Finally, using comprehensive yeast two-hybrid screens, we identified 156 phage protein interactions, and this intraviral interactome was used to propose a structural model of Dp-1. PMID:21097633

  5. A Transporter Interactome Is Essential for the Acquisition of Antimicrobial Resistance to Antibiotics

    PubMed Central

    Shuster, Yonatan; Steiner-Mordoch, Sonia; Alon Cudkowicz, Noemie; Schuldiner, Shimon

    2016-01-01

    Awareness of the problem of antimicrobial resistance (AMR) has escalated and drug-resistant infections are named among the most urgent problems facing clinicians today. Our experiments here identify a transporter interactome and portray its essential function in acquisition of antimicrobial resistance. By exposing E. coli cells to consecutive increasing concentrations of the fluoroquinolone norfloxacin we generated in the laboratory highly resistant strains that carry multiple mutations, most of them identical to those identified in clinical isolates. With this experimental paradigm, we show that the MDTs function in a coordinated mode to provide an essential first-line defense mechanism, preventing the drug reaching lethal concentrations, until a number of stable efficient alterations occur that allow survival. Single-component efflux transporters remove the toxic compounds from the cytoplasm to the periplasmic space where TolC-dependent transporters expel them from the cell. We postulate a close interaction between the two types of transporters to prevent rapid leak of the hydrophobic substrates back into the cell. The findings change the prevalent concept that in Gram-negative bacteria a single multidrug transporter, AcrAB-TolC type, is responsible for the resistance. The concept of a functional interactome, the process of identification of its members, the elucidation of the nature of the interactions and its role in cell physiology will change the existing paradigms in the field. We anticipate that our work will have an impact on the present strategy searching for inhibitors of AcrAB-TolC as adjuvants of existing antibiotics and provide novel targets for this urgent undertaking. PMID:27050393

  6. Synthesis of an inositol hexakisphosphate (IP6) affinity probe to study the interactome from a colon cancer cell line.

    PubMed

    Yin, Meng-Xin; Catimel, Bruno; Gregory, Mark; Condron, Melanie; Kapp, Eugene; Holmes, Andrew B; Burgess, Antony W

    2016-03-14

    Inositol hexakisphosphate (InsP6 or IP6) is an important signalling molecule in vesicular trafficking, neurotransmission, immune responses, regulation of protein kinases and phosphatases, activation of ion channels, antioxidant functions and anticancer activities. An IP6 probe was synthesised from myo-inositol via a derivatised analogue, which was immobilised through a terminal amino group onto Dynabeads. Systematic analysis of the IP6 interactome has been performed using the IP6 affinity probe using cytosolic extracts from the LIM1215 colonic carcinoma cell line. LC/MS/MS analysis identified 77 proteins or protein complexes that bind to IP6 specifically, including AP-2 complex proteins and β-arrestins as well as a number of novel potential IP6 interacting proteins. Bioinformatic enrichment analysis of the IP6 interactome reinforced the concept that IP6 regulates a number of biological processes including cell cycle and division, signal transduction, intracellular protein transport, vesicle-mediated transport and RNA splicing. PMID:26840369

  7. Cardiolipin defines the interactome of the major ADP/ATP carrier protein of the mitochondrial inner membrane

    PubMed Central

    Claypool, Steven M.; Oktay, Yavuz; Boontheung, Pinmanee; Loo, Joseph A.; Koehler, Carla M.

    2008-01-01

    Defined mutations in the mitochondrial ADP/ATP carrier (AAC) are associated with certain types of progressive external ophthalmoplegia. AAC is required for oxidative phosphorylation (OXPHOS), and dysregulation of AAC has been implicated in apoptosis. Little is known about the AAC interactome, aside from a known requirement for the phospholipid cardiolipin (CL) and that it is thought to function as a homodimer. Using a newly developed dual affinity tag, we demonstrate that yeast AAC2 physically participates in several protein complexes of distinct size and composition. The respiratory supercomplex and several smaller AAC2-containing complexes, including other members of the mitochondrial carrier family, are identified here. In the absence of CL, most of the defined interactions are destabilized or undetectable. The absence of CL and/or AAC2 results in distinct yet additive alterations in respiratory supercomplex structure and respiratory function. Thus, a single lipid can significantly alter the functional interactome of an individual protein. PMID:18779372

  8. The L1TD1 Protein Interactome Reveals the Importance of Post-transcriptional Regulation in Human Pluripotency

    PubMed Central

    Emani, Maheswara Reddy; Närvä, Elisa; Stubb, Aki; Chakroborty, Deepankar; Viitala, Miro; Rokka, Anne; Rahkonen, Nelly; Moulder, Robert; Denessiouk, Konstantin; Trokovic, Ras; Lund, Riikka; Elo, Laura L.; Lahesmaa, Riitta

    2015-01-01

    Summary The RNA-binding protein L1TD1 is one of the most specific and abundant proteins in pluripotent stem cells and is essential for the maintenance of pluripotency in human cells. Here, we identify the protein interaction network of L1TD1 in human embryonic stem cells (hESCs) and provide insights into the interactome network constructed in human pluripotent cells. Our data reveal that L1TD1 has an important role in RNA splicing, translation, protein traffic, and degradation. L1TD1 interacts with multiple stem-cell-specific proteins, many of which are still uncharacterized in the context of development. Further, we show that L1TD1 is a part of the pluripotency interactome network of OCT4, SOX2, and NANOG, bridging nuclear and cytoplasmic regulation and highlighting the importance of RNA biology in pluripotency. PMID:25702638

  9. Spatiotemporal Wave Patterns: Information Dynamics

    SciTech Connect

    Mikhail Rabinovich; Lev Tsimring

    2006-01-20

    Pattern formation has traditionally been studied in non-equilibrium physics from the viewpoint of describing the basic structures and their interactions. While this is still an important area of research, the emphasis in the last few years has shifted towards analysis of specific properties of patterns in various complex media. For example, diverse and unexpected phenomena occur in neuro-like media that are characterized by highly non-trivial local dynamics. We carried out an active research program on analysis of spatio-temporal patterns in various physical systems (convection, oscillating fluid layer, soap film), as well as in neuro-like media, with an emphasis on informational aspects of the dynamics. Nonlinear nonequilibrium media and their discrete analogs have a unique ability to represent, memorize, and process the information contained in spatio-temporal patterns. Recent neurophysiological experiments demonstrated a certain universality of spatio-temporal representation of information by neural ensembles. Information processing is also revealed in the spatio-temporal dynamics of cellular patterns in nonequilibrium media. It is extremely important for many applications to study the informational aspects of these dynamics, including the origins and mechanisms of information generation, propagation and storage. Some of our results are: the discovery of self-organization of periodically oscillatory patterns in chaotic heterogeneous media; the analysis of the propagation of the information along a chaotic media as function of the entropy of the signal; the analysis of wave propagation in discrete non-equilibrium media with autocatalytic properties, which simulates the calcium dynamics in cellular membranes. Based on biological experiments we suggest the mechanism by which the spatial sensory information is transferred into the spatio-temporal code in the neural media. We also found a new mechanism of self-pinning in cellular structures and the related phenomenon of stick-slip front motion.

  10. Comparative analysis of virus-host interactomes with a mammalian high- throughput protein complementation assay based on Gaussia princeps luciferase

    PubMed Central

    Neveu, Grgory; Cassonnet, Patricia; Vidalain, Pierre-Olivier; Rolloy, Caroline; Mendoza, Jos; Jones, Louis; Tangy, Frdric; Muller, Mandy; Demeret, Caroline; Tafforeau, Lionel; Lotteau, Vincent; Rabourdin-Combe, Chantal; Trav, Gilles; Dricot, Amlie; Hill, David E.; Vidal, Marc; Favre, Michel; Jacob, Yves

    2012-01-01

    Comparative interactomics is a strategy for inferring potential interactions among orthologous proteins or iginterologs. Herein we focus, in contrast to standard homology-based inference, on the divergence of protein interaction profiles among closely related organisms, showing that the approach can correlate specific traits to phenotypic differences. As a model, this new comparative interactomic approach was applied at a large scale to human papillomaviruses (HPVs) proteins. The oncogenic potential of HPVs is mainly determined by the E6 and E7 early proteins. We have mapped and overlapped the virus-host protein interaction networks of E6 and E7 proteins from 11 distinct HPV genotypes, selected for their different tropisms and pathologies. We generated robust and comprehensive datasets by combining two orthogonal protein interation assays: yeast two-hybrid (Y2H), and our recently described High-Throughput Gaussia princeps Protein Complementation Assay (HT-GPCA). HT-GPCA detects protein interaction by measuring the interaction-mediated reconstitution of activity of a split Gaussia princeps luciferase. Hierarchical clustering of interaction profiles recapitulated HPV phylogeny and was used to correlate specific virus-host interaction profiles with pathological traits, reflecting the distinct carcinogenic potentials of different HPVs. This comparative interactomics constitutes a reliable and powerful strategy to decipher molecular relationships in virtually any combination of microorganism-host interactions. PMID:22898364

  11. 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. PMID:26590968

  12. 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

  13. 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.

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

    PubMed

    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

    2016-05-01

    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

  15. Spatiotemporal instability of an electrified falling film.

    PubMed

    Samanta, Arghya

    2016-01-01

    The linear spatiotemporal response to an infinitesimal disturbance is analyzed for an electrified falling film based on the Orr-Sommerfeld boundary value problem. Four spatial branches are identified, which lose their spatial symmetry in the presence of an electric field. In addition, the absolute and convective instabilities are studied within the frameworks of the saddle point approach and the collision criterion. The collision criterion offers two unstable branches that characterize the exact range of the unstable wave packet that is diminished in the presence of an electric field. In contrast, the saddle point approach offers only one unstable branch. The associated unstable range of the wave packet is similar to that predicted by the collision criterion only when the electric field is enhanced. It is shown that the electrified falling film is convectively unstable. PMID:26871172

  16. Spatiotemporal instability of an electrified falling film

    NASA Astrophysics Data System (ADS)

    Samanta, Arghya

    2016-01-01

    The linear spatiotemporal response to an infinitesimal disturbance is analyzed for an electrified falling film based on the Orr-Sommerfeld boundary value problem. Four spatial branches are identified, which lose their spatial symmetry in the presence of an electric field. In addition, the absolute and convective instabilities are studied within the frameworks of the saddle point approach and the collision criterion. The collision criterion offers two unstable branches that characterize the exact range of the unstable wave packet that is diminished in the presence of an electric field. In contrast, the saddle point approach offers only one unstable branch. The associated unstable range of the wave packet is similar to that predicted by the collision criterion only when the electric field is enhanced. It is shown that the electrified falling film is convectively unstable.

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

    SciTech Connect

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

    2015-08-28

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

  18. Protein-drug interactome analysis of SSRI-mediated neurorecovery following stroke.

    PubMed

    Chen, Hong-Fang; Pan, Xiao-Ling; Wang, Jian-Wei; Kong, Hui-Mei; Fu, Ya-Ming

    2014-06-01

    Serotonin selective reuptake inhibitors (SSRIs) have been widely used as first-line drugs in the treatment of a range of depressive and anxiety disorders. Recently, clinical studies found that this class of agents also shows significant efficacy in promoting neurogenesis, neuroplasticity and neurorecovery following stroke. Here, we attempt to elucidate molecular mechanism and biological implication underlying the SSRI-mediated neurorecovery. In the procedure, a comprehensive protein-drug interactome (PDI) was constructed for various SSRIs and their major metabolites as well as a group of control drugs across a large panel of human neuroproteins via a high-throughput molecular docking approach. The obtained PDI was then analyzed at systematic level to extract unexpected targets for SSRIs/metabolites. Biological network analysis and gene ontology (GO) enrichment solidified that the inferred targets have high potential to be directly or indirectly involved in diverse neural events, and further molecular dynamics (MD) simulation and post molecular mechanics-Poisson Boltzmann/surface area (MM-PB/SA) characterization revealed a stable complex architecture and high-affinity interaction between the targets and SSRIs/metabolites. Specifically, two human proteins, i.e. neurogenic locus notch homolog protein 1 (NOTCH 1) and Rho-associated protein kinase 1 (ROCK 1), were suggested as promising regulators in the SSRI-mediated neurorecovery, which can be targeted efficiently by fluoxetine and paroxetine, respectively, as well as other SSRIs and metabolites. PMID:24705245

  19. 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

  20. Identification of LMO2 transcriptome and interactome in diffuse large B-cell lymphoma.

    PubMed

    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; Lossos, Izidore S

    2012-06-01

    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

  1. Lamina Associated Polypeptide 1 (LAP1) Interactome and Its Functional Features

    PubMed Central

    Serrano, Joana B.; da Cruz e Silva, Odete A. B.; Rebelo, Sandra

    2016-01-01

    Lamina-associated polypeptide 1 (LAP1) is a type II transmembrane protein of the inner nuclear membrane encoded by the human gene TOR1AIP1. LAP1 is involved in maintaining the nuclear envelope structure and appears be involved in the positioning of lamins and chromatin. To date, LAP1’s precise function has not been fully elucidated but analysis of its interacting proteins will permit unraveling putative associations to specific cellular pathways and cellular processes. By assessing public databases it was possible to identify the LAP1 interactome, and this was curated. In total, 41 interactions were identified. Several functionally relevant proteins, such as TRF2, TERF2IP, RIF1, ATM, MAD2L1 and MAD2L1BP were identified and these support the putative functions proposed for LAP1. Furthermore, by making use of the Ingenuity Pathways Analysis tool and submitting the LAP1 interactors, the top two canonical pathways were “Telomerase signalling” and “Telomere Extension by Telomerase” and the top functions “Cell Morphology”, “Cellular Assembly and Organization” and “DNA Replication, Recombination, and Repair”. Once again, putative LAP1 functions are reinforced but novel functions are emerging. PMID:26784240

  2. Telomere-regulating genes and the telomere interactome in familial cancers.

    PubMed

    Robles-Espinoza, Carla Daniela; Velasco-Herrera, Martin del Castillo; Hayward, Nicholas K; Adams, David J

    2015-02-01

    Telomeres are repetitive sequence structures at the ends of linear chromosomes that consist of double-stranded DNA repeats followed by a short single-stranded DNA protrusion. Telomeres need to be replicated in each cell cycle and protected from DNA-processing enzymes, tasks that cells execute using specialized protein complexes such as telomerase (that includes TERT), which aids in telomere maintenance and replication, and the shelterin complex, which protects chromosome ends. These complexes are also able to interact with a variety of other proteins, referred to as the telomere interactome, to fulfill their biological functions and control signaling cascades originating from telomeres. Given their essential role in genomic maintenance and cell-cycle control, germline mutations in telomere-regulating proteins and their interacting partners have been found to underlie a variety of diseases and cancer-predisposition syndromes. These syndromes can be characterized by progressively shortening telomeres, in which carriers can present with organ failure due to stem cell senescence among other characteristics, or can also present with long or unprotected telomeres, providing an alternative route for cancer formation. This review summarizes the critical roles that telomere-regulating proteins play in cell-cycle control and cell fate and explores the current knowledge on different cancer-predisposing conditions that have been linked to germline defects in these proteins and their interacting partners. PMID:25244922

  3. Genome-wide bimolecular fluorescence complementation analysis of SUMO interactome in yeast.

    PubMed

    Sung, Min-Kyung; Lim, Gyubum; Yi, Dae-Gwan; Chang, Yeon Ji; Yang, Eun Bin; Lee, Kiyoung; Huh, Won-Ki

    2013-04-01

    The definition of protein-protein interactions (PPIs) in the natural cellular context is essential for properly understanding various biological processes. So far, however, most large-scale PPI analyses have not been performed in the natural cellular context. Here, we describe the construction of a Saccharomyces cerevisiae fusion library in which each endogenous gene is C-terminally tagged with the N-terminal fragment of Venus (VN) for a genome-wide bimolecular fluorescence complementation assay, a powerful technique for identifying PPIs in living cells. We illustrate the utility of the VN fusion library by systematically analyzing the interactome of the small ubiquitin-related modifier (SUMO) and provide previously unavailable information on the subcellular localization, types, and protease dependence of SUMO interactions. Our data set is highly complementary to the existing data sets and represents a useful resource for expanding the understanding of the physiological roles of SUMO. In addition, the VN fusion library provides a useful research tool that makes it feasible to systematically analyze PPIs in the natural cellular context. PMID:23403034

  4. Interactome of the negative regulator of nuclear import BRCA1-binding protein 2.

    PubMed

    Fatima, Shadma; Wagstaff, Kylie M; Loveland, Kate L; Jans, David A

    2015-01-01

    Although the negative regulator of nuclear import (NRNI) BRCA1 binding protein 2 (BRAP2) is highly expressed in testis, its role is largely unknown. Here we address this question by documenting the BRAP2 interactome from human testis, using the yeast 2-hybrid system to identify BRAP2-interacting proteins with roles in diverse cellular processes, including regulation of the actin cytoskeleton, ubiquitinylation, cell cycle/apoptosis and transcription. Interaction with BRAP2 in adult mouse testis with three of these, PH domain and leucine rich repeat protein phosphatase 1 (PHLPP1), A-Kinase anchor protein (AKAP3) and DNA methyl transferase 1 (DNMT1), was confirmed by coimmunoprecipitation assays. BRAP2's ability to inhibit PHLPP1 and DNMT1 nuclear localisation was also confirmed by quantitative confocal microscopy. Importantly, the physiological relevance thereof was implied by the cytoplasmic localisation of PHLPP1, AKAP3 and DNMT1 in pachytene spermatocytes/round spermatids where BRAP2 is present at high levels, and nuclear localisation of PHLPP1 and DNMT1 in spermatogonia concomitant with lower levels of BRAP2. Interestingly, BRAP2 was also present in murine spermatozoa, in part colocalised with AKAP3. Together the results indicate for the first time that BRAP2 may play an important NRNI role in germ cells of the testis, with an additional, scaffold/structural role in mature spermatozoa. PMID:25820252

  5. Auxotrophy and intrapopulation complementary in the 'interactome' of a cultivated freshwater model community.

    PubMed

    Garcia, Sarahi L; Buck, Moritz; McMahon, Katherine D; Grossart, Hans-Peter; Eiler, Alexander; Warnecke, Falk

    2015-09-01

    Microorganisms are usually studied either in highly complex natural communities or in isolation as monoclonal model populations that we manage to grow in the laboratory. Here, we uncover the biology of some of the most common and yet-uncultured bacteria in freshwater environments using a mixed culture from Lake Grosse Fuchskuhle. From a single shotgun metagenome of a freshwater mixed culture of low complexity, we recovered four high-quality metagenome-assembled genomes (MAGs) for metabolic reconstruction. This analysis revealed the metabolic interconnectedness and niche partitioning of these naturally dominant bacteria. In particular, vitamin- and amino acid biosynthetic pathways were distributed unequally with a member of Crenarchaeota most likely being the sole producer of vitamin B12 in the mixed culture. Using coverage-based partitioning of the genes recovered from a single MAG intrapopulation metabolic complementarity was revealed pointing to 'social' interactions for the common good of populations dominating freshwater plankton. As such, our MAGs highlight the power of mixed cultures to extract naturally occurring 'interactomes' and to overcome our inability to isolate and grow the microbes dominating in nature. PMID:26179741

  6. Locus-specific targeting to the X-chromosome revealed by the RNA interactome of CTCF

    PubMed Central

    Kung, Johnny T.; Kesner, Barry; An, Jee Young; Ahn, Janice Y.; Cifuentes-Rojas, Catherine; Colognori, David; Jeon, Yesu; Szanto, Attila; del Rosario, Brian C.; Pinter, Stefan F.; Erwin, Jennifer A.; Lee, Jeannie T.

    2015-01-01

    CTCF is a master regulator that plays important roles in genome architecture and gene expression. How CTCF is recruited in a locus-specific manner is not fully understood. Evidence from epigenetic processes, such as X-chromosome inactivation (XCI), indicates that CTCF associates functionally with RNA. Using genome-wide approaches to investigate the relationship between its RNA interactome and epigenomic landscape, here we report that CTCF binds thousands of transcripts in mouse embryonic stem cells, many in close proximity to CTCF’s genomic binding sites. CTCF is a specific and high-affinity RNA-binding protein (Kd <1 nM). During XCI, CTCF differentially binds the active and inactive X-chromosomes and interacts directly with Tsix, Xite, and Xist RNAs. Tsix and Xite RNAs target CTCF to the X-inactivation center, thereby inducing homologous X-chromosome pairing. Our work elucidates one mechanism by which CTCF is recruited in a locus-specific manner and implicates CTCF-RNA interactions in long-range chromosomal interactions. PMID:25578877

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

    SciTech Connect

    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 special 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.

  8. 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. PMID:22618246

  9. Lamina Associated Polypeptide 1 (LAP1) Interactome and Its Functional Features.

    PubMed

    Serrano, Joana B; da Cruz E Silva, Odete A B; Rebelo, Sandra

    2016-01-01

    Lamina-associated polypeptide 1 (LAP1) is a type II transmembrane protein of the inner nuclear membrane encoded by the human gene TOR1AIP1. LAP1 is involved in maintaining the nuclear envelope structure and appears be involved in the positioning of lamins and chromatin. To date, LAP1's precise function has not been fully elucidated but analysis of its interacting proteins will permit unraveling putative associations to specific cellular pathways and cellular processes. By assessing public databases it was possible to identify the LAP1 interactome, and this was curated. In total, 41 interactions were identified. Several functionally relevant proteins, such as TRF2, TERF2IP, RIF1, ATM, MAD2L1 and MAD2L1BP were identified and these support the putative functions proposed for LAP1. Furthermore, by making use of the Ingenuity Pathways Analysis tool and submitting the LAP1 interactors, the top two canonical pathways were "Telomerase signalling" and "Telomere Extension by Telomerase" and the top functions "Cell Morphology", "Cellular Assembly and Organization" and "DNA Replication, Recombination, and Repair". Once again, putative LAP1 functions are reinforced but novel functions are emerging. PMID:26784240

  10. The extracellular interactome of the human adenovirus family reveals diverse strategies for immunomodulation.

    PubMed

    Martinez-Martin, Nadia; Ramani, Sree R; Hackney, Jason A; Tom, Irene; Wranik, Bernd J; Chan, Michelle; Wu, Johnny; Paluch, Maciej T; Takeda, Kentaro; Hass, Philip E; Clark, Hilary; Gonzalez, Lino C

    2016-01-01

    Viruses encode secreted and cell-surface expressed proteins essential to modulate host immune defenses and establish productive infections. However, to date there has been no systematic study of the extracellular interactome of any human virus. Here we utilize the E3 proteins, diverse and rapidly evolving transmembrane-containing proteins encoded by human adenoviruses, as a model system to survey the extracellular immunomodulatory landscape. From a large-scale protein interaction screen against a microarray of more than 1,500 human proteins, we find and validate 51 previously unidentified virus-host interactions. Our results uncover conserved strategies as well as substantial diversity and multifunctionality in host targeting within and between viral species. Prominent modulation of the leukocyte immunoglobulin-like and signalling lymphocyte activation molecule families and a number of inhibitory receptors were identified as hubs for viral perturbation, suggesting unrecognized immunoregulatory strategies. We describe a virus-host extracellular interaction map of unprecedented scale that provides new insights into viral immunomodulation. PMID:27145901

  11. Proteomic analysis of the TerC interactome: Novel links to tellurite resistance and pathogenicity.

    PubMed

    Turkovicova, L; Smidak, R; Jung, G; Turna, J; Lubec, G; Aradska, J

    2016-03-16

    The tellurite resistance gene operon (ter) is widely spread among bacterial species, particularly pathogenic species. The ter operon has been implicated in tellurite resistance, phage inhibition, colicine resistance, and pathogenicity. The TerC protein represents one of the key proteins in tellurite resistance and shows no significant homology to any protein of known function. So far, there is no experimental evidence for TerC interaction partners. In this study, proteomic-based methods, including blue native electrophoresis and co-immunoprecipitation combined with LC-MS/MS, have been used to identify TerC interaction partners and thus providing indirect evidence for tentative functions of TerC in Escherichia coli. An interactome has been constructed and robust physical interaction of integral membrane protein TerC with TerB, DctA, PspA, HslU, and RplK has been shown. The TerC-TerB complex appears to act as a central unit that may link different functional modules with biochemical activities of C4-dicarboxylate transport, inner membrane stress response (phage shock protein regulatory complex), ATPase/chaperone activity, and proteosynthesis. In previous reports, it was hypothesized that a transmembrane unit formed by TerC protein may interact with the TerD family, but herein neither TerD nor TerE proteins were identified as TerC complex components. We propose that TerD/TerE participates in tellurite resistance through TerC-independent action. PMID:26778143

  12. The extracellular interactome of the human adenovirus family reveals diverse strategies for immunomodulation

    PubMed Central

    Martinez-Martin, Nadia; Ramani, Sree R.; Hackney, Jason A.; Tom, Irene; Wranik, Bernd J.; Chan, Michelle; Wu, Johnny; Paluch, Maciej T.; Takeda, Kentaro; Hass, Philip E.; Clark, Hilary; Gonzalez, Lino C.

    2016-01-01

    Viruses encode secreted and cell-surface expressed proteins essential to modulate host immune defenses and establish productive infections. However, to date there has been no systematic study of the extracellular interactome of any human virus. Here we utilize the E3 proteins, diverse and rapidly evolving transmembrane-containing proteins encoded by human adenoviruses, as a model system to survey the extracellular immunomodulatory landscape. From a large-scale protein interaction screen against a microarray of more than 1,500 human proteins, we find and validate 51 previously unidentified virus–host interactions. Our results uncover conserved strategies as well as substantial diversity and multifunctionality in host targeting within and between viral species. Prominent modulation of the leukocyte immunoglobulin-like and signalling lymphocyte activation molecule families and a number of inhibitory receptors were identified as hubs for viral perturbation, suggesting unrecognized immunoregulatory strategies. We describe a virus–host extracellular interaction map of unprecedented scale that provides new insights into viral immunomodulation. PMID:27145901

  13. The molecular basis for ANE syndrome revealed by the large ribosomal subunit processome interactome

    PubMed Central

    McCann, Kathleen L; Teramoto, Takamasa; Zhang, Jun; Tanaka Hall, Traci M; Baserga, Susan J

    2016-01-01

    ANE syndrome is a ribosomopathy caused by a mutation in an RNA recognition motif of RBM28, a nucleolar protein conserved to yeast (Nop4). While patients with ANE syndrome have fewer mature ribosomes, it is unclear how this mutation disrupts ribosome assembly. Here we use yeast as a model system and show that the mutation confers growth and pre-rRNA processing defects. Recently, we found that Nop4 is a hub protein in the nucleolar large subunit (LSU) processome interactome. Here we demonstrate that the ANE syndrome mutation disrupts Nop4’s hub function by abrogating several of Nop4’s protein-protein interactions. Circular dichroism and NMR demonstrate that the ANE syndrome mutation in RRM3 of human RBM28 disrupts domain folding. We conclude that the ANE syndrome mutation generates defective protein folding which abrogates protein-protein interactions and causes faulty pre-LSU rRNA processing, thus revealing one aspect of the molecular basis of this human disease. DOI: http://dx.doi.org/10.7554/eLife.16381.001 PMID:27077951

  14. The Intracellular Interactome of Tetraspanin-enriched Microdomains Reveals Their Function as Sorting Machineries toward Exosomes*

    PubMed Central

    Perez-Hernandez, Daniel; Gutiérrez-Vázquez, Cristina; Jorge, Inmaculada; López-Martín, Soraya; Ursa, Angeles; Sánchez-Madrid, Francisco; Vázquez, Jesús; Yáñez-Mó, María

    2013-01-01

    Extracellular vesicles are emerging as a potent mechanism of intercellular communication because they can systemically exchange genetic and protein material between cells. Tetraspanin molecules are commonly used as protein markers of extracellular vesicles, although their role in the unexplored mechanisms of cargo selection into exosomes has not been addressed. For that purpose, we have characterized the intracellular tetraspanin-enriched microdomain (TEM) interactome by high throughput mass spectrometry, in both human lymphoblasts and their derived exosomes, revealing a clear pattern of interaction networks. Proteins interacting with TEM receptors cytoplasmic regions presented a considerable degree of overlap, although some highly specific CD81 tetraspanin ligands, such as Rac GTPase, were detected. Quantitative proteomics showed that TEM ligands account for a great proportion of the exosome proteome and that a selective repertoire of CD81-associated molecules, including Rac, is not correctly routed to exosomes in cells from CD81-deficient animals. Our data provide evidence that insertion into TEM may be necessary for protein inclusion into the exosome structure. PMID:23463506

  15. Influenza virus-host interactome screen as a platform for antiviral drug development

    PubMed Central

    Watanabe, Tokiko; Kawakami, Eiryo; Shoemaker, Jason E.; Lopes, Tiago J. S.; Matsuoka, Yukiko; Tomita, Yuriko; Kozuka-Hata, Hiroko; Gorai, Takeo; Kuwahara, Tomoko; Takeda, Eiji; Nagata, Atsushi; Takano, Ryo; Kiso, Maki; Yamashita, Makoto; Sakai-Tagawa, Yuko; Katsura, Hiroaki; Nonaka, Naoki; Fujii, Hiroko; Fujii, Ken; Sugita, Yukihiko; Noda, Takeshi; Goto, Hideo; Fukuyama, Satoshi; Watanabe, Shinji; Neumann, Gabriele; Oyama, Masaaki; Kitano, Hiroaki; Kawaoka, Yoshihiro

    2015-01-01

    SUMMARY Host factors required for viral replication are ideal drug targets because they are less likely than viral proteins to mutate under drug-mediated selective pressure. Although genome-wide screens have identified host proteins involved in influenza virus replication, limited mechanistic understanding of how these factors affect influenza has hindered potential drug development. We conducted a systematic analysis to identify and validate host factors that associate with influenza virus proteins and affect viral replication. After identifying over one thousand host factors that co-immunoprecipitate with specific viral proteins, we generated a network of virus-host protein interactions based on the stage of the viral lifecycle affected upon host factor down-regulation. Using compounds that inhibit these host factors, we validated several proteins, notably Golgi-specific brefeldin A resistant guanine nucleotide exchange factor (GBF1) and JAK1, as potential antiviral drug targets. Thus, virus-host interactome screens are powerful strategies to identify targetable host factors and guide antiviral drug development. PMID:25464832

  16. Influenza virus-host interactome screen as a platform for antiviral drug development.

    PubMed

    Watanabe, Tokiko; Kawakami, Eiryo; Shoemaker, Jason E; Lopes, Tiago J S; Matsuoka, Yukiko; Tomita, Yuriko; Kozuka-Hata, Hiroko; Gorai, Takeo; Kuwahara, Tomoko; Takeda, Eiji; Nagata, Atsushi; Takano, Ryo; Kiso, Maki; Yamashita, Makoto; Sakai-Tagawa, Yuko; Katsura, Hiroaki; Nonaka, Naoki; Fujii, Hiroko; Fujii, Ken; Sugita, Yukihiko; Noda, Takeshi; Goto, Hideo; Fukuyama, Satoshi; Watanabe, Shinji; Neumann, Gabriele; Oyama, Masaaki; Kitano, Hiroaki; Kawaoka, Yoshihiro

    2014-12-10

    Host factors required for viral replication are ideal drug targets because they are less likely than viral proteins to mutate under drug-mediated selective pressure. Although genome-wide screens have identified host proteins involved in influenza virus replication, limited mechanistic understanding of how these factors affect influenza has hindered potential drug development. We conducted a systematic analysis to identify and validate host factors that associate with influenza virus proteins and affect viral replication. After identifying over 1,000 host factors that coimmunoprecipitate with specific viral proteins, we generated a network of virus-host protein interactions based on the stage of the viral life cycle affected upon host factor downregulation. Using compounds that inhibit these host factors, we validated several proteins, notably Golgi-specific brefeldin A-resistant guanine nucleotide exchange factor 1 (GBF1) and JAK1, as potential antiviral drug targets. Thus, virus-host interactome screens are powerful strategies to identify targetable host factors and guide antiviral drug development. PMID:25464832

  17. A semiparametric spatio-temporal model for solar irradiance data

    DOE PAGESBeta

    Patrick, Joshua D.; Harvill, Jane L.; Hansen, Clifford W.

    2016-03-01

    Here, we evaluate semiparametric spatio-temporal models for global horizontal irradiance at high spatial and temporal resolution. These models represent the spatial domain as a lattice and are capable of predicting irradiance at lattice points, given data measured at other lattice points. Using data from a 1.2 MW PV plant located in Lanai, Hawaii, we show that a semiparametric model can be more accurate than simple interpolation between sensor locations. We investigate spatio-temporal models with separable and nonseparable covariance structures and find no evidence to support assuming a separable covariance structure. These results indicate a promising approach for modeling irradiance atmore » high spatial resolution consistent with available ground-based measurements. Moreover, this kind of modeling may find application in design, valuation, and operation of fleets of utility-scale photovoltaic power systems.« less

  18. Precursor of transition to turbulence: spatiotemporal wave front.

    PubMed

    Bhaumik, S; Sengupta, T K

    2014-04-01

    To understand transition to turbulence via 3D disturbance growth, we report here results obtained from the solution of Navier-Stokes equation (NSE) to reproduce experimental results obtained by minimizing background disturbances and imposing deterministic excitation inside the shear layer. A similar approach was adopted in Sengupta and Bhaumik [Phys. Rev. Lett. 107, 154501 (2011)], where a route of transition from receptivity to fully developed turbulent stage was explained for 2D flow in terms of the spatio-temporal wave-front (STWF). The STWF was identified as the unit process of 2D turbulence creation for low amplitude wall excitation. Theoretical prediction of STWF for boundary layer was established earlier in Sengupta, Rao, and Venkatasubbaiah [Phys. Rev. Lett. 96, 224504 (2006)] from the Orr-Sommerfeld equation as due to spatiotemporal instability. Here, the same unit process of the STWF during transition is shown to be present for 3D disturbance field from the solution of governing NSE. PMID:24827343

  19. Spatio-temporal analysis of Salmonella surveillance data in Thailand.

    PubMed

    Domingues, A R; Vieira, A R; Hendriksen, R S; Pulsrikarn, C; Aarestrup, F M

    2014-08-01

    This study evaluates the usefulness of spatio-temporal statistical tools to detect outbreaks using routine surveillance data where limited epidemiological information is available. A dataset from 2002 to 2007 containing information regarding date, origin, source and serotype of 29,586 Salmonella isolates from Thailand was analysed. Data was grouped into human and non-human categories and the analysis was performed for the top five occurring serovars for each year of the study period. A total 91 human and 39 non-human significant spatio-temporal clusters were observed, accounting for 11% and 16% of the isolates, respectively. Serovar-specific associations between human and non-human clusters were also evaluated. Results show that these statistical tools can provide information for use in outbreak prevention and detection, in countries where only limited data is available. Moreover, it is suggested that monitoring non-human reservoirs can be relevant in predicting future Salmonella human cases. PMID:24103334

  20. Noise tolerant spatiotemporal chaos computing

    SciTech Connect

    Kia, Behnam; Kia, Sarvenaz; Ditto, William L.; Lindner, John F.; Sinha, Sudeshna

    2014-12-01

    We introduce and design a noise tolerant chaos computing system based on a coupled map lattice (CML) and the noise reduction capabilities inherent in coupled dynamical systems. The resulting spatiotemporal chaos computing system is more robust to noise than a single map chaos computing system. In this CML based approach to computing, under the coupled dynamics, the local noise from different nodes of the lattice diffuses across the lattice, and it attenuates each other's effects, resulting in a system with less noise content and a more robust chaos computing architecture.

  1. Noise tolerant spatiotemporal chaos computing.

    PubMed

    Kia, Behnam; Kia, Sarvenaz; Lindner, John F; Sinha, Sudeshna; Ditto, William L

    2014-12-01

    We introduce and design a noise tolerant chaos computing system based on a coupled map lattice (CML) and the noise reduction capabilities inherent in coupled dynamical systems. The resulting spatiotemporal chaos computing system is more robust to noise than a single map chaos computing system. In this CML based approach to computing, under the coupled dynamics, the local noise from different nodes of the lattice diffuses across the lattice, and it attenuates each other's effects, resulting in a system with less noise content and a more robust chaos computing architecture. PMID:25554030

  2. a Spatio-Temporal Framework for Modeling Active Layer Thickness

    NASA Astrophysics Data System (ADS)

    Touyz, J.; Streletskiy, D. A.; Nelson, F. E.; Apanasovich, T. V.

    2015-07-01

    The Arctic is experiencing an unprecedented rate of environmental and climate change. The active layer (the uppermost layer of soil between the atmosphere and permafrost that freezes in winter and thaws in summer) is sensitive to both climatic and environmental changes, and plays an important role in the functioning, planning, and economic activities of Arctic human and natural ecosystems. This study develops a methodology for modeling and estimating spatial-temporal variations in active layer thickness (ALT) using data from several sites of the Circumpolar Active Layer Monitoring network, and demonstrates its use in spatial-temporal interpolation. The simplest model's stochastic component exhibits no spatial or spatio-temporal dependency and is referred to as the naïve model, against which we evaluate the performance of the other models, which assume that the stochastic component exhibits either spatial or spatio-temporal dependency. The methods used to fit the models are then discussed, along with point forecasting. We compare the predicted fit of the various models at key study sites located in the North Slope of Alaska and demonstrate the advantages of space-time models through a series of error statistics such as mean squared error, mean absolute and percent deviance from observed data. We find the difference in performance between the spatio-temporal and remaining models is significant for all three error statistics. The best stochastic spatio-temporal model increases predictive accuracy, compared to the naïve model, of 33.3%, 36.2% and 32.5% on average across the three error metrics at the key sites for a one-year hold out period.

  3. A human B-cell interactome identifies MYB and FOXM1 as master regulators of proliferation in germinal centers

    PubMed Central

    Lefebvre, Celine; Rajbhandari, Presha; Alvarez, Mariano J; Bandaru, Pradeep; Lim, Wei Keat; Sato, Mai; Wang, Kai; Sumazin, Pavel; Kustagi, Manjunath; Bisikirska, Brygida C; Basso, Katia; Beltrao, Pedro; Krogan, Nevan; Gautier, Jean; Dalla-Favera, Riccardo; Califano, Andrea

    2010-01-01

    Assembly of a transcriptional and post-translational molecular interaction network in B cells, the human B-cell interactome (HBCI), reveals a hierarchical, transcriptional control module, where MYB and FOXM1 act as synergistic master regulators of proliferation in the germinal center (GC). Eighty percent of genes jointly regulated by these transcription factors are activated in the GC, including those encoding proteins in a complex regulating DNA pre-replication, replication, and mitosis. These results indicate that the HBCI analysis can be used for the identification of determinants of major human cell phenotypes and provides a paradigm of general applicability to normal and pathologic tissues. PMID:20531406

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

    SciTech Connect

    Davidson, George S.; Brown, William Michael

    2007-09-01

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

  5. Spatiotemporal Thinking in the Geosciences

    NASA Astrophysics Data System (ADS)

    Shipley, T. F.; Manduca, C. A.; Ormand, C. J.; Tikoff, B.

    2011-12-01

    Reasoning about spatial relations is a critical skill for geoscientists. Within the geosciences different disciplines may reason about different sorts of relationships. These relationships may span vastly different spatial and temporal scales (from the spatial alignment in atoms in crystals to the changes in the shape of plates). As part of work in a research center on spatial thinking in STEM education, we have been working to classify the spatial skills required in geology, develop tests for each spatial skill, and develop the cognitive science tools to promote the critical spatial reasoning skills. Research in psychology, neurology and linguistics supports a broad classification of spatial skills along two dimensions: one versus many objects (which roughly translates to object- focused and navigation focused skills) and static versus dynamic spatial relations. The talk will focus on the interaction of space and time in spatial cognition in the geosciences. We are working to develop measures of skill in visualizing spatiotemporal changes. A new test developed to measure visualization of brittle deformations will be presented. This is a skill that has not been clearly recognized in the cognitive science research domain and thus illustrates the value of interdisciplinary work that combines geosciences with cognitive sciences. Teaching spatiotemporal concepts can be challenging. Recent theoretical work suggests analogical reasoning can be a powerful tool to aid student learning to reason about temporal relations using spatial skills. Recent work in our lab has found that progressive alignment of spatial and temporal scales promotes accurate reasoning about temporal relations at geological time scales.

  6. Spatiotemporal evolution of ventricular fibrillation

    NASA Astrophysics Data System (ADS)

    Witkowski, Francis X.; Leon, L. Joshua; Penkoske, Patricia A.; Giles, Wayne R.; Spano, Mark L.; Ditto, William L.; Winfree, Arthur T.

    1998-03-01

    Sudden cardiac death is the leading cause of death in the industrialized world, with the majority of such tragedies being due to ventricular fibrillation. Ventricular fibrillation is a frenzied and irregular disturbance of the heart rhythm that quickly renders the heart incapable of sustaining life. Rotors, electrophysiological structures that emit rotating spiral waves, occur in several systems that all share with the heart the functional properties of excitability and refractoriness. These re-entrant waves, seen in numerical solutions of simplified models of cardiac tissue, may occur during ventricular tachycardias,. It has been difficult to detect such forms of re-entry in fibrillating mammalian ventricles. Here we show that, in isolated perfused dog hearts, high spatial and temporal resolution mapping of optical transmembrane potentials can easily detect transiently erupting rotors during the early phase of ventricular fibrillation. This activity is characterized by a relatively high spatiotemporal cross-correlation. During this early fibrillatory interval, frequent wavefront collisions and wavebreak generation are also dominant features. Interestingly, this spatiotemporal pattern undergoes an evolution to a less highly spatially correlated mechanism that lacks the epicardial manifestations of rotors despite continued myocardial perfusion.

  7. Anticancer activity of galactoxyloglucan polysaccharide-conjugated doxorubicin nanoparticles: Mechanistic insights and interactome analysis.

    PubMed

    Joseph, Manu M; Aravind, S R; George, Suraj K; Raveendran Pillai, K; Mini, S; Sreelekha, T T

    2015-06-01

    Toxicity associated with chemotherapeutic drugs such as doxorubicin (Dox), is one of the major obstacles that is currently affecting patients. PST-Dox (Galactoxyloglucan, PST001-conjugated Dox) nanoparticles were synthesized by encapsulating Dox with polysaccharide PST001, isolated from Tamarindus indica (Ti) by ionic gelation with tripolyphosphate (TPP). Herein, we demonstrate a detailed mechanistic and interactome network analysis that is specific to PST-Dox action in cancer cells and normal lymphocytes. Our results show that PST-Dox is superior to its parental counterparts, exhibiting a greater cytotoxicity by the induction of apoptosis against a wide variety of cancers by enhanced cellular uptake of Dox from the nanoparticle conjugates. Also, PST-Dox nanoparticles were non-toxic to normal lymphocytes with limited immunostimulatory effects up to certain doses. Elucidation of molecular mechanism by whole genome microarray in cancer cells and lymphocytes revealed that a large number of genes were dysregulated specifically in cancer cells. Specifically, a unique target gene EGR1, contextually determined translational activation of P53 in the cancerous and non-cancerous cells. Most of the key downregulated genes were tyrosine kinases, indicating the potential inhibitory action of PST-Dox on tyrosine kinase oncogenic pathways. Western blotting of proteins corresponding to the genes that were altered at the genomic level was very well correlated in the majority of them, except in a few that demonstrated post-transcriptional modifications. The important findings and highly disciplined approaches highlighted in the present study will speed up the therapeutic potential of this augmented nanoparticle formulation for more robust clinical studies and testing in several cancers. PMID:25864443

  8. The phosphotyrosine interactome of the insulin receptor family and its substrates IRS-1 and IRS-2.

    PubMed

    Hanke, Stefan; Mann, Matthias

    2009-03-01

    The insulin signaling pathway is critical in regulating glucose levels and is associated with diabetes, obesity, and longevity. A tyrosine phosphorylation cascade creates docking sites for protein interactions, initiating subsequent propagation of the signal throughout the cell. The phosphotyrosine interactome of this medically important pathway has not yet been studied comprehensively. We therefore applied quantitative interaction proteomics to exhaustively profile all potential phosphotyrosine-dependent interaction sites in its key players. We targeted and compared insulin receptor substrates 1 and 2 (IRS-1 and IRS-2) as central distributors of the insulin signal, the insulin receptor, the insulin-like growth factor 1 receptor, and the insulin receptor-related receptor. Using the stable isotope labeling by amino acids in cell culture (SILAC) approach with phosphorylated versus non-phosphorylated bait peptides, we found phosphorylation-specific interaction partners for 52 out of 109 investigated sites. In addition, doubly and triply phosphorylated motifs provided insight into the combinatorial effects of phosphorylation events in close proximity to each other. Our results retrieve known interactions and substantially broaden the spectrum of potential interaction partners of IRS-1 and IRS-2. A large number of common interactors rationalize their extensive functional redundancy. However, several proteins involved in signaling and metabolism interact differentially with IRS-1 and IRS-2 and thus provide leads into their different physiological roles. Differences in interactions at the receptor level are reflected in multisite recruitment of SHP2 by the insulin-like growth factor 1 receptor and limited but exclusive interactions with the IRR. In common with other recent reports, our data furthermore hint at non-SH2 or phosphotyrosine-binding domain-mediated phosphotyrosine binding. PMID:19001411

  9. Quantitative network mapping of the human kinome interactome reveals new clues for rational kinase inhibitor discovery and individualized cancer therapy

    PubMed Central

    Cheng, Feixiong; Jia, Peilin; Wang, Quan; Zhao, Zhongming

    2014-01-01

    The human kinome is gaining importance through its promising cancer therapeutic targets, yet no general model to address the kinase inhibitor resistance has emerged. Here, we constructed a systems biology-based framework to catalogue the human kinome, including 538 kinase genes, in the broader context of the human interactome. Specifically, we constructed three networks: a kinase-substrate interaction network containing 7,346 pairs connecting 379 kinases to 36,576 phosphorylation sites in 1,961 substrates, a protein-protein interaction network (PPIN) containing 92,699 pairs, and an atomic resolution PPIN containing 4,278 pairs. We identified the conserved regulatory phosphorylation motifs (e.g., Ser/Thr-Pro) using a sequence logo analysis. We found the typical anticancer target selection strategy that uses network hubs as drug targets, might lead to a high adverse drug reaction risk. Furthermore, we found the distinct network centrality of kinases creates a high anticancer drug resistance risk by feedback or crosstalk mechanisms within cellular networks. This notion is supported by the systematic network and pathway analyses that anticancer drug resistance genes are significantly enriched as hubs and heavily participate in multiple signaling pathways. Collectively, this comprehensive human kinome interactome map sheds light on anticancer drug resistance mechanisms and provides an innovative resource for rational kinase inhibitor design. PMID:25003367

  10. The Cellular Interactome of the Coronavirus Infectious Bronchitis Virus Nucleocapsid Protein and Functional Implications for Virus Biology

    PubMed Central

    Munday, Diane; Bickerton, Erica; Britton, Paul; Rodgers, Mark A.; Whitehouse, Adrian; Zhou, En-Min

    2013-01-01

    The coronavirus nucleocapsid (N) protein plays a multifunctional role in the virus life cycle, from regulation of replication and transcription and genome packaging to modulation of host cell processes. These functions are likely to be facilitated by interactions with host cell proteins. The potential interactome of the infectious bronchitis virus (IBV) N protein was mapped using stable isotope labeling with amino acids in cell culture (SILAC) coupled to a green fluorescent protein-nanotrap pulldown methodology and liquid chromatography-tandem mass spectrometry. The addition of the SILAC label allowed discrimination of proteins that were likely to specifically bind to the N protein over background binding. Overall, 142 cellular proteins were selected as potentially binding to the N protein, many as part of larger possible complexes. These included ribosomal proteins, nucleolar proteins, translation initiation factors, helicases, and hnRNPs. The association of selected cellular proteins with IBV N protein was confirmed by immunoblotting, cosedimentation, and confocal microscopy. Further, the localization of selected proteins in IBV-infected cells as well as their activity during virus infection was assessed by small interfering RNA-mediated depletion, demonstrating the functional importance of cellular proteins in the biology of IBV. This interactome not only confirms previous observations made with other coronavirus and IBV N proteins with both overexpressed proteins and infectious virus but also provides novel data that can be exploited to understand the interaction between the virus and the host cell. PMID:23637410

  11. Susceptibility genes are enriched in those of the herpes simplex virus 1/host interactome in psychiatric and neurological disorders.

    PubMed

    Carter, Chris J

    2013-12-01

    Herpes simplex virus 1 (HSV-1) can promote beta-amyloid deposition and tau phosphorylation, demyelination or cognitive deficits relevant to Alzheimer's disease or multiple sclerosis and to many neuropsychiatric disorders with which it has been implicated. A seroprevalence much higher than disease incidence has called into question any primary causal role. However, as also the case with risk-promoting polymorphisms (also present in control populations), any causal effects are likely to be conditional. During its life cycle, the virus binds to many proteins and modifies the expression of multiple genes creating a host/pathogen interactome involving 1347 host genes. This data set is heavily enriched in the susceptibility genes for multiple sclerosis (P = 1.3E-99) > Alzheimer's disease > schizophrenia > Parkinsonism > depression > bipolar disorder > childhood obesity > chronic fatigue > autism > and anorexia (P = 0.047) but not attention deficit hyperactivity disorder, a relationship maintained for genome-wide association study data sets in multiple sclerosis and Alzheimer's disease. Overlapping susceptibility gene/interactome data sets disrupt signalling networks relevant to each disease, suggesting that disease susceptibility genes may filter the attentions of the pathogen towards particular pathways and pathologies. In this way, the same pathogen could contribute to multiple diseases in a gene-dependent manner and condition the risk-promoting effects of the genes whose function it disrupts. PMID:23913659

  12. Quantitative network mapping of the human kinome interactome reveals new clues for rational kinase inhibitor discovery and individualized cancer therapy.

    PubMed

    Cheng, Feixiong; Jia, Peilin; Wang, Quan; Zhao, Zhongming

    2014-06-15

    The human kinome is gaining importance through its promising cancer therapeutic targets, yet no general model to address the kinase inhibitor resistance has emerged. Here, we constructed a systems biology-based framework to catalogue the human kinome, including 538 kinase genes, in the broader context of the human interactome. Specifically, we constructed three networks: a kinase-substrate interaction network containing 7,346 pairs connecting 379 kinases to 36,576 phosphorylation sites in 1,961 substrates, a protein-protein interaction network (PPIN) containing 92,699 pairs, and an atomic resolution PPIN containing 4,278 pairs. We identified the conserved regulatory phosphorylation motifs (e.g., Ser/Thr-Pro) using a sequence logo analysis. We found the typical anticancer target selection strategy that uses network hubs as drug targets, might lead to a high adverse drug reaction risk. Furthermore, we found the distinct network centrality of kinases creates a high anticancer drug resistance risk by feedback or crosstalk mechanisms within cellular networks. This notion is supported by the systematic network and pathway analyses that anticancer drug resistance genes are significantly enriched as hubs and heavily participate in multiple signaling pathways. Collectively, this comprehensive human kinome interactome map sheds light on anticancer drug resistance mechanisms and provides an innovative resource for rational kinase inhibitor design. PMID:25003367

  13. JAK2-Centered Interactome Hotspot Identified by an Integrative Network Algorithm in Acute Stanford Type A Aortic Dissection

    PubMed Central

    Teschendorff, Andrew E.; Hong, Tao; Wang, Linyan; Qian, Mengjia; Wang, Chunsheng; Wang, Xiangdong

    2014-01-01

    The precise mechanisms underlying dissections, especially those without connective tissue diseases or congenital vascular diseases, are incompletely understood. This study attempted to identify both the expression profile of the dissected ascending aorta and the interactome hotspots associated with the disease, using microarray technology and gene regulatory network analysis. There were 2,737 genes differentially expressed between patients with acute Stanford type A aortic dissection and controls. Eight interactome hotspots significantly associated with aortic dissection were identified by an integrative network algorithm. In particular, we identified a JAK2-centered expression module, which was validated in an independent gene expression microarray data set, and which was characterized by over-expressed cytokines and receptors in acute aortic dissection cases, indicating that JAK2 may play a key role in the inflammatory process, which potentially contributes to the occurrence of acute aortic dissection. Overall, the analytical strategy used in this study offered the possibility to identify functional relevant network modules and subsequently facilitated the biological interpretation in the complicated disease. PMID:24586754

  14. 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

  15. Mapping the H+ (V)-ATPase interactome: identification of proteins involved in trafficking, folding, assembly and phosphorylation

    PubMed Central

    Merkulova, Maria; Păunescu, Teodor G.; Azroyan, Anie; Marshansky, Vladimir; Breton, Sylvie; Brown, Dennis

    2015-01-01

    V-ATPases (H+ ATPases) are multisubunit, ATP-dependent proton pumps that regulate pH homeostasis in virtually all eukaryotes. They are involved in key cell biological processes including vesicle trafficking, endosomal pH sensing, membrane fusion and intracellular signaling. They also have critical systemic roles in renal acid excretion and blood pH balance, male fertility, bone remodeling, synaptic transmission, olfaction and hearing. Furthermore, V-ATPase dysfunction either results in or aggravates various other diseases, but little is known about the complex protein interactions that regulate these varied V-ATPase functions. Therefore, we performed a proteomic analysis to identify V-ATPase associated proteins and construct a V-ATPase interactome. Our analysis using kidney tissue revealed V-ATPase-associated protein clusters involved in protein quality control, complex assembly and intracellular trafficking. ARHGEF7, DMXL1, EZR, NCOA7, OXR1, RPS6KA3, SNX27 and 9 subunits of the chaperonin containing TCP1 complex (CCT) were found to interact with V-ATPase for the first time in this study. Knockdown of two interacting proteins, DMXL1 and WDR7, inhibited V-ATPase-mediated intracellular vesicle acidification in a kidney cell line, providing validation for the utility of our interactome as a screen for functionally important novel V-ATPase-regulating proteins. Our data, therefore, provide new insights and directions for the analysis of V-ATPase cell biology and (patho)physiology. PMID:26442671

  16. Spatiotemporal behavior and nonlinear dynamics in a phase conjugate resonator

    NASA Technical Reports Server (NTRS)

    Liu, Siuying Raymond

    1993-01-01

    The work described can be divided into two parts. The first part is an investigation of the transient behavior and stability property of a phase conjugate resonator (PCR) below threshold. The second part is an experimental and theoretical study of the PCR's spatiotemporal dynamics above threshold. The time-dependent coupled wave equations for four-wave mixing (FWM) in a photorefractive crystal, with two distinct interaction regions caused by feedback from an ordinary mirror, was used to model the transient dynamics of a PCR below threshold. The conditions for self-oscillation were determined and the solutions were used to define the PCR's transfer function and analyze its stability. Experimental results for the buildup and decay times confirmed qualitatively the predicted behavior. Experiments were carried out above threshold to study the spatiotemporal dynamics of the PCR as a function of Pragg detuning and the resonator's Fresnel number. The existence of optical vortices in the wavefront were identified by optical interferometry. It was possible to describe the transverse dynamics and the spatiotemporal instabilities by modeling the three-dimensional-coupled wave equations in photorefractive FWM using a truncated modal expansion approach.

  17. Spatiotemporal System Identification With Continuous Spatial Maps and Sparse Estimation.

    PubMed

    Aram, Parham; Kadirkamanathan, Visakan; Anderson, Sean R

    2015-11-01

    We present a framework for the identification of spatiotemporal linear dynamical systems. We use a state-space model representation that has the following attributes: 1) the number of spatial observation locations are decoupled from the model order; 2) the model allows for spatial heterogeneity; 3) the model representation is continuous over space; and 4) the model parameters can be identified in a simple and sparse estimation procedure. The model identification procedure we propose has four steps: 1) decomposition of the continuous spatial field using a finite set of basis functions where spatial frequency analysis is used to determine basis function width and spacing, such that the main spatial frequency contents of the underlying field can be captured; 2) initialization of states in closed form; 3) initialization of state-transition and input matrix model parameters using sparse regression-the least absolute shrinkage and selection operator method; and 4) joint state and parameter estimation using an iterative Kalman-filter/sparse-regression algorithm. To investigate the performance of the proposed algorithm we use data generated by the Kuramoto model of spatiotemporal cortical dynamics. The identification algorithm performs successfully, predicting the spatiotemporal field with high accuracy, whilst the sparse regression leads to a compact model. PMID:25647667

  18. 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. PMID:26922696

  19. 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 ?23-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

  20. Computational genomic analysis of PARK7 interactome reveals high BBS1 gene expression as a prognostic factor favoring survival in malignant pleural mesothelioma.

    PubMed

    Vavougios, Georgios D; Solenov, Evgeniy I; Hatzoglou, Chrissi; Baturina, Galina S; Katkova, Liubov E; Molyvdas, Paschalis Adam; Gourgoulianis, Konstantinos I; Zarogiannis, Sotirios G

    2015-10-01

    The aim of our study was to assess the differential gene expression of Parkinson protein 7 (PARK7) interactome in malignant pleural mesothelioma (MPM) using data mining techniques to identify novel candidate genes that may play a role in the pathogenicity of MPM. We constructed the PARK7 interactome using the ConsensusPathDB database. We then interrogated the Oncomine Cancer Microarray database using the Gordon Mesothelioma Study, for differential gene expression of the PARK7 interactome. In ConsensusPathDB, 38 protein interactors of PARK7 were identified. In the Gordon Mesothelioma Study, 34 of them were assessed out of which SUMO1, UBC3, KIAA0101, HDAC2, DAXX, RBBP4, BBS1, NONO, RBBP7, HTRA2, and STUB1 were significantly overexpressed whereas TRAF6 and MTA2 were significantly underexpressed in MPM patients (network 2). Furthermore, Kaplan-Meier analysis revealed that MPM patients with high BBS1 expression had a median overall survival of 16.5 vs. 8.7 mo of those that had low expression. For validation purposes, we performed a meta-analysis in Oncomine database in five sarcoma datasets. Eight network 2 genes (KIAA0101, HDAC2, SUMO1, RBBP4, NONO, RBBP7, HTRA2, and MTA2) were significantly differentially expressed in an array of 18 different sarcoma types. Finally, Gene Ontology annotation enrichment analysis revealed significant roles of the PARK7 interactome in NuRD, CHD, and SWI/SNF protein complexes. In conclusion, we identified 13 novel genes differentially expressed in MPM, never reported before. Among them, BBS1 emerged as a novel predictor of overall survival in MPM. Finally, we identified that PARK7 interactome is involved in novel pathways pertinent in MPM disease. PMID:26254420

  1. Forecasting the Spatio-Temporal Dynamics of the Magnetosphere

    NASA Astrophysics Data System (ADS)

    Chen, J.; Sharma, A.; Veeramani, T.

    2007-12-01

    The spatio-temporal dynamics of the magnetosphere is a crucial component of effective space weather forecasting. The extensive data of the solar wind-magnetosphere interaction has been used to build predictive models of the magnetosphere based on nonlinear dynamical approaches. The time series data of the distributed observations are used to develop spatio-temporal dynamics of the magnetosphere. In this approach the solar wind - magnetosphere coupling is modeled as an input-output system with the solar wind variables as the input and the magnetic field variations at the ground stations as the magnetospheric response. The magnetic field perturbation at the ground and the corresponding solar wind data stations during the solar maximum period are compiled for these studies. The ground magnetometer data are from from CANOPUS, IMAGE and WDC magnetometer chain of stations. This new data set is used to study the spatio-temporal structure, including the coupling between the high and mid-latitude regions. A technique that utilizes the daily rotation of the Earth as a longitudinal sampling process is used to construct a two dimensional representation of the high latitude magnetic perturbations both in magnetic latitude and magnetic local time. This nonlinear model is used to predict the spatial structure of geomagnetic disturbances during intense geospace storms. In order to understand the predictability of space weather, the correlated database is used to study the causal relationships based on information theoretic approaches. This yields the mutual information between the solar wind variables and the ground magnetic field variations, and among the ground stations themselves. The information flow within the coupled system is analyzed by computing the transfer entropy among them.

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

    PubMed Central

    Bish, Rebecca; Cuevas-Polo, Nerea; Cheng, Zhe; Hambardzumyan, Dolores; Munschauer, Mathias; Landthaler, Markus; Vogel, Christine

    2015-01-01

    DDX6 (p54/RCK) is a human RNA helicase with central roles in mRNA decay and translation repression. To help our understanding of how DDX6 performs these multiple functions, we conducted the first unbiased, large-scale study to map the DDX6-centric protein-protein interactome using immunoprecipitation and mass spectrometry. Using DDX6 as bait, we identify a high-confidence and high-quality set of protein interaction partners which are enriched for functions in RNA metabolism and ribosomal proteins. The screen is highly specific, maximizing the number of true positives, as demonstrated by the validation of 81% (47/58) of the RNA-independent interactors through known functions and interactions. Importantly, we minimize the number of indirect interaction partners through use of a nuclease-based digestion to eliminate RNA. We describe eleven new interactors, including proteins involved in splicing which is an as-yet unknown role for DDX6. We validated and characterized in more detail the interaction of DDX6 with Nuclear fragile X mental retardation-interacting protein 2 (NUFIP2) and with two previously uncharacterized proteins, FAM195A and FAM195B (here referred to as granulin-1 and granulin-2, or GRAN1 and GRAN2). We show that NUFIP2, GRAN1, and GRAN2 are not P-body components, but re-localize to stress granules upon exposure to stress, suggesting a function in translation repression in the cellular stress response. Using a complementary analysis that resolved DDX6’s multiple complex memberships, we further validated these interaction partners and the presence of splicing factors. As DDX6 also interacts with the E3 SUMO ligase TIF1β, we tested for and observed a significant enrichment of sumoylation amongst DDX6’s interaction partners. Our results represent the most comprehensive screen for direct interaction partners of a key regulator of RNA life cycle and localization, highlighting new stress granule components and possible DDX6 functions—many of which are likely conserved across eukaryotes. PMID:26184334

  3. A weighted and integrated drug-target interactome: drug repurposing for schizophrenia as a use case

    PubMed Central

    2015-01-01

    Background Computational pharmacology can uniquely address some issues in the process of drug development by providing a macroscopic view and a deeper understanding of drug action. Specifically, network-assisted approach is promising for the inference of drug repurposing. However, the drug-target associations coming from different sources and various assays have much noise, leading to an inflation of the inference errors. To reduce the inference errors, it is necessary and critical to create a comprehensive and weighted data set of drug-target associations. Results In this study, we created a weighted and integrated drug-target interactome (WinDTome) to provide a comprehensive resource of drug-target associations for computational pharmacology. We first collected drug-target interactions from six commonly used drug-target centered data sources including DrugBank, KEGG, TTD, MATADOR, PDSP Ki Database, and BindingDB. Then, we employed the record linkage method to normalize drugs and targets to the unique identifiers by utilizing the public data sources including PubChem, Entrez Gene, and UniProt. To assess the reliability of the drug-target associations, we assigned two scores (Score_S and Score_R) to each drug-target association based on their data sources and publication references. Consequently, the WinDTome contains 546,196 drug-target associations among 303,018 compounds and 4,113 genes. To assess the application of the WinDTome, we designed a network-based approach for drug repurposing using mental disorder schizophrenia (SCZ) as a case. Starting from 41 known SCZ drugs and their targets, we inferred a total of 264 potential SCZ drugs through the associations of drug-target with Score_S higher than two in WinDTome and human protein-protein interactions. Among the 264 SCZ-related drugs, 39 drugs have been investigated in clinical trials for SCZ treatment and 74 drugs for the treatment of other mental disorders, respectively. Compared with the results using other Score_S cutoff values, single data source, or the data from STITCH, the inference of 264 SCZ-related drugs had the highest performance. Conclusions The WinDTome generated in this study contains comprehensive drug-target associations with confidence scores. Its application to the SCZ drug repurposing demonstrated that the WinDTome is promising to serve as a useful resource for drug repurposing. PMID:26100720

  4. Spatio-Temporal Clustering of Monitoring Network

    NASA Astrophysics Data System (ADS)

    Hussain, I.; Pilz, J.

    2009-04-01

    Pakistan has much diversity in seasonal variation of different locations. Some areas are in desserts and remain very hot and waterless, for example coastal areas are situated along the Arabian Sea and have very warm season and a little rainfall. Some areas are covered with mountains, have very low temperature and heavy rainfall; for instance Karakoram ranges. The most important variables that have an impact on the climate are temperature, precipitation, humidity, wind speed and elevation. Furthermore, it is hard to find homogeneous regions in Pakistan with respect to climate variation. Identification of homogeneous regions in Pakistan can be useful in many aspects. It can be helpful for prediction of the climate in the sub-regions and for optimizing the number of monitoring sites. In the earlier literature no one tried to identify homogeneous regions of Pakistan with respect to climate variation. There are only a few papers about spatio-temporal clustering of monitoring network. Steinhaus (1956) presented the well-known K-means clustering method. It can identify a predefined number of clusters by iteratively assigning centriods to clusters based. Castro et al. (1997) developed a genetic heuristic algorithm to solve medoids based clustering. Their method is based on genetic recombination upon random assorting recombination. The suggested method is appropriate for clustering the attributes which have genetic characteristics. Sap and Awan (2005) presented a robust weighted kernel K-means algorithm incorporating spatial constraints for clustering climate data. The proposed algorithm can effectively handle noise, outliers and auto-correlation in the spatial data, for effective and efficient data analysis by exploring patterns and structures in the data. Soltani and Modarres (2006) used hierarchical and divisive cluster analysis to categorize patterns of rainfall in Iran. They only considered rainfall at twenty-eight monitoring sites and concluded that eight clusters existed. Soltani and Modarres (2006) classified the sites by using only average rainfall of sites, they did not consider time replications and spatial coordinates. Kerby et.al (2007) purposed spatial clustering method based on likelihood. They took account of the geographic locations through the variance covariance matrix. Their purposed method works like hierarchical clustering methods. Moreovere, it is inappropiriate for time replication data and could not perform well for large number of sites. Tuia.et.al (2008) used scan statistics for identifying spatio-temporal clusters for fire sequences in the Tuscany region in Italy. The scan statistics clustering method was developed by Kulldorff et al. (1997) to detect spatio-temporal clusters in epidemiology and assessing their significance. The purposed scan statistics method is used only for univariate discrete stochastic random variables. In this paper we make use of a very simple approach for spatio-temporal clustering which can create separable and homogeneous clusters. Most of the clustering methods are based on Euclidean distances. It is well known that geographic coordinates are spherical coordinates and estimating Euclidean distances from spherical coordinates is inappropriate. As a transformation from geographic coordinates to rectangular (D-plane) coordinates we use the Lambert projection method. The partition around medoids clustering method is incorporated on the data including D-plane coordinates. Ordinary kriging is taken as validity measure for the precipitation data. The kriging results for clusters are more accurate and have less variation compared to complete monitoring network precipitation data. References Casto.V.E and Murray.A.T (1997). Spatial Clustering with Data Mining with Genetic Algorithms. http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.56.8573 Kaufman.L and Rousseeuw.P.J (1990). Finding Groups in Data: An Introduction to Cluster Analysis. Wiley series of Probability and Mathematical Statistics, New York. Kulldorf.M (1997). A spatial scan statistic. Commun. Stat.-Theor. Math. 26(6), 1481-1496 Kerby. A , Marx. D, Samal. A and Adamchuck. V. (2007). Spatial Clustering Using the Likelihood Function. Seventh IEEE International Conference on Data Mining - Workshops Steinhaus.H (1956). Sur la division des corp materiels en parties. Bull. Acad. Polon. Sci., C1. III vol IV:801- 804 Snyder, J. P. (1987). Map Projection: A Working Manual. U. S. Geological Survey Professional Paper 1395. Washington, DC: U. S. Government Printing Office, pp. 104-110 Sap.M.N and Awan. A.M (2005). Finding Spatio-Temporal Patterns in Climate Data Using Clustering. Proceedings of the International Conference on Cyberworlds (CW'05) Soltani.S and Modarres.R (2006). Classification of Spatio -Temporal Pattern of Rainfall in Iran: Using Hierarchical and Divisive Cluster Analysis. Journal of Spatial Hydrology Vol.6, No.2 Tuia.D, Ratle.F, Lasaponara.R, Telesca.L and Kanevski.M (2008). Scan Statistics Analysis for Forest Fire Clusters. Commun. in Nonlinear science and numerical simulation 13,1689-1694.

  5. 3D hybrid wound devices for spatiotemporally controlled release kinetics.

    PubMed

    Ozbolat, Ibrahim T; Koc, Bahattin

    2012-12-01

    This paper presents localized and temporal control of release kinetics over 3-dimensional (3D) hybrid wound devices to improve wound-healing process. Imaging study is performed to extract wound bed geometry in 3D. Non-Uniform Rational B-Splines (NURBS) based surface lofting is applied to generate functionally graded regions. Diffusion-based release kinetics model is developed to predict time-based release of loaded modifiers for functionally graded regions. Multi-chamber single nozzle solid freeform dispensing system is used to fabricate wound devices with controlled dispensing concentration. Spatiotemporal control of biological modifiers thus enables a way to achieve target delivery to improve wound healing. PMID:22672934

  6. Spatiotemporal Communication with Synchronized Optical Chaos

    NASA Astrophysics Data System (ADS)

    García-Ojalvo, J.; Roy, Rajarshi

    2001-05-01

    We propose a model system that allows communication of spatiotemporal information using an optical chaotic carrier waveform. The system is based on broad-area nonlinear optical ring cavities, which exhibit spatiotemporal chaos in a wide parameter range. Message recovery is possible through chaotic synchronization between transmitter and receiver. Numerical simulations demonstrate the feasibility of the proposed scheme, and the benefit of the parallelism of information transfer with optical wave fronts.

  7. Spatiotemporal recurrences of sandpile avalanches

    NASA Astrophysics Data System (ADS)

    Tarun, Anjali B.; Paguirigan, Antonino A.; Batac, Rene C.

    2015-10-01

    We study the space and time properties of avalanches in a continuous sandpile model by constructing a temporally directed network linking together the recurrent avalanche events based on their spatial separation. We use two different criteria for network construction: a later event is connected to a previous one if it is either nearest or farthest from it among all the later events. With this, we observe scale-free regimes emerge as characterized by the following power-law exponents: (a) α = 1.7 for the avalanche size distributions; (b) βF = 2.1 in the in-degree distribution of farthest recurrences; (c) δ = 1 for the separation distances; and (d) γ = 1 for the temporal separations of recurrences. Our results agree with earlier observations that describe the sandpile avalanches as repulsive events, i.e. the next avalanche is more likely to be physically separated from an earlier one. These observations, which are not captured by usual interoccurrence statistics and by random connection mechanisms, suggest an underlying spatiotemporal organization in the sandpile that makes it useful for modeling real-world systems.

  8. 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

  9. Proteomic Analysis of the SH2Domain-containing Leukocyte Protein of 76 kDa (SLP76) Interactome*

    PubMed Central

    Bounab, Yacine; Hesse, Anne-Marie-; Iannascoli, Bruno; Grieco, Luca; Cout, Yohann; Niarakis, Anna; Roncagalli, Romain; Lie, Eunkyung; Lam, Kong-Peng; Demangel, Caroline; Thieffry, Denis; Garin, Jrme; Malissen, Bernard; Daron, Marc

    2013-01-01

    We report the first proteomic analysis of the SLP76 interactome in resting and activated primary mouse mast cells. This was made possible by a novel genetic approach used for the first time here. It consists in generating knock-in mice that express signaling molecules bearing a C-terminal tag that has a high affinity for a streptavidin analog. Tagged molecules can be used as molecular baits to affinity-purify the molecular complex in which they are engaged, which can then be studied by mass spectrometry. We examined first SLP76 because, although this cytosolic adapter is critical for both T cell and mast cell activation, its role is well known in T cells but not in mast cells. Tagged SLP76 was expressed in physiological amounts and fully functional in mast cells. We unexpectedly found that SLP76 is exquisitely sensitive to mast cell granular proteases, that Zn2+-dependent metalloproteases are especially abundant in mast cells and that they were responsible for SLP76 degradation. Adding a Zn2+ chelator fully protected SLP76 in mast cell lysates, thereby enabling an efficient affinity-purification of this adapter with its partners. Label-free quantitative mass spectrometry analysis of affinity-purified SLP76 interactomes uncovered both partners already described in T cells and novel partners seen in mast cells only. Noticeably, molecules inducibly recruited in both cell types primarily concur to activation signals, whereas molecules recruited in activated mast cells only are mostly associated with inhibition signals. The transmembrane adapter LAT2, and the serine/threonine kinase with an exchange factor activity Bcr were the most recruited molecules. Biochemical and functional validations established the unexpected finding that Bcr is recruited by SLP76 and positively regulates antigen-induced mast cell activation. Knock-in mice expressing tagged molecules with a normal tissue distribution and expression therefore provide potent novel tools to investigate signalosomes and to uncover novel signaling molecules in mast cells. PMID:23820730

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

    PubMed

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

    2012-01-01

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

  11. 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

  12. Bayesian spatio-temporal analysis and geospatial risk factors of human monocytic ehrlichiosis.

    PubMed

    Raghavan, Ram K; Neises, Daniel; Goodin, Douglas G; Andresen, Daniel A; Ganta, Roman R

    2014-01-01

    Variations in spatio-temporal patterns of Human Monocytic Ehrlichiosis (HME) infection in the state of Kansas, USA were examined and the relationship between HME relative risk and various environmental, climatic and socio-economic variables were evaluated. HME data used in the study was reported to the Kansas Department of Health and Environment between years 2005-2012, and geospatial variables representing the physical environment [National Land cover/Land use, NASA Moderate Resolution Imaging Spectroradiometer (MODIS)], climate [NASA MODIS, Prediction of Worldwide Renewable Energy (POWER)], and socio-economic conditions (US Census Bureau) were derived from publicly available sources. Following univariate screening of candidate variables using logistic regressions, two Bayesian hierarchical models were fit; a partial spatio-temporal model with random effects and a spatio-temporal interaction term, and a second model that included additional covariate terms. The best fitting model revealed that spatio-temporal autocorrelation in Kansas increased steadily from 2005-2012, and identified poverty status, relative humidity, and an interactive factor, 'diurnal temperature range x mixed forest area' as significant county-level risk factors for HME. The identification of significant spatio-temporal pattern and new risk factors are important in the context of HME prevention, for future research in the areas of ecology and evolution of HME, and as well as climate change impacts on tick-borne diseases. PMID:24992684

  13. Spatiotemporal features for asynchronous event-based data

    PubMed Central

    Lagorce, Xavier; Ieng, Sio-Hoi; Clady, Xavier; Pfeiffer, Michael; Benosman, Ryad B.

    2015-01-01

    Bio-inspired asynchronous event-based vision sensors are currently introducing a paradigm shift in visual information processing. These new sensors rely on a stimulus-driven principle of light acquisition similar to biological retinas. They are event-driven and fully asynchronous, thereby reducing redundancy and encoding exact times of input signal changes, leading to a very precise temporal resolution. Approaches for higher-level computer vision often rely on the reliable detection of features in visual frames, but similar definitions of features for the novel dynamic and event-based visual input representation of silicon retinas have so far been lacking. This article addresses the problem of learning and recognizing features for event-based vision sensors, which capture properties of truly spatiotemporal volumes of sparse visual event information. A novel computational architecture for learning and encoding spatiotemporal features is introduced based on a set of predictive recurrent reservoir networks, competing via winner-take-all selection. Features are learned in an unsupervised manner from real-world input recorded with event-based vision sensors. It is shown that the networks in the architecture learn distinct and task-specific dynamic visual features, and can predict their trajectories over time. PMID:25759637

  14. Spatiotemporal neural pattern similarity supports episodic memory.

    PubMed

    Lu, Yi; Wang, Changming; Chen, Chuansheng; Xue, Gui

    2015-03-16

    Formal computational models of human memory posit a central role of feature representations in episodic memory encoding and retrieval [1-4]. Correspondingly, fMRI studies have found that, in addition to activity level [5, 6], the neural activation pattern similarity across repetitions (i.e., self-similarity) was greater for subsequently remembered than forgotten items [7-9]. This self-similarity has been suggested to reflect pattern reinstatement due to study-phase retrieval [7, 10, 11]. However, the low temporal resolution of fMRI measures could determine neither the temporal precision of study-phase reinstatement nor the processing stage at which the reinstatement supported subsequent memory [12]. Meanwhile, although self-similarity has been shown to correlate with the activity level in the left lateral prefrontal cortex (LPFC) [10, 13], a causal link between left LPFC function and pattern similarity remains to be established. Combining transcranial direct current stimulation (tDCS) and EEG, we found that greater spatiotemporal pattern similarity (STPS) across repetitions of the same item (i.e., self-STPS) during encoding predicted better subsequent memory. The self-STPS located in the right frontal electrodes occurred approximately 500 ms after stimulus onset, reflected item-specific encoding, and contributed to memory above and beyond the effects of ERP amplitude and global pattern similarity (i.e., similarity to all other items in memory space). Anodal stimulation over the left LPFC specifically enhanced memory performance and item-specific STPS in the right frontal electrodes. These results support a causal role of LPFC in enhancing STPS and memory and contribute to a mechanistic understanding of memory formation. PMID:25728695

  15. Mercury Toolset for Spatiotemporal Metadata

    NASA Astrophysics Data System (ADS)

    Devarakonda, Ranjeet; Palanisamy, Giri; Green, James; Wilson, Bruce; Rhyne, B. Timothy; Lindsley, Chris

    2010-06-01

    Mercury (http://mercury.ornl.gov) is a set of tools for federated harvesting, searching, and retrieving metadata, particularly spatiotemporal metadata. Version 3.0 of the Mercury toolset provides orders of magnitude improvements in search speed, support for additional metadata formats, integration with Google Maps for spatial queries, facetted type search, support for RSS (Really Simple Syndication) delivery of search results, and enhanced customization to meet the needs of the multiple projects that use Mercury. It provides a single portal to very quickly search for data and information contained in disparate data management systems, each of which may use different metadata formats. Mercury harvests metadata and key data from contributing project servers distributed around the world and builds a centralized index. The search interfaces then allow the users to perform a variety of fielded, spatial, and temporal searches across these metadata sources. This centralized repository of metadata with distributed data sources provides extremely fast search results to the user, while allowing data providers to advertise the availability of their data and maintain complete control and ownership of that data. Mercury periodically (typically daily)harvests metadata sources through a collection of interfaces and re-indexes these metadata to provide extremely rapid search capabilities, even over collections with tens of millions of metadata records. A number of both graphical and application interfaces have been constructed within Mercury, to enable both human users and other computer programs to perform queries. Mercury was also designed to support multiple different projects, so that the particular fields that can be queried and used with search filters are easy to configure for each different project.

  16. Mercury Toolset for Spatiotemporal Metadata

    NASA Technical Reports Server (NTRS)

    Wilson, Bruce E.; Palanisamy, Giri; Devarakonda, Ranjeet; Rhyne, B. Timothy; Lindsley, Chris; Green, James

    2010-01-01

    Mercury (http://mercury.ornl.gov) is a set of tools for federated harvesting, searching, and retrieving metadata, particularly spatiotemporal metadata. Version 3.0 of the Mercury toolset provides orders of magnitude improvements in search speed, support for additional metadata formats, integration with Google Maps for spatial queries, facetted type search, support for RSS (Really Simple Syndication) delivery of search results, and enhanced customization to meet the needs of the multiple projects that use Mercury. It provides a single portal to very quickly search for data and information contained in disparate data management systems, each of which may use different metadata formats. Mercury harvests metadata and key data from contributing project servers distributed around the world and builds a centralized index. The search interfaces then allow the users to perform a variety of fielded, spatial, and temporal searches across these metadata sources. This centralized repository of metadata with distributed data sources provides extremely fast search results to the user, while allowing data providers to advertise the availability of their data and maintain complete control and ownership of that data. Mercury periodically (typically daily) harvests metadata sources through a collection of interfaces and re-indexes these metadata to provide extremely rapid search capabilities, even over collections with tens of millions of metadata records. A number of both graphical and application interfaces have been constructed within Mercury, to enable both human users and other computer programs to perform queries. Mercury was also designed to support multiple different projects, so that the particular fields that can be queried and used with search filters are easy to configure for each different project.

  17. Spatio-temporal Dynamics of Audiovisual Speech Processing

    PubMed Central

    Bernstein, Lynne E.; Auer, Edward T.; Wagner, Michael; Ponton, Curtis W.

    2007-01-01

    The cortical processing of auditory-alone, visual-alone, and audiovisual speech information is temporally and spatially distributed, and functional magnetic resonance imaging (fMRI) cannot adequately resolve its temporal dynamics. In order to investigate a hypothesized spatio-temporal organization for audiovisual speech processing circuits, event-related potentials (ERPs) were recorded using electroencephalography (EEG). Stimuli were congruent audiovisual /b?/, incongruent auditory /b?/ synchronized with visual /g?/, auditory-only /b?/, and visual-only /b?/ and /g?/. Current density reconstructions (CDRs) of the ERP data were computed across the latency interval of 50-250 milliseconds. The CDRs demonstrated complex spatio-temporal activation patterns that differed across stimulus conditions. The hypothesized circuit that was investigated here comprised initial integration of audiovisual speech by the middle superior temporal sulcus (STS), followed by recruitment of the intraparietal sulcus (IPS), followed by activation of Broca's area (Miller and d'Esposito, 2005). The importance of spatio-temporally sensitive measures in evaluating processing pathways was demonstrated. Results showed, strikingly, early (< 100 msec) and simultaneous activations in areas of the supramarginal and angular gyrus (SMG/AG), the IPS, the inferior frontal gyrus, and the dorsolateral prefrontal cortex. Also, emergent left hemisphere SMG/AG activation, not predicted based on the unisensory stimulus conditions was observed at approximately 160 to 220 msec. The STS was neither the earliest nor most prominent activation site, although it is frequently considered the sine qua non of audiovisual speech integration. As discussed here, the relatively late activity of the SMG/AG solely under audiovisual conditions is a possible candidate audiovisual speech integration response. PMID:17920933

  18. Host-Mycobacterium avium subsp. paratuberculosis interactome reveals a novel iron assimilation mechanism linked to nitric oxide stress during early infection

    PubMed Central

    2013-01-01

    Background The initial interaction between host cell and pathogen sets the stage for the ensuing infection and ultimately determine the course of disease. However, there is limited knowledge of the transcripts utilized by host and pathogen and how they may impact one another during this critical step. The purpose of this study was to create a host-Mycobacterium avium subsp. paratuberculosis (MAP) interactome for early infection in an epithelium-macrophage co-culture system using RNA-seq. Results Establishment of the host-MAP interactome revealed a novel iron assimilation system for carboxymycobactin. Iron assimilation is linked to nitric oxide synthase-2 production by the host and subsequent nitric oxide buildup. Iron limitation as well as nitric oxide is a prompt for MAP to enter into an iron sequestration program. This new iron sequestration program provides an explanation for mycobactin independence in some MAP strains grown in vitro as well as during infection within the host cell. Utilization of such a pathway is likely to aid MAP establishment and long-term survival within the host. Conclusions The host-MAP interactome identified a number of metabolic, DNA repair and virulence genes worthy for consideration as novel drug targets as well as future pathogenesis studies. Reported interactome data may also be utilized to conduct focused, hypothesis-driven research. Co-culture of uninfected bovine epithelial cells (MAC-T) and primary bovine macrophages creates a tolerant genotype as demonstrated by downregulation of inflammatory pathways. This co-culture system may serve as a model to investigate other bovine enteric pathogens. PMID:24112552

  19. STAT: Spatio-Temporal Analytics Toolkit

    NASA Astrophysics Data System (ADS)

    Liu, Xuan; Xing, Songhua; Uppala, Murali; Hampapur, Arun

    2011-06-01

    Most of the defense and security applications involve various types of spatial temporal data coming from multiple data source layers. How to analyze the large amount of cross layer geospatial temporal data to get actionable insights is an increasingly important challenge to these applications. There are a lot of research work in the area of spatial data model and management, spatial query and spatial data mining. However, applying these technologies to create a cross cutting analytics solutions is very time consuming and challenging. There is lack of framework and mechanism to plug in reusable spatio-temporal analytics assets. In this paper, we discuss a spatio-temporal analytics toolkit that provides a common underlying information fusion infrastructure, and a plug-in mechanism to support reusable cross domain spatiotemporal analytics.

  20. 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. PMID:22465599

  1. Evolutionary diversification of the BetaM interactome acquired through co-option of the ATP1B4 gene in placental mammals

    PubMed Central

    Korneenko, Tatyana V.; Pestov, Nikolay B.; Ahmad, Nisar; Okkelman, Irina A.; Dmitriev, Ruslan I.; Shakhparonov, Mikhail I.; Modyanov, Nikolai N.

    2016-01-01

    ATP1B4 genes represent a rare instance of orthologous vertebrate gene co-option that radically changed properties of the encoded BetaM proteins, which function as Na,K-ATPase subunits in lower vertebrates and birds. Eutherian BetaM has lost its ancestral function and became a muscle-specific resident of the inner nuclear membrane. Our earlier work implicated BetaM in regulation of gene expression through direct interaction with the transcriptional co-regulator SKIP. To gain insight into evolution of BetaM interactome we performed expanded screening of eutherian and avian cDNA libraries using yeast-two-hybrid and split-ubiquitin systems. The inventory of identified BetaM interactors includes lamina-associated protein LAP-1, myocyte nuclear envelope protein Syne1, BetaM itself, heme oxidases HMOX1 and HMOX2; transcription factor LZIP/CREB3, ERGIC3, PHF3, reticulocalbin-3, and β-sarcoglycan. No new interactions were found for chicken BetaM and human Na,K-ATPase β1, β2 and β3 isoforms, indicating the uniqueness of eutherian BetaM interactome. Analysis of truncated forms of BetaM indicates that residues 72-98 adjacent to the membrane in nucleoplasmic domain are important for the interaction with SKIP. These findings demonstrate that evolutionary alterations in structural and functional properties of eutherian BetaM proteins are associated with the increase in its interactome complexity. PMID:26939788

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

    PubMed Central

    Simões, Joana; Amado, Francisco M.

    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. PMID:26097882

  3. Evolutionary diversification of the BetaM interactome acquired through co-option of the ATP1B4 gene in placental mammals.

    PubMed

    Korneenko, Tatyana V; Pestov, Nikolay B; Ahmad, Nisar; Okkelman, Irina A; Dmitriev, Ruslan I; Shakhparonov, Mikhail I; Modyanov, Nikolai N

    2016-01-01

    ATP1B4 genes represent a rare instance of orthologous vertebrate gene co-option that radically changed properties of the encoded BetaM proteins, which function as Na,K-ATPase subunits in lower vertebrates and birds. Eutherian BetaM has lost its ancestral function and became a muscle-specific resident of the inner nuclear membrane. Our earlier work implicated BetaM in regulation of gene expression through direct interaction with the transcriptional co-regulator SKIP. To gain insight into evolution of BetaM interactome we performed expanded screening of eutherian and avian cDNA libraries using yeast-two-hybrid and split-ubiquitin systems. The inventory of identified BetaM interactors includes lamina-associated protein LAP-1, myocyte nuclear envelope protein Syne1, BetaM itself, heme oxidases HMOX1 and HMOX2; transcription factor LZIP/CREB3, ERGIC3, PHF3, reticulocalbin-3, and β-sarcoglycan. No new interactions were found for chicken BetaM and human Na,K-ATPase β1, β2 and β3 isoforms, indicating the uniqueness of eutherian BetaM interactome. Analysis of truncated forms of BetaM indicates that residues 72-98 adjacent to the membrane in nucleoplasmic domain are important for the interaction with SKIP. These findings demonstrate that evolutionary alterations in structural and functional properties of eutherian BetaM proteins are associated with the increase in its interactome complexity. PMID:26939788

  4. Spatiotemporal resource distribution and foraging strategies of ants (Hymenoptera: Formicidae)

    PubMed Central

    Lanan, Michele

    2014-01-01

    The distribution of food resources in space and time is likely to be an important factor governing the type of foraging strategy used by ants. However, no previous systematic attempt has been made to determine whether spatiotemporal resource distribution is in fact correlated with foraging strategy across the ants. In this analysis, I present data compiled from the literature on the foraging strategy and food resource use of 402 species of ants from across the phylogenetic tree. By categorizing the distribution of resources reported in these studies in terms of size relative to colony size, spatial distribution relative to colony foraging range, frequency of occurrence in time relative to worker life span, and depletability (i.e., whether the colony can cause a change in resource frequency), I demonstrate that different foraging strategies are indeed associated with specific spatiotemporal resource attributes. The general patterns I describe here can therefore be used as a framework to inform predictions in future studies of ant foraging behavior. No differences were found between resources collected via short-term recruitment strategies (group recruitment, short-term trails, and volatile recruitment), whereas different resource distributions were associated with solitary foraging, trunk trails, long-term trail networks, group raiding, and raiding. In many cases, ant species use a combination of different foraging strategies to collect diverse resources. It is useful to consider these foraging strategies not as separate options but as modular parts of the total foraging effort of a colony. PMID:25525497

  5. Spatio-temporal statistical models with applications to atmospheric processes

    SciTech Connect

    Wikle, C.K.

    1996-12-31

    This doctoral dissertation is presented as three self-contained papers. An introductory chapter considers traditional spatio-temporal statistical methods used in the atmospheric sciences from a statistical perspective. Although this section is primarily a review, many of the statistical issues considered have not been considered in the context of these methods and several open questions are posed. The first paper attempts to determine a means of characterizing the semiannual oscillation (SAO) spatial variation in the northern hemisphere extratropical height field. It was discovered that the midlatitude SAO in 500hPa geopotential height could be explained almost entirely as a result of spatial and temporal asymmetries in the annual variation of stationary eddies. It was concluded that the mechanism for the SAO in the northern hemisphere is a result of land-sea contrasts. The second paper examines the seasonal variability of mixed Rossby-gravity waves (MRGW) in lower stratospheric over the equatorial Pacific. Advanced cyclostationary time series techniques were used for analysis. It was found that there are significant twice-yearly peaks in MRGW activity. Analyses also suggested a convergence of horizontal momentum flux associated with these waves. In the third paper, a new spatio-temporal statistical model is proposed that attempts to consider the influence of both temporal and spatial variability. This method is mainly concerned with prediction in space and time, and provides a spatially descriptive and temporally dynamic model.

  6. A Spatio-temporal Model of African Animal Trypanosomosis Risk

    PubMed Central

    Dicko, Ahmadou H.; Percoma, Lassane; Sow, Adama; Adam, Yahaya; Mahama, Charles; Sidibé, Issa; Dayo, Guiguigbaza-Kossigan; Thévenon, Sophie; Fonta, William; Sanfo, Safietou; Djiteye, Aligui; Salou, Ernest; Djohan, Vincent; Cecchi, Giuliano; Bouyer, Jérémy

    2015-01-01

    Background African animal trypanosomosis (AAT) is a major constraint to sustainable development of cattle farming in sub-Saharan Africa. The habitat of the tsetse fly vector is increasingly fragmented owing to demographic pressure and shifts in climate, which leads to heterogeneous risk of cyclical transmission both in space and time. In Burkina Faso and Ghana, the most important vectors are riverine species, namely Glossina palpalis gambiensis and G. tachinoides, which are more resilient to human-induced changes than the savannah and forest species. Although many authors studied the distribution of AAT risk both in space and time, spatio-temporal models allowing predictions of it are lacking. Methodology/Principal Findings We used datasets generated by various projects, including two baseline surveys conducted in Burkina Faso and Ghana within PATTEC (Pan African Tsetse and Trypanosomosis Eradication Campaign) national initiatives. We computed the entomological inoculation rate (EIR) or tsetse challenge using a range of environmental data. The tsetse apparent density and their infection rate were separately estimated and subsequently combined to derive the EIR using a “one layer-one model” approach. The estimated EIR was then projected into suitable habitat. This risk index was finally validated against data on bovine trypanosomosis. It allowed a good prediction of the parasitological status (r2 = 67%), showed a positive correlation but less predictive power with serological status (r2 = 22%) aggregated at the village level but was not related to the illness status (r2 = 2%). Conclusions/Significance The presented spatio-temporal model provides a fine-scale picture of the dynamics of AAT risk in sub-humid areas of West Africa. The estimated EIR was high in the proximity of rivers during the dry season and more widespread during the rainy season. The present analysis is a first step in a broader framework for an efficient risk management of climate-sensitive vector-borne diseases. PMID:26154506

  7. Annotating spatio-temporal datasets for meaningful analysis in the Web

    NASA Astrophysics Data System (ADS)

    Stasch, Christoph; Pebesma, Edzer; Scheider, Simon

    2014-05-01

    More and more environmental datasets that vary in space and time are available in the Web. This comes along with an advantage of using the data for other purposes than originally foreseen, but also with the danger that users may apply inappropriate analysis procedures due to lack of important assumptions made during the data collection process. In order to guide towards a meaningful (statistical) analysis of spatio-temporal datasets available in the Web, we have developed a Higher-Order-Logic formalism that captures some relevant assumptions in our previous work [1]. It allows to proof on meaningful spatial prediction and aggregation in a semi-automated fashion. In this poster presentation, we will present a concept for annotating spatio-temporal datasets available in the Web with concepts defined in our formalism. Therefore, we have defined a subset of the formalism as a Web Ontology Language (OWL) pattern. It allows capturing the distinction between the different spatio-temporal variable types, i.e. point patterns, fields, lattices and trajectories, that in turn determine whether a particular dataset can be interpolated or aggregated in a meaningful way using a certain procedure. The actual annotations that link spatio-temporal datasets with the concepts in the ontology pattern are provided as Linked Data. In order to allow data producers to add the annotations to their datasets, we have implemented a Web portal that uses a triple store at the backend to store the annotations and to make them available in the Linked Data cloud. Furthermore, we have implemented functions in the statistical environment R to retrieve the RDF annotations and, based on these annotations, to support a stronger typing of spatio-temporal datatypes guiding towards a meaningful analysis in R. [1] Stasch, C., Scheider, S., Pebesma, E., Kuhn, W. (2014): "Meaningful spatial prediction and aggregation", Environmental Modelling & Software, 51, 149-165.

  8. Proximity biotinylation and affinity purification are complementary approaches for the interactome mapping of chromatin-associated protein complexes

    PubMed Central

    Lambert, Jean-Philippe; Tucholska, Monika; Go, Christopher; Knight, James D.R.; Gingras, Anne-Claude

    2014-01-01

    Mapping protein-protein interactions for chromatin-associated proteins remains challenging. Here we explore the use of BioID, a proximity biotinylation approach in which a mutated biotin ligase (BirA*) is fused to a bait of interest, allowing for the local activation of biotin and subsequent biotinylation of proteins in the bait vicinity. BioID allowed for successful interactome mapping of core histones and members of the mediator complex. We explored the background signal produced by the BioID approach and found that using distinct types of controls increased the stringency of our statistical analysis with SAINTexpress. A direct comparison of BioID with our AP-MS protocol optimized for chromatin-associated protein complexes revealed that the approaches identified few shared interaction partners and enriched for distinct biological processes; yet, both approaches permitted the recovery of biologically meaningful interactions. While no clear bias could be observed for either technique toward protein complexes of particular functions, BioID allowed for the purification of proteins of lower cellular abundance. Finally, we were able to identify a strong association of MED4 with the centrosome by BioID and validated this finding by immunofluorescence. In summary, BioID complements AP-MS for the study of chromatin-associated protein complexes. PMID:25281560

  9. A non-synonymous single-nucleotide polymorphism associated with multiple sclerosis risk affects the EVI5 interactome.

    PubMed

    Didonna, Alessandro; Isobe, Noriko; Caillier, Stacy J; Li, Kathy H; Burlingame, Alma L; Hauser, Stephen L; Baranzini, Sergio E; Patsopoulos, Nikolaos A; Oksenberg, Jorge R

    2015-12-15

    Despite recent progress in the characterization of genetic loci associated with multiple sclerosis (MS) risk, the ubiquitous linkage disequilibrium operating across the genome has stalled efforts to distinguish causative variants from proxy single-nucleotide polymorphisms (SNPs). Here, we have identified through fine mapping and meta-analysis EVI5 as the most plausible disease risk gene within the 1p22.1 locus. We further show that an exonic SNP associated with risk induces changes in superficial hydrophobicity patterns of the coiled-coil domain of EVI5, which, in turns, affects the EVI5 interactome. Immunoprecipitation of wild-type and mutated EVI5 followed by mass spectrometry generated a roster of disease-specific interactors functionally linked to lipid metabolism. Among the exclusive binding partners of the risk variant, we describe the novel interaction with sphingosine 1-phosphate lyase (SGPL1)-a key enzyme for the creation of the sphingosine-1 phosphate gradient, which is relevant to the pathogenic process and therapeutic management of MS. PMID:26433934

  10. A disease module in the interactome explains disease heterogeneity, drug response and captures novel pathways and genes in asthma.

    PubMed

    Sharma, Amitabh; Menche, Jörg; Huang, C Chris; Ort, Tatiana; Zhou, Xiaobo; Kitsak, Maksim; Sahni, Nidhi; Thibault, Derek; Voung, Linh; Guo, Feng; Ghiassian, Susan Dina; Gulbahce, Natali; Baribaud, Frédéric; Tocker, Joel; Dobrin, Radu; Barnathan, Elliot; Liu, Hao; Panettieri, Reynold A; Tantisira, Kelan G; Qiu, Weiliang; Raby, Benjamin A; Silverman, Edwin K; Vidal, Marc; Weiss, Scott T; Barabási, Albert-László

    2015-06-01

    Recent advances in genetics have spurred rapid progress towards the systematic identification of genes involved in complex diseases. Still, the detailed understanding of the molecular and physiological mechanisms through which these genes affect disease phenotypes remains a major challenge. Here, we identify the asthma disease module, i.e. the local neighborhood of the interactome whose perturbation is associated with asthma, and validate it for functional and pathophysiological relevance, using both computational and experimental approaches. We find that the asthma disease module is enriched with modest GWAS P-values against the background of random variation, and with differentially expressed genes from normal and asthmatic fibroblast cells treated with an asthma-specific drug. The asthma module also contains immune response mechanisms that are shared with other immune-related disease modules. Further, using diverse omics (genomics, gene-expression, drug response) data, we identify the GAB1 signaling pathway as an important novel modulator in asthma. The wiring diagram of the uncovered asthma module suggests a relatively close link between GAB1 and glucocorticoids (GCs), which we experimentally validate, observing an increase in the level of GAB1 after GC treatment in BEAS-2B bronchial epithelial cells. The siRNA knockdown of GAB1 in the BEAS-2B cell line resulted in a decrease in the NFkB level, suggesting a novel regulatory path of the pro-inflammatory factor NFkB by GAB1 in asthma. PMID:25586491

  11. Interactome analysis of gene expression profile reveals potential novel key transcriptional regulators of skin pathology in vitiligo.

    PubMed

    Dey-Rao, R; Sinha, A A

    2016-01-01

    Selective destruction of epidermal melanocytes is central to vitiligo (VL), a common acquired, autoimmune depigmentory disorder of the skin. Like other autoimmune diseases, the pathogenesis of VL is obscure and both multifactorial and polygenic. The prevailing theory is that VL may be part of an autoimmune diathesis. To evaluate mechanisms underlying disease development and progression, we studied genome-wide gene expression from lesional and non-lesional skin of patients with non-segmental VL. Unbiased clustering and principal components analyses reveals a 'lesional pathology'-based signature. Pathway-based analyses of the differentially expressed genes underscore processes such as melanocyte development and cell cycle as central drivers of the disease state. Interactome analysis identifies several key transcriptional regulators potentially affecting disease pathogenesis both within and 'hidden' from the data set. Finally, two genes within six identified transcriptional 'hot spots' coincide with previous VL-associated genetic elements. The remaining genes in the 'hot spots' offer an additional set of potential disease-linked loci that may help to guide future studies aimed at identifying disease risk genes. PMID:26562080

  12. Topological characteristics of target genes regulated by abiotic-stress-responsible miRNAs in a rice interactome network.

    PubMed

    Zhang, Linzhong; Xuan, Hongdong; Zuo, Yongchun; Xu, Gaojian; Wang, Ping; Song, Youhong; Zhang, Shihua

    2016-05-01

    A great number of microRNAs (miRNAs) have been identified in responding and acting in gene regulatory networks associated with plant tolerance to abiotic stress conditions, such as drought, salinity, and high temperature. The topological exploration of target genes regulated by abiotic-stress-responsible miRNAs (ASRmiRs) in a network facilitates to discover the molecular basis of plant abiotic stress response. This study was based on the staple food rice (Oryza sativa) in which ASRmiRs were manually curated. After having compared the topological properties of target genes (stress-miR-targets) with those (non-stress-miR-targets) not regulated by ASRmiRs in a rice interactome network, we found that stress-miR-targets exhibited distinguishable topological properties. The interaction probability analysis and k-core decomposition showed that stress-miR-targets preferentially interacted with non-stress-miR-targets and located at the peripheral positions in the network. Our results indicated an obvious topological distinction between the two types of genes, reflecting the specific mechanisms of action of stress-miR-targets in rice abiotic stress response. Also, the results may provide valuable clues to elucidate molecular mechanisms of crop response to abiotic stress. PMID:26830287

  13. Multi-scale perturbations of protein interactomes reveal their mechanisms of regulation, robustness and insights into genotype-phenotype maps.

    PubMed

    Filteau, Marie; Vignaud, Hélène; Rochette, Samuel; Diss, Guillaume; Chrétien, Andrée-Ève; Berger, Caroline M; Landry, Christian R

    2016-03-01

    Cellular architectures and signaling machineries are organized through protein-protein interactions (PPIs). High-throughput methods to study PPIs in yeast have opened a new perspective on the organization of the cell by allowing the study of whole protein interactomes. Recent investigations have moved from the description of this organization to the analysis of its dynamics by experimenting how protein interaction networks (PINs) are rewired in response to perturbations. Here we review studies that have used the budding yeast as an experimental system to explore these altered networks. Given the large space of possible PPIs and the diversity of potential genetic and environmental perturbations, high-throughput methods are an essential requirement to survey PIN perturbations on a large scale. Network perturbations are typically conceptualized as the removal of entire proteins (nodes), the modification of single PPIs (edges) or changes in growth conditions. These studies have revealed mechanisms of PPI regulation, PIN architectural organization, robustness and sensitivity to perturbations. Despite these major advances, there are still inherent limits to current technologies that lead to a trade-off between the number of perturbations and the number of PPIs that can be considered simultaneously. Nevertheless, as we exemplify here, targeted approaches combined with the existing resources remain extremely powerful to explore the inner organization of cells and their responses to perturbations. PMID:26476431

  14. Affinity purification-mass spectrometry analysis of bcl-2 interactome identified SLIRP as a novel interacting protein.

    PubMed

    Trisciuoglio, D; Desideri, M; Farini, V; De Luca, T; Di Martile, M; Tupone, M G; Urbani, A; D'Aguanno, S; Del Bufalo, D

    2016-01-01

    Members of the bcl-2 protein family share regions of sequence similarity, the bcl-2 homology (BH) domains. Bcl-2, the most studied member of this family, has four BH domains, BH1-4, and has a critical role in resistance to antineoplastic drugs by regulating the mitochondrial apoptotic pathway. Moreover, it is also involved in other relevant cellular processes such as tumor progression, angiogenesis and autophagy. Deciphering the network of bcl-2-interacting factors should provide a critical advance in understanding the different functions of bcl-2. Here, we characterized bcl-2 interactome by mass spectrometry in human lung adenocarcinoma cells. In silico functional analysis associated most part of the identified proteins to mitochondrial functions. Among them we identified SRA stem-loop interacting RNA-binding protein, SLIRP, a mitochondrial protein with a relevant role in regulating mitochondrial messenger RNA (mRNA) homeostasis. We validated bcl-2/SLIRP interaction by immunoprecipitation and immunofluorescence experiments in cancer cell lines from different histotypes. We showed that, although SLIRP is not involved in mediating bcl-2 ability to protect from apoptosis and oxidative damage, bcl-2 binds and stabilizes SLIRP protein and regulates mitochondrial mRNA levels. Moreover, we demonstrated that the BH4 domain of bcl-2 has a role in maintaining this binding. PMID:26866271

  15. Proteome Based Construction of the Lymphocyte Function-Associated Antigen 1 (LFA-1) Interactome in Human Dendritic Cells

    PubMed Central

    Eich, Christina; Lasonder, Edwin; Cruz, Luis J.; Reinieren-Beeren, Inge; Cambi, Alessandra; Figdor, Carl G.; Buschow, Sonja I.

    2016-01-01

    The β2-integrin lymphocyte function-associated antigen 1 (LFA-1) plays an important role in the migration, adhesion and intercellular communication of dendritic cells (DCs). During the differentiation of human DCs from monocyte precursors, LFA-1 ligand binding capacity is completely lost, even though its expression levels were remained constant. Yet LFA-1-mediated adhesive capacity on DCs can be regained by exposing DCs to the chemokine CCL21, suggesting a high degree of regulation of LFA-1 activity during the course of DC differentiation. The molecular mechanisms underlying this regulation of LFA-1 function in DCs, however, remain elusive. To get more insight we attempted to identify specific LFA-1 binding partners that may play a role in regulating LFA-1 activity in DCs. We used highly sensitive label free quantitative mass-spectrometry to identify proteins co-immunoprecipitated (co-IP) with LFA-1 from ex vivo generated DCs. Among the potential binding partners we identified not only established components of integrin signalling pathways and cytoskeletal proteins, but also several novel LFA-1 binding partners including CD13, galectin-3, thrombospondin-1 and CD44. Further comparison to the LFA-1 interaction partners in monocytes indicated that DC differentiation was accompanied by an overall increase in LFA-1 associated proteins, in particular cytoskeletal, signalling and plasma membrane (PM) proteins. The here presented LFA-1 interactome composed of 78 proteins thus represents a valuable resource of potential regulators of LFA-1 function during the DC lifecycle. PMID:26889827

  16. Proteome Based Construction of the Lymphocyte Function-Associated Antigen 1 (LFA-1) Interactome in Human Dendritic Cells.

    PubMed

    Eich, Christina; Lasonder, Edwin; Cruz, Luis J; Reinieren-Beeren, Inge; Cambi, Alessandra; Figdor, Carl G; Buschow, Sonja I

    2016-01-01

    The β2-integrin lymphocyte function-associated antigen 1 (LFA-1) plays an important role in the migration, adhesion and intercellular communication of dendritic cells (DCs). During the differentiation of human DCs from monocyte precursors, LFA-1 ligand binding capacity is completely lost, even though its expression levels were remained constant. Yet LFA-1-mediated adhesive capacity on DCs can be regained by exposing DCs to the chemokine CCL21, suggesting a high degree of regulation of LFA-1 activity during the course of DC differentiation. The molecular mechanisms underlying this regulation of LFA-1 function in DCs, however, remain elusive. To get more insight we attempted to identify specific LFA-1 binding partners that may play a role in regulating LFA-1 activity in DCs. We used highly sensitive label free quantitative mass-spectrometry to identify proteins co-immunoprecipitated (co-IP) with LFA-1 from ex vivo generated DCs. Among the potential binding partners we identified not only established components of integrin signalling pathways and cytoskeletal proteins, but also several novel LFA-1 binding partners including CD13, galectin-3, thrombospondin-1 and CD44. Further comparison to the LFA-1 interaction partners in monocytes indicated that DC differentiation was accompanied by an overall increase in LFA-1 associated proteins, in particular cytoskeletal, signalling and plasma membrane (PM) proteins. The here presented LFA-1 interactome composed of 78 proteins thus represents a valuable resource of potential regulators of LFA-1 function during the DC lifecycle. PMID:26889827

  17. Rapid analyses of proteomes and interactomes using an integrated solid-phase extraction-liquid chromatography-MS/MS system.

    PubMed

    Binai, Nadine A; Marino, Fabio; Soendergaard, Peter; Bache, Nicolai; Mohammed, Shabaz; Heck, Albert J R

    2015-02-01

    Here, we explore applications of a LC system using disposable solid-phase extraction (SPE) cartridges and very short LC-MS/MS gradients that allows for rapid analyses in less than 10 min analysis time. The setup consists of an autosampler harboring two sets of 96 STAGE tips that function as precolumns and a short RP analytical column running 6.5 min gradients. This system combines efficiently with several proteomics workflows such as offline prefractionation methods, including 1D gel electrophoresis and strong-cation exchange chromatography. It also enables the analysis of interactomes obtained by affinity purification with an analysis time of approximately 1 h. In a typical shotgun proteomics experiment involving 36 SCX fractions of an AspN digested cell lysate, we detected over 3600 protein groups with an analysis time of less than 5.5 h. This innovative fast LC system reduces proteome analysis time while maintaining sufficient proteomic detail. This has particular relevance for the use of proteomics within a clinical environment, where large sample numbers and fast turnover times are essential. PMID:25485597

  18. AF4 and AF4N protein complexes: recruitment of P-TEFb kinase, their interactome and potential functions

    PubMed Central

    Scholz, Bastian; Kowarz, Eric; Rssler, Tanja; Ahmad, Khalil; Steinhilber, Dieter; Marschalek, Rolf

    2015-01-01

    AF4/AFF1 and AF5/AFF4 are the molecular backbone to assemble super-elongation complexes (SECs) that have two main functions: (1) control of transcriptional elongation by recruiting the positive transcription elongation factor b (P-TEFb = CyclinT1/CDK9) that is usually stored in inhibitory 7SK RNPs; (2) binding of different histone methyltransferases, like DOT1L, NSD1 and CARM1. This way, transcribed genes obtain specific histone signatures (e.g. H3K79me2/3, H3K36me2) to generate a transcriptional memory system. Here we addressed several questions: how is P-TEFb recruited into SEC, how is the AF4 interactome composed, and what is the function of the naturally occuring AF4N protein variant which exhibits only the first 360 amino acids of the AF4 full-length protein. Noteworthy, shorter protein variants are a specific feature of all AFF protein family members. Here, we demonstrate that full-length AF4 and AF4N are both catalyzing the transition of P-TEFb from 7SK RNP to their N-terminal domain. We have also mapped the protein-protein interaction network within both complexes. In addition, we have first evidence that the AF4N protein also recruits TFIIH and the tumor suppressor MEN1. This indicate that AF4N may have additional functions in transcriptional initiation and in MEN1-dependend transcriptional processes. PMID:26171280

  19. The interactome of Streptococcus pneumoniae and its bacteriophages show highly specific patterns of interactions among bacteria and their phages

    PubMed Central

    Mariano, Rachelle; Wuchty, Stefan; Vizoso-Pinto, Maria G.; Häuser, Roman; Uetz, Peter

    2016-01-01

    Although an abundance of bacteriophages exists, little is known about interactions between their proteins and those of their bacterial hosts. Here, we experimentally determined the phage-host interactomes of the phages Dp-1 and Cp-1 and their underlying protein interaction network in the host Streptococcus pneumoniae. We compared our results to the interaction patterns of E. coli phages lambda and T7. Dp-1 and Cp-1 target highly connected host proteins, occupy central network positions, and reach many protein clusters through the interactions of their targets. In turn, lambda and T7 targets cluster to conserved and essential proteins in E. coli, while such patterns were largely absent in S. pneumoniae. Furthermore, targets in E. coli were mutually strongly intertwined, while targets of Dp-1 and Cp-1 were strongly connected through essential and orthologous proteins in their immediate network vicinity. In both phage-host systems, the impact of phages on their protein targets appears to extend from their network neighbors, since proteins that interact with phage targets were located in central network positions, have a strong topologically disruptive effect and touch complexes with high functional heterogeneity. Such observations suggest that the phages, biological impact is accomplished through a surprisingly limited topological reach of their targets. PMID:27103053

  20. Interactome analysis identifies a new paralogue of XRCC4 in non-homologous end joining DNA repair pathway

    PubMed Central

    Xing, Mengtan; Yang, Mingrui; Huo, Wei; Feng, Feng; Wei, Leizhen; Jiang, Wenxia; Ning, Shaokai; Yan, Zhenxin; Li, Wen; Wang, Qingsong; Hou, Mei; Dong, Chunxia; Guo, Rong; Gao, Ge; Ji, Jianguo; Zha, Shan; Lan, Li; Liang, Huanhuan; Xu, Dongyi

    2015-01-01

    Non-homologous end joining (NHEJ) is a major pathway to repair DNA double-strand breaks (DSBs), which can display different types of broken ends. However, it is unclear how NHEJ factors organize to repair diverse types of DNA breaks. Here, through systematic analysis of the human NHEJ factor interactome, we identify PAXX as a direct interactor of Ku. The crystal structure of PAXX is similar to those of XRCC4 and XLF. Importantly, PAXX-deficient cells are sensitive to DSB-causing agents. Moreover, epistasis analysis demonstrates that PAXX functions together with XLF in response to ionizing radiation-induced complex DSBs, whereas they function redundantly in response to Topo2 inhibitor-induced simple DSBs. Consistently, PAXX and XLF coordinately promote the ligation of complex but not simple DNA ends in vitro. Altogether, our data identify PAXX as a new NHEJ factor and provide insight regarding the organization of NHEJ factors responding to diverse types of DSB ends. PMID:25670504

  1. In Vivo Mapping of Eukaryotic RNA Interactomes Reveals Principles of Higher-Order Organization and Regulation.

    PubMed

    Aw, Jong Ghut Ashley; Shen, Yang; Wilm, Andreas; Sun, Miao; Lim, Xin Ni; Boon, Kum-Loong; Tapsin, Sidika; Chan, Yun-Shen; Tan, Cheng-Peow; Sim, Adelene Y L; Zhang, Tong; Susanto, Teodorus Theo; Fu, Zhiyan; Nagarajan, Niranjan; Wan, Yue

    2016-05-19

    Identifying pairwise RNA-RNA interactions is key to understanding how RNAs fold and interact with other RNAs inside the cell. We present a high-throughput approach, sequencing of psoralen crosslinked, ligated, and selected hybrids (SPLASH), that maps pairwise RNA interactions in vivo with high sensitivity and specificity, genome-wide. Applying SPLASH to human and yeast transcriptomes revealed the diversity and dynamics of thousands of long-range intra- and intermolecular RNA-RNA interactions. Our analysis highlighted key structural features of RNA classes, including the modular organization of mRNAs, its impact on translation and decay, and the enrichment of long-range interactions in noncoding RNAs. Additionally, intermolecular mRNA interactions were organized into network clusters and were remodeled during cellular differentiation. We also identified hundreds of known and new snoRNA-rRNA binding sites, expanding our knowledge of rRNA biogenesis. These results highlight the underexplored complexity of RNA interactomes and pave the way to better understanding how RNA organization impacts biology. PMID:27184079

  2. The interactome of Streptococcus pneumoniae and its bacteriophages show highly specific patterns of interactions among bacteria and their phages.

    PubMed

    Mariano, Rachelle; Wuchty, Stefan; Vizoso-Pinto, Maria G; Häuser, Roman; Uetz, Peter

    2016-01-01

    Although an abundance of bacteriophages exists, little is known about interactions between their proteins and those of their bacterial hosts. Here, we experimentally determined the phage-host interactomes of the phages Dp-1 and Cp-1 and their underlying protein interaction network in the host Streptococcus pneumoniae. We compared our results to the interaction patterns of E. coli phages lambda and T7. Dp-1 and Cp-1 target highly connected host proteins, occupy central network positions, and reach many protein clusters through the interactions of their targets. In turn, lambda and T7 targets cluster to conserved and essential proteins in E. coli, while such patterns were largely absent in S. pneumoniae. Furthermore, targets in E. coli were mutually strongly intertwined, while targets of Dp-1 and Cp-1 were strongly connected through essential and orthologous proteins in their immediate network vicinity. In both phage-host systems, the impact of phages on their protein targets appears to extend from their network neighbors, since proteins that interact with phage targets were located in central network positions, have a strong topologically disruptive effect and touch complexes with high functional heterogeneity. Such observations suggest that the phages, biological impact is accomplished through a surprisingly limited topological reach of their targets. PMID:27103053

  3. “Stop Ne(c)king around”: How interactomics contributes to functionally characterize Nek family kinases

    PubMed Central

    Meirelles, Gabriela Vaz; Perez, Arina Marina; de Souza, Edmárcia Elisa; Basei, Fernanda Luisa; Papa, Priscila Ferreira; Melo Hanchuk, Talita Diniz; Cardoso, Vanessa Bomfim; Kobarg, Jörg

    2014-01-01

    Aside from Polo and Aurora, a third but less studied kinase family involved in mitosis regulation is the never in mitosis-gene A (NIMA)-related kinases (Neks). The founding member of this family is the sole member NIMA of Aspergillus nidulans, which is crucial for the initiation of mitosis in that organism. All 11 human Neks have been functionally assigned to one of the three core functions established for this family in mammals: (1) centrioles/mitosis; (2) primary ciliary function/ciliopathies; and (3) DNA damage response (DDR). Recent findings, especially on Nek 1 and 8, showed however, that several Neks participate in parallel in at least two of these contexts: primary ciliary function and DDR. In the core section of this in-depth review, we report the current detailed functional knowledge on each of the 11 Neks. In the discussion, we return to the cross-connections among Neks and point out how our and other groups’ functional and interactomics studies revealed that most Neks interact with protein partners associated with two if not all three of the functional contexts. We then raise the hypothesis that Neks may be the connecting regulatory elements that allow the cell to fine tune and synchronize the cellular events associated with these three core functions. The new and exciting findings on the Nek family open new perspectives and should allow the Neks to finally claim the attention they deserve in the field of kinases and cell cycle biology. PMID:24921005

  4. Affinity purification-mass spectrometry analysis of bcl-2 interactome identified SLIRP as a novel interacting protein

    PubMed Central

    Trisciuoglio, D; Desideri, M; Farini, V; De Luca, T; Di Martile, M; Tupone, M G; Urbani, A; D'Aguanno, S; Del Bufalo, D

    2016-01-01

    Members of the bcl-2 protein family share regions of sequence similarity, the bcl-2 homology (BH) domains. Bcl-2, the most studied member of this family, has four BH domains, BH1–4, and has a critical role in resistance to antineoplastic drugs by regulating the mitochondrial apoptotic pathway. Moreover, it is also involved in other relevant cellular processes such as tumor progression, angiogenesis and autophagy. Deciphering the network of bcl-2-interacting factors should provide a critical advance in understanding the different functions of bcl-2. Here, we characterized bcl-2 interactome by mass spectrometry in human lung adenocarcinoma cells. In silico functional analysis associated most part of the identified proteins to mitochondrial functions. Among them we identified SRA stem–loop interacting RNA-binding protein, SLIRP, a mitochondrial protein with a relevant role in regulating mitochondrial messenger RNA (mRNA) homeostasis. We validated bcl-2/SLIRP interaction by immunoprecipitation and immunofluorescence experiments in cancer cell lines from different histotypes. We showed that, although SLIRP is not involved in mediating bcl-2 ability to protect from apoptosis and oxidative damage, bcl-2 binds and stabilizes SLIRP protein and regulates mitochondrial mRNA levels. Moreover, we demonstrated that the BH4 domain of bcl-2 has a role in maintaining this binding. PMID:26866271

  5. Spatiotemporal dynamics and optical vortices in a photorefractive phase-conjugate resonator

    NASA Technical Reports Server (NTRS)

    Liu, Siuying Raymond; Indebetouw, Guy

    1992-01-01

    A truncated modal expansion approach is used to study the spatiotemporal dynamics of a phase-conjugate resonator as a function of Bragg detuning. The numerical results reveal a rich variety of behaviors. Emphasis is given to the spatial distribution of optical vortices, their trajectories and their relationship to the beam's spatial coherence. The limitations of the model are discussed and experimental results are presented for comparison with the model's predictions and assessment of its soundness.

  6. Spatiotemporal Symmetry in Rings of Coupled Biological Oscillators of Physarum Plasmodial Slime Mold

    NASA Astrophysics Data System (ADS)

    Takamatsu, Atsuko; Tanaka, Reiko; Yamada, Hiroyasu; Nakagaki, Toshiyuki; Fujii, Teruo; Endo, Isao

    2001-08-01

    Spatiotemporal patterns in rings of coupled biological oscillators of the plasmodial slime mold, Physarum polycephalum, were investigated by comparing with results analyzed by the symmetric Hopf bifurcation theory based on group theory. In three-, four-, and five-oscillator systems, all types of oscillation modes predicted by the theory were observed including a novel oscillation mode, a half period oscillation, which has not been reported anywhere in practical systems. Our results support the effectiveness of the symmetric Hopf bifurcation theory in practical systems.

  7. Spatiotemporal Symmetry in Rings of Coupled Biological Oscillators of Physarum Plasmodial Slime Mold

    SciTech Connect

    Takamatsu, Atsuko; Tanaka, Reiko; Yamada, Hiroyasu; Nakagaki, Toshiyuki; Fujii, Teruo; Endo, Isao

    2001-08-13

    Spatiotemporal patterns in rings of coupled biological oscillators of the plasmodial slime mold, Physarum polycephalum, were investigated by comparing with results analyzed by the symmetric Hopf bifurcation theory based on group theory. In three-, four-, and five-oscillator systems, all types of oscillation modes predicted by the theory were observed including a novel oscillation mode, a half period oscillation, which has not been reported anywhere in practical systems. Our results support the effectiveness of the symmetric Hopf bifurcation theory in practical systems.

  8. Nonlinear Analysis of Spatiotemporal Heart Data

    NASA Astrophysics Data System (ADS)

    Simonotto, Jennifer; Spano, Mark; Ditto, William; Kavanagh, Katherine; Harrison, Robert G.

    2002-03-01

    Studying the nonlinear dynamics of ventricular fibrillation (VF) and ventricular tachycardia (VT) is necessary for the development of better models of and treatments for VF/VT. Through the use of voltage sensitive dyes and new high speed video cameras, we can now obtain optical mapping data that exhibit signal to noise ratios high enough to tackle (in 2D) the acquisition and analysis of spatiotemporal dynamics of VF/VT. It is now possible to effectively apply conventional statistical analyses (spatial correlation, coherence, signal decomposition), as well as techniques based upon wavefront motion (phase maps, propagation velocity vectors, waveform dynamics) of the electrical waves under study. Yet it is unclear if these measures alone will suffice to describe the complexity of the system. Thus we combine statistical and optical analysis with nonlinear analysis (entropy measures, symbolic dynamics, unstable periodic orbits (UPO) statistics) in order to extract the most information of the spatiotemporal behavior of VF/VT.

  9. What Is Spatio-Temporal Data Warehousing?

    NASA Astrophysics Data System (ADS)

    Vaisman, Alejandro; Zimányi, Esteban

    In the last years, extending OLAP (On-Line Analytical Processing) systems with spatial and temporal features has attracted the attention of the GIS (Geographic Information Systems) and database communities. However, there is no a commonly agreed definition of what is a spatio-temporal data warehouse and what functionality such a data warehouse should support. Further, the solutions proposed in the literature vary considerably in the kind of data that can be represented as well as the kind of queries that can be expressed. In this paper we present a conceptual framework for defining spatio-temporal data warehouses using an extensible data type system. We also define a taxonomy of different classes of queries of increasing expressive power, and show how to express such queries using an extension of the tuple relational calculus with aggregated functions.

  10. Communicating with optical spatio-temporal chaos

    NASA Astrophysics Data System (ADS)

    Garcia-Ojalvo, Jordi; Roy, Rajarshi

    2002-06-01

    Encoding information in temporal chaotic signals and decoding it via chaotic synchronization between transmitter and receiver constitute nowadays a well-established technique. The method has been successfully implemented in electronic and optical systems. The latter, besides offering high speed of information transfer, provide a natural way of spatiotemporal communication through the use of broad chaotic optical wavefronts. An optical setup for spatiotemporal chaotic communications was recently proposed based on nonlinear ring cavities. In this article, we examine further in detail such a proposal, comparing two different encoding methods, namely injection and modulation. In the two cases, the correlation between input, transmitted, and output signals is estimated by means of measures taken from information theory. The influence of the message amplitude and parameter mismatch is analyzed.

  11. Spatiotemporal resonances in a microfluidic system.

    PubMed

    Dodge, A; Hountondji, A; Jullien, M C; Tabeling, P

    2005-11-01

    We report on the experimental observation of a spatiotemporal resonance phenomenon, in which a temporal excitation locks with a spatial pattern in an open flow system. The observation is made in a microfluidic system. We obtain the expected regimes--mixing and resonant patterns--in qualitative agreement with the theory. As an application, we realized a dual system particle extraction-micromixer. PMID:16383750

  12. Controlling spatiotemporal chaos in coupled map lattices

    SciTech Connect

    Zhu, KaiEn; Chen, Tianlun

    2001-06-01

    A simple method is presented for controlling spatiotemporal chaos in coupled map lattices to a homogeneous state. This method can be applied to many kinds of models such as coupled map lattices (CML), one-way open CML (the open-flow model), and globally coupled map. We offer the stability analysis of the homogeneous state. Simple and sufficient conditions are obtained for controlling the above mentioned models. Our theoretical results agree well with numerical simulations.

  13. Spatiotemporal coupling in dispersive nonlinear planar waveguides

    NASA Astrophysics Data System (ADS)

    Ryan, Andrew T.; Agrawal, Govind P.

    1995-12-01

    The multidimensional nonlinear Schrodinger equation governs the spatial and temporal evolution of an optical field inside a nonlinear dispersive medium. Although spatial (diffractive) and temporal (dispersive) effects can be studied independently in a linear medium, they become mutually coupled in a nonlinear medium. We present the results of numerical simulations showing this spatiotemporal coupling for ultrashort pulses propagating in dispersive Kerr media. We investigate how spatiotemporal coupling affects the behavior of the optical field in each of the four regimes defined by the type of group-velocity dispersion (normal or anomalous) and the type of nonlinearity (focusing or defocusing). We show that dispersion, through spatiotemporal coupling, can either enhance or suppress self-focusing and self-defocusing. Similarly, we demonstrate that diffraction can either enhance or suppress pulse compression or broadening. We also discuss how these effects can be controlled with optical phase modulation, such as that provided by a lens (spatial phase modulation) or frequency chirping (temporal phase modulation). Copyright (c) 1995 Optical Society of America

  14. Spatiotemporal transcriptome of the human brain

    PubMed Central

    Kang, Hyo Jung; Kawasawa, Yuka Imamura; Cheng, Feng; Zhu, Ying; Xu, Xuming; Li, Mingfeng; Sousa, André M. M.; Pletikos, Mihovil; Meyer, Kyle A.; Sedmak, Goran; Guennel, Tobias; Shin, Yurae; Johnson, Matthew B.; Krsnik, Željka; Mayer, Simone; Fertuzinhos, Sofia; Umlauf, Sheila; Lisgo, Steven N.; Vortmeyer, Alexander; Weinberger, Daniel R.; Mane, Shrikant; Hyde, Thomas M.; Huttner, Anita; Reimers, Mark; Kleinman, Joel E.; Šestan, Nenad

    2012-01-01

    Summary Here we report the generation and analysis of genome-wide exon-level transcriptome data from 16 brain regions comprising the cerebellar cortex, mediodorsal nucleus of the thalamus, striatum, amygdala, hippocampus, and 11 areas of the neocortex. The dataset was generated from 1,340 tissue samples collected from one or both hemispheres of 57 postmortem human brains, spanning from embryonic development to late adulthood and representing males and females of multiple ethnicities. We also performed genotyping of 2.5 million SNPs and assessed copy number variations for all donors. Approximately 86% of protein-coding genes were found to be expressed using stringent criteria, and over 90% of these were differentially regulated at the whole transcript or exon level across regions and/or time. The majority of these spatiotemporal differences occurred before birth, followed by an increase in the similarity among regional transcriptomes during postnatal lifespan. Genes were organized into functionally distinct co-expression networks, and sex differences were present in gene expression and exon usage. Finally, we demonstrate how these results can be used to profile trajectories of genes associated with neurodevelopmental processes, cell types, neurotransmitter systems, autism, and schizophrenia, as well as to discover associations between SNPs and spatiotemporal gene expression. This study provides a comprehensive, publicly available dataset on the spatiotemporal human brain transcriptome and new insights into the transcriptional foundations of human neurodevelopment. PMID:22031440

  15. 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

  16. A Hierarchical Bayesian Approach for Learning Sparse Spatio-Temporal Decomposition of Multichannel EEG

    PubMed Central

    Wu, Wei; Chen, Zhe; Gao, Shangkai; Brown, Emery N.

    2011-01-01

    Multichannel electroencephalography (EEG) offers a non-invasive tool to explore spatio-temporal dynamics of brain activity. With EEG recordings consisting of multiple trials, traditional signal processing approaches that ignore inter-trial variability in the data may fail to accurately estimate the underlying spatio-temporal brain patterns. Moreover, precise characterization of such inter-trial variability per se can be of high scientific value in establishing the relationship between brain activity and behavior. In this paper, a statistical modeling framework is introduced for learning spatiotemporal decomposition of multiple-trial EEG data recorded under two contrasting experimental conditions. By modeling the variance of source signals as random variables varying across trials, the proposed two-stage hierarchical Bayesian model is able to capture inter-trial amplitude variability in the data in a sparse way where a parsimonious representation of the data can be obtained. A variational Bayesian (VB) algorithm is developed for statistical inference of the hierarchical model. The efficacy of the proposed modeling framework is validated with the analysis of both synthetic and real EEG data. In the simulation study we show that even at low signal-to-noise ratios our approach is able to recover with high precision the underlying spatiotemporal patterns and the evolution of source amplitude across trials; on two brain-computer interface (BCI) data sets we show that our VB algorithm can extract physiologically meaningful spatio-temporal patterns and make more accurate predictions than other two widely used algorithms: the common spatial patterns (CSP) algorithm and the Infomax algorithm for independent component analysis (ICA). The results demonstrate that our statistical modeling framework can serve as a powerful tool for extracting brain patterns, characterizing trial-to-trial brain dynamics, and decoding brain states by exploiting useful structures in the data. PMID:21420499

  17. Mining spatiotemporal co-occurrence patterns in solar datasets

    NASA Astrophysics Data System (ADS)

    Aydin, B.; Kempton, D.; Akkineni, V.; Angryk, R.; Pillai, K. G.

    2015-11-01

    We address the problem of mining spatiotemporal co-occurrence patterns (STCOPs) in solar datasets with extended polygon-based geometric representations. Specifically designed spatiotemporal indexing techniques are used in the mining of STCOPs. These include versions of two well-known spatiotemporal trajectory indexing techniques: the scalable and efficient trajectory index and Chebyshev polynomial indexing. We present a framework, STCOP-MINER, implementing a filter-and-refine STCOP mining algorithm, with the indexing techniques mentioned for efficiently performing data analysis.

  18. Climate-mediated spatiotemporal variability in terrestrial productivity across Europe

    NASA Astrophysics Data System (ADS)

    Wu, X.; Babst, F.; Ciais, P.; Frank, D.; Reichstein, M.; Wattenbach, M.; Zang, C.; Mahecha, M. D.

    2014-06-01

    Quantifying the interannual variability (IAV) of the terrestrial ecosystem productivity and its sensitivity to climate is crucial for improving carbon budget predictions. In this context it is necessary to disentangle the influence of climate from impacts of other mechanisms underlying the spatiotemporal patterns of IAV of the ecosystem productivity. In this study we investigated the spatiotemporal patterns of IAV of historical observations of European crop yields in tandem with a set of climate variables. We further evaluated if relevant remote-sensing retrievals of NDVI (normalized difference vegetation index) and FAPAR (fraction of absorbed photosynthetically active radiation) depict a similar behaviour. Our results reveal distinct spatial patterns in the IAV of the analysed proxies linked to terrestrial productivity. In particular, we find higher IAV in water-limited regions of Europe (Mediterranean and temperate continental Europe) compared to other regions in both crop yield and remote-sensing observations. Our results further indicate that variations in the water balance during the active growing season exert a more pronounced and direct effect than variations of temperature on explaining the spatial patterns in IAV of productivity-related variables in temperate Europe. Overall, we observe a temporally increasing trend in the IAV of terrestrial productivity and an increasing sensitivity of productivity to water availability in dry regions of Europe during the 1975-2009 period. In the same regions, a simultaneous increase in the IAV of water availability was detected. These findings suggest intricate responses of carbon fluxes to climate variability in Europe and that the IAV of terrestrial productivity has become potentially more sensitive to changes in water availability in the dry regions in Europe. The changing sensitivity of terrestrial productivity accompanied by the changing IAV of climate is expected to impact carbon stocks and the net carbon balance of European ecosystems.

  19. Protein interactome mining defines melatonin MT1 receptors as integral component of presynaptic protein complexes of neurons.

    PubMed

    Benleulmi-Chaachoua, Abla; Chen, Lina; Sokolina, Kate; Wong, Victoria; Jurisica, Igor; Emerit, Michel Boris; Darmon, Michèle; Espin, Almudena; Stagljar, Igor; Tafelmeyer, Petra; Zamponi, Gerald W; Delagrange, Philippe; Maurice, Pascal; Jockers, Ralf

    2016-01-01

    In mammals, the hormone melatonin is mainly produced by the pineal gland with nocturnal peak levels. Its peripheral and central actions rely either on its intrinsic antioxidant properties or on binding to melatonin MT1 and MT2 receptors, belonging to the G protein-coupled receptor (GPCR) super-family. Melatonin has been reported to be involved in many functions of the central nervous system such as circadian rhythm regulation, neurotransmission, synaptic plasticity, memory, sleep, and also in Alzheimer's disease and depression. However, little is known about the subcellular localization of melatonin receptors and the molecular aspects involved in neuronal functions of melatonin. Identification of protein complexes associated with GPCRs has been shown to be a valid approach to improve our understanding of their function. By combining proteomic and genomic approaches we built an interactome of MT1 and MT2 receptors, which comprises 378 individual proteins. Among the proteins interacting with MT1 , but not with MT2 , we identified several presynaptic proteins, suggesting a potential role of MT1 in neurotransmission. Presynaptic localization of MT1 receptors in the hypothalamus, striatum, and cortex was confirmed by subcellular fractionation experiments and immunofluorescence microscopy. MT1 physically interacts with the voltage-gated calcium channel Cav 2.2 and inhibits Cav 2.2-promoted Ca(2+) entry in an agonist-independent manner. In conclusion, we show that MT1 is part of the presynaptic protein network and negatively regulates Cav 2.2 activity, providing a first hint for potential synaptic functions of MT1 . PMID:26514267

  20. 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

  1. A SILAC-based proteomics elicits the molecular interactome of alisertib (MLN8237) in human erythroleukemia K562 cells

    PubMed Central

    Shu, Li-Ping; Zhou, Zhi-Wei; Zi, Dan; He, Zhi-Xu; Zhou, Shu-Feng

    2015-01-01

    Alisertib (MLN8237, ALS), an Aurora kinase A (AURKA) inhibitor, exerts potent anti-tumor effects in the treatment of solid tumor and hematologic malignancies in preclinical and clinical studies. However, the fully spectrum of molecular targets of ALS and its anticancer effect in the treatment of chronic myeloid leukemia (CML) are not clear. This study aimed to examine the proteomic responses to ALS treatment and unveil the molecular interactome and possible mechanisms for its anticancer effect in K562 cells using stable-isotope labeling by amino acids in cell culture (SILAC) approach. The proteomic data identified that ALS treatment modulated the expression of 1541 protein molecules (570 up; 971 down). The pathway analysis showed that 299 signaling pathways and 459 cellular functional proteins directly responded to ALS treatment in K562 cells. These targeted molecules and signaling pathways were mainly involved in cell growth and proliferation, cell metabolism, and cell survival and death. Subsequently, the effects of ALS on cell cycle distribution, apoptosis, and autophagy were verified. The flow cytometric analysis showed that ALS significantly induced G2/M phase arrest and the Western blotting assays showed that ALS induced apoptosis via mitochondria-dependent pathway and promoted autophagy with the involvement of PI3K/Akt/mTOR, p38 MAPK, and AMPK signaling pathways in K562 cells. Collectively, this study provides a clue to quantitatively evaluate the proteomic responses to ALS and assists in globally identifying the potential molecular targets and elucidating the underlying mechanisms of ALS for CML treatment, which may help develop new efficacious and safe therapies for CML treatment. PMID:26807190

  2. Spatio-Temporal Patterns of Schistosomiasis Japonica in Lake and Marshland Areas in China: The Effect of Snail Habitats

    PubMed Central

    Hu, Yi; Gao, Jie; Chi, Meina; Luo, Can; Lynn, Henry; Sun, Liqian; Tao, Bo; Wang, Decheng; Zhang, Zhijie; Jiang, Qingwu

    2014-01-01

    The progress of the integrated control policy for schistosomiasis implemented since 2005 in China, which is aiming at reducing the roles of bovines and humans as infection sources, may be challenged by persistent presence of infected snails in lake and marshland areas. Based on annual parasitologic data for schistosomiasis during 2004–2011 in Xingzi County, a spatio-temporal kriging model was used to investigate the spatio-temporal pattern of schistosomiasis risk. Results showed that environmental factors related to snail habitats can explain the spatio-temporal variation of schistosomiasis. Predictive maps of schistosomiasis risk illustrated that clusters of the disease fluctuated during 2004–2008; there was an extensive outbreak in 2008 and attenuated disease occurrences afterwards. An area with an annually constant cluster of schistosomiasis was identified. Our study suggests that targeting snail habitats located within high-risk areas for schistosomiasis would be an economic and sustainable way of schistosomiasis control in the future. PMID:24980498

  3. Spatio-temporal patterns of schistosomiasis japonica in lake and marshland areas in China: the effect of snail habitats.

    PubMed

    Hu, Yi; Gao, Jie; Chi, Meina; Luo, Can; Lynn, Henry; Sun, Liqian; Tao, Bo; Wang, Decheng; Zhang, Zhijie; Jiang, Qingwu

    2014-09-01

    The progress of the integrated control policy for schistosomiasis implemented since 2005 in China, which is aiming at reducing the roles of bovines and humans as infection sources, may be challenged by persistent presence of infected snails in lake and marshland areas. Based on annual parasitologic data for schistosomiasis during 2004-2011 in Xingzi County, a spatio-temporal kriging model was used to investigate the spatio-temporal pattern of schistosomiasis risk. Results showed that environmental factors related to snail habitats can explain the spatio-temporal variation of schistosomiasis. Predictive maps of schistosomiasis risk illustrated that clusters of the disease fluctuated during 2004-2008; there was an extensive outbreak in 2008 and attenuated disease occurrences afterwards. An area with an annually constant cluster of schistosomiasis was identified. Our study suggests that targeting snail habitats located within high-risk areas for schistosomiasis would be an economic and sustainable way of schistosomiasis control in the future. PMID:24980498

  4. Size-dependent diffusion promotes the emergence of spatiotemporal patterns.

    PubMed

    Zhang, Lai; Thygesen, Uffe Høgsbro; Banerjee, Malay

    2014-07-01

    Spatiotemporal patterns, indicating the spatiotemporal variability of individual abundance, are a pronounced scenario in ecological interactions. Most of the existing models for spatiotemporal patterns treat species as homogeneous groups of individuals with average characteristics by ignoring intraspecific physiological variations at the individual level. Here we explore the impacts of size variation within species resulting from individual ontogeny, on the emergence of spatiotemporal patterns in a fully size-structured population model. We found that size dependency of animal's diffusivity greatly promotes the formation of spatiotemporal patterns, by creating regular spatiotemporal patterns out of temporal chaos. We also found that size-dependent diffusion can substitute large-amplitude base harmonics with spatiotemporal patterns with lower amplitude oscillations but with enriched harmonics. Finally, we found that the single-generation cycle is more likely to drive spatiotemporal patterns compared to predator-prey cycles, meaning that the mechanism of Hopf bifurcation might be more common than hitherto appreciated since the former cycle is more widespread than the latter in case of interacting populations. Due to the ubiquity of individual ontogeny in natural ecosystems we conclude that diffusion variability within populations is a significant driving force for the emergence of spatiotemporal patterns. Our results offer a perspective on self-organized phenomena, and pave a way to understand such phenomena in systems organized as complex ecological networks. PMID:25122357

  5. Spatiotemporal-specific lncRNAs in the brain, colon, liver and lung of macaque during development.

    PubMed

    Li, Feng; Xiao, Yun; Huang, Fei; Deng, Wei; Zhao, Hongying; Shi, Xinrui; Wang, Shuyuan; Yu, Xuexin; Zhang, Lianfeng; Han, Zujing; Luo, Longhai; Zhu, Qianhua; Jiang, Wei; Cheng, Shujun; Li, Xia; Zhang, Kaitai

    2015-12-01

    Genome-wide expression profiling during development provides useful information to uncover the potential molecular mechanisms of development in mammals. Recent studies have revealed that a subset of lncRNAs can regulate major biological processes during development. Here, we sequenced four tissues, including brain, colon, liver and lung, using RNA-seq across three developmental stages (early, middle and late stage), and then constructed genome-wide expression profiles during macaque development. In each tissue, we identified developmental time-specific lncRNA and mRNA clusters that displayed diverse expression alteration patterns, including a gradual increase, a gradual decrease, or a reversal of expression. These lncRNAs showed more specific functional associations with their corresponding tissues relative to the developmental time-specific mRNAs. Furthermore, we identified 20 spatiotemporal-specific co-modules including 101 lncRNAs and 609 mRNAs distributed at different developmental stages in different tissues. Our findings suggested that lncRNAs could play critical roles in the development of macaques through close cooperation with mRNAs. Finally, we predicted the functions of the spatiotemporal-specific lncRNAs by their spatiotemporal cooperation with mRNAs and further validated our findings using gene knockdown data of mouse. Our study reveals the spatiotemporal characteristics of lncRNAs and provides a functional map of the spatiotemporal-specific lncRNAs during the development of macaques. PMID:26456323

  6. Effects on orientation perception of manipulating the spatio-temporal prior probability of stimuli.

    PubMed

    Guo, Kun; Nevado, Angel; Robertson, Robert G; Pulgarin, Maribel; Thiele, Alexander; Young, Malcolm P

    2004-01-01

    Spatial and temporal regularities commonly exist in natural visual scenes. The knowledge of the probability structure of these regularities is likely to be informative for an efficient visual system. Here we explored how manipulating the spatio-temporal prior probability of stimuli affects human orientation perception. Stimulus sequences comprised four collinear bars (predictors) which appeared successively towards the foveal region, followed by a target bar with the same or different orientation. Subjects' orientation perception of the foveal target was biased towards the orientation of the predictors when presented in a highly ordered and predictable sequence. The discrimination thresholds were significantly elevated in proportion to increasing prior probabilities of the predictors. Breaking this sequence, by randomising presentation order or presentation duration, decreased the thresholds. These psychophysical observations are consistent with a Bayesian model, suggesting that a predictable spatio-temporal stimulus structure and an increased probability of collinear trials are associated with the increasing prior expectation of collinear events. Our results suggest that statistical spatio-temporal stimulus regularities are effectively integrated by human visual cortex over a range of spatial and temporal positions, thereby systematically affecting perception. PMID:15246751

  7. A spatio-temporal absorbing state model for disease and syndromic surveillance.

    PubMed

    Heaton, Matthew J; Banks, David L; Zou, Jian; Karr, Alan F; Datta, Gauri; Lynch, James; Vera, Francisco

    2012-08-30

    Reliable surveillance models are an important tool in public health because they aid in mitigating disease outbreaks, identify where and when disease outbreaks occur, and predict future occurrences. Although many statistical models have been devised for surveillance purposes, none are able to simultaneously achieve the important practical goals of good sensitivity and specificity, proper use of covariate information, inclusion of spatio-temporal dynamics, and transparent support to decision-makers. In an effort to achieve these goals, this paper proposes a spatio-temporal conditional autoregressive hidden Markov model with an absorbing state. The model performs well in both a large simulation study and in an application to influenza/pneumonia fatality data. PMID:22388709

  8. Spatiotemporal dynamics of random stimuli account for trial-to-trial variability in perceptual decision making.

    PubMed

    Park, Hame; Lueckmann, Jan-Matthis; von Kriegstein, Katharina; Bitzer, Sebastian; Kiebel, Stefan J

    2016-01-01

    Decisions in everyday life are prone to error. Standard models typically assume that errors during perceptual decisions are due to noise. However, it is unclear how noise in the sensory input affects the decision. Here we show that there are experimental tasks for which one can analyse the exact spatio-temporal details of a dynamic sensory noise and better understand variability in human perceptual decisions. Using a new experimental visual tracking task and a novel Bayesian decision making model, we found that the spatio-temporal noise fluctuations in the input of single trials explain a significant part of the observed responses. Our results show that modelling the precise internal representations of human participants helps predict when perceptual decisions go wrong. Furthermore, by modelling precisely the stimuli at the single-trial level, we were able to identify the underlying mechanism of perceptual decision making in more detail than standard models. PMID:26752272

  9. Spatiotemporal dynamics of random stimuli account for trial-to-trial variability in perceptual decision making

    PubMed Central

    Park, Hame; Lueckmann, Jan-Matthis; von Kriegstein, Katharina; Bitzer, Sebastian; Kiebel, Stefan J.

    2016-01-01

    Decisions in everyday life are prone to error. Standard models typically assume that errors during perceptual decisions are due to noise. However, it is unclear how noise in the sensory input affects the decision. Here we show that there are experimental tasks for which one can analyse the exact spatio-temporal details of a dynamic sensory noise and better understand variability in human perceptual decisions. Using a new experimental visual tracking task and a novel Bayesian decision making model, we found that the spatio-temporal noise fluctuations in the input of single trials explain a significant part of the observed responses. Our results show that modelling the precise internal representations of human participants helps predict when perceptual decisions go wrong. Furthermore, by modelling precisely the stimuli at the single-trial level, we were able to identify the underlying mechanism of perceptual decision making in more detail than standard models. PMID:26752272

  10. 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

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

    PubMed Central

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

    2014-01-01

    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. PMID:24850888

  12. Spatiotemporal evolution of bacterial biofilm colonies

    NASA Astrophysics Data System (ADS)

    Wilking, James; Koehler, Stephan; Sinha, Naveen; Seminara, Agnese; Brenner, Michael; Weitz, David

    2014-03-01

    Many bacteria on earth live in surface-attached communities known as biofilms. Gene expression in a biofilm is typically varied, resulting in a variety of phenotypes within a single film. These phenotypes play a critical role in biofilm physiology and development. We use time-resolved, wide-field fluorescence microscopy to image triple-labeled fluorescent Bacillus Subtilis colonies grown on agar to determine in a non-invasive fashion the evolving phenotypes. We infer their transition rates from the resulting spatiotemporal maps of gene expression. Moreover, we correlate these transition rates with local measurements of nutrient concentration to determine the influence of extracellular signals on gene expression.

  13. Spatiotemporal dynamics of networks of excitable nodes

    NASA Astrophysics Data System (ADS)

    Steele, Aaron J.; Tinsley, Mark; Showalter, Kenneth

    2006-03-01

    A network of excitable nodes based on the photosensitive Belousov-Zhabotinsky reaction is studied in experiments and simulations. The addressable medium allows both local and nonlocal links between the nodes. The initial spread of excitation across the network as well as the asymptotic oscillatory behavior are described. Synchronization of the spatiotemporal dynamics occurs by entrainment to high-frequency network pacemakers formed by excitation loops. Analysis of the asymptotic behavior reveals that the dynamics of the network is governed by a subnetwork selected during the initial transient period.

  14. Spatiotemporal rogue events in femtosecond filamentation

    SciTech Connect

    Majus, D.; Jukna, V.; Valiulis, G.; Dubietis, A.; Faccio, D.

    2011-02-15

    We present experimental and numerical investigations of optical extreme (rogue) event statistics recorded in the regime of femtosecond pulse filamentation in water. In the spectral domain, the extreme events manifest themselves as either large or small extremes of the spectral intensity, justified by right- or left-tailed statistical distributions, respectively. In the time domain, the observed extreme events are associated with pulse splitting and energy redistribution in space and therefore are exquisitely linked to three-dimensional, spatiotemporal dynamics and formation of the X waves.

  15. Subwavelength ultrasonic circulator based on spatiotemporal modulation

    NASA Astrophysics Data System (ADS)

    Fleury, Romain; Sounas, Dimitrios L.; Alù, Andrea

    2015-05-01

    Enabling efficient nonreciprocal acoustic devices is challenging, yet very desirable for a variety of applications, including acoustic imaging, underwater communications, energy concentration and harvesting, signal processing, and noise control. We discuss the theory and design of a fully linear compact acoustic circulator based on spatiotemporal modulation of the effective acoustic index, providing a compact and practical way to realize large sound circulation at any desired frequency. Our proposal enables tunable isolation levels of over 40 dB, with insertion losses as low as 0.3 dB, in a noise-free, integrable, frequency scalable device whose total size does not exceed λ /6 .

  16. Discovering RNA-Protein Interactome by Using Chemical Context Profiling of the RNA-Protein Interface

    PubMed Central

    Parisien, Marc; Wang, Xiaoyun; Perdrizet, George; Lamphear, Corissa; Fierke, Carol A.; Maheshwari, Ketan C.; Wilde, Michael J.; Sosnick, Tobin R.; Pan, Tao

    2013-01-01

    SUMMARY RNA-protein (RNP) interactions generally are required for RNA function. At least 5% of human genes code for RNA-binding proteins. Whereas many approaches can identify the RNA partners for a specific protein, finding the protein partners for a specific RNA is difficult. We present a machine-learning method that scores a protein’s binding potential for an RNA structure by utilizing the chemical context profiles of the interface from known RNP structures. Our approach is applicable even when only a single RNP structure is available. We examined 801 mammalian proteins and find that 37 (4.6%) potentially bind transfer RNA (tRNA). Most are enzymes involved in cellular processes unrelated to translation and were not known to interact with RNA. We experimentally tested six positive and three negative predictions for tRNA binding in vivo, and all nine predictions were correct. Our computational approach provides a powerful complement to experiments in discovering new RNPs. PMID:23665222

  17. Spatio-temporal population estimates for risk management

    NASA Astrophysics Data System (ADS)

    Cockings, Samantha; Martin, David; Smith, Alan; Martin, Rebecca

    2013-04-01

    Accurate estimation of population at risk from hazards and effective emergency management of events require not just appropriate spatio-temporal modelling of hazards but also of population. While much recent effort has been focused on improving the modelling and predictions of hazards (both natural and anthropogenic), there has been little parallel advance in the measurement or modelling of population statistics. Different hazard types occur over diverse temporal cycles, are of varying duration and differ significantly in their spatial extent. Even events of the same hazard type, such as flood events, vary markedly in their spatial and temporal characteristics. Conceptually and pragmatically then, population estimates should also be available for similarly varying spatio-temporal scales. Routine population statistics derived from traditional censuses or surveys are usually static representations in both space and time, recording people at their place of usual residence on census/survey night and presenting data for administratively defined areas. Such representations effectively fix the scale of population estimates in both space and time, which is unhelpful for meaningful risk management. Over recent years, the Pop24/7 programme of research, based at the University of Southampton (UK), has developed a framework for spatio-temporal modelling of population, based on gridded population surfaces. Based on a data model which is fully flexible in terms of space and time, the framework allows population estimates to be produced for any time slice relevant to the data contained in the model. It is based around a set of origin and destination centroids, which have capacities, spatial extents and catchment areas, all of which can vary temporally, such as by time of day, day of week, season. A background layer, containing information on features such as transport networks and landuse, provides information on the likelihood of people being in certain places at specific times. Unusual patterns associated with special events can also be modelled and the framework is fully volume preserving. Outputs from the model are gridded population surfaces for the specified time slice, either for total population or by sub-groups (e.g. age). Software to implement the models (SurfaceBuilder247) has been developed and pre-processed layers for typical time slices for England and Wales in 2001 and 2006 are available for UK academic purposes. The outputs and modelling framework from the Pop24/7 programme provide significant opportunities for risk management applications. For estimates of mid- to long-term cumulative population exposure to hazards, such as in flood risk mapping, populations can be produced for numerous time slices and integrated with flood models. For applications in emergency response/ management, time-specific population models can be used as seeds for agent-based models or other response/behaviour models. Estimates for sub-groups of the population also permit exploration of vulnerability through space and time. This paper outlines the requirements for effective spatio-temporal population models for risk management. It then describes the Pop24/7 framework and illustrates its potential for risk management through presentation of examples from natural and anthropogenic hazard applications. The paper concludes by highlighting key challenges for future research in this area.

  18. Workload induced spatio-temporal distortions and safety of flight

    SciTech Connect

    Barrett, C.L.; Weisgerber, S.A.; Naval Weapons Center, China Lake, CA )

    1989-01-01

    A theoretical analysis of the relationship between cognitive complexity and the perception of time and distance is presented and experimentally verified. Complex tasks produce high rates of mental representation which affect the subjective sense of duration and, through the subjective time scale, the percept of distance derived from dynamic visual cues (i.e., visual cues requiring rate integration). The analysis of the interrelationship of subjective time and subjective distance yields the prediction that, as a function of cognitive complexity, distance estimates derived from dynamic visual cues will be longer than the actual distance whereas estimates based on perceived temporal duration will be shorter than the actual distance. This prediction was confirmed in an experiment in which subjects (both pilots and non-pilots) estimated distances using either temporal cues or dynamic visual cues. The distance estimation task was also combined with secondary loading tasks in order to vary the overall task complexity. The results indicated that distance estimates based on temporal cues were underestimated while estimates based on visual cues were overestimated. This spatio-temporal distortion effect increased with increases in overall task complexity. 30 refs., 6 figs., 1 tab.

  19. Spatiotemporal modeling of monthly soil temperature using artificial neural networks

    NASA Astrophysics Data System (ADS)

    Wu, Wei; Tang, Xiao-Ping; Guo, Nai-Jia; Yang, Chao; Liu, Hong-Bin; Shang, Yue-Feng

    2013-08-01

    Soil temperature data are critical for understanding land-atmosphere interactions. However, in many cases, they are limited at both spatial and temporal scales. In the current study, an attempt was made to predict monthly mean soil temperature at a depth of 10 cm using artificial neural networks (ANNs) over a large region with complex terrain. Gridded independent variables, including latitude, longitude, elevation, topographic wetness index, and normalized difference vegetation index, were derived from a digital elevation model and remote sensing images with a resolution of 1 km. The good performance and robustness of the proposed ANNs were demonstrated by comparisons with multiple linear regressions. On average, the developed ANNs presented a relative improvement of about 44 % in root mean square error, 70 % in mean absolute percentage error, and 18 % in coefficient of determination over classical linear models. The proposed ANN models were then applied to predict soil temperatures at unsampled locations across the study area. Spatiotemporal variability of soil temperature was investigated based on the obtained database. Future work will be needed to test the applicability of ANNs for estimating soil temperature at finer scales.

  20. Advances in template-based protein docking by utilizing interfaces towards completing structural interactome.

    PubMed

    Muratcioglu, Serena; Guven-Maiorov, Emine; Keskin, Özlem; Gursoy, Attila

    2015-12-01

    The increase in the number of structurally determined protein complexes strengthens template-based docking (TBD) methods for modelling protein-protein interactions (PPIs). These methods utilize the known structures of protein complexes as templates to predict the quaternary structure of the target proteins. The templates may be partial or complete structures. Interface based (partial) methods have recently gained interest due in part to the observation that the interface regions are reusable. We describe how available template interfaces can be used to obtain the structural models of protein interactions. Despite the agreement that a majority of the protein complexes can be modelled using the available Protein Data Bank (PDB) structures, a handful of studies argue that we need more template proteins to increase the structural coverage of PPIs. We also discuss the performance of the interface TBD methods at large scale, and the significance of capturing multiple conformations for improving accuracy. PMID:26539658

  1. A network medicine approach to quantify distance between hereditary disease modules on the interactome

    NASA Astrophysics Data System (ADS)

    Caniza, Horacio; Romero, Alfonso E.; Paccanaro, Alberto

    2015-12-01

    We introduce a MeSH-based method that accurately quantifies similarity between heritable diseases at molecular level. This method effectively brings together the existing information about diseases that is scattered across the vast corpus of biomedical literature. We prove that sets of MeSH terms provide a highly descriptive representation of heritable disease and that the structure of MeSH provides a natural way of combining individual MeSH vocabularies. We show that our measure can be used effectively in the prediction of candidate disease genes. We developed a web application to query more than 28.5 million relationships between 7,574 hereditary diseases (96% of OMIM) based on our similarity measure.

  2. A network medicine approach to quantify distance between hereditary disease modules on the interactome

    PubMed Central

    Caniza, Horacio; Romero, Alfonso E.; Paccanaro, Alberto

    2015-01-01

    We introduce a MeSH-based method that accurately quantifies similarity between heritable diseases at molecular level. This method effectively brings together the existing information about diseases that is scattered across the vast corpus of biomedical literature. We prove that sets of MeSH terms provide a highly descriptive representation of heritable disease and that the structure of MeSH provides a natural way of combining individual MeSH vocabularies. We show that our measure can be used effectively in the prediction of candidate disease genes. We developed a web application to query more than 28.5 million relationships between 7,574 hereditary diseases (96% of OMIM) based on our similarity measure. PMID:26631976

  3. Asynchronous Visualization of Spatiotemporal Information for Multiple Moving Targets

    ERIC Educational Resources Information Center

    Wang, Huadong

    2013-01-01

    In the modern information age, the quantity and complexity of spatiotemporal data is increasing both rapidly and continuously. Sensor systems with multiple feeds that gather multidimensional spatiotemporal data will result in information clusters and overload, as well as a high cognitive load for users of these systems. To meet future…

  4. Asynchronous Visualization of Spatiotemporal Information for Multiple Moving Targets

    ERIC Educational Resources Information Center

    Wang, Huadong

    2013-01-01

    In the modern information age, the quantity and complexity of spatiotemporal data is increasing both rapidly and continuously. Sensor systems with multiple feeds that gather multidimensional spatiotemporal data will result in information clusters and overload, as well as a high cognitive load for users of these systems. To meet future

  5. Spatiotemporal Data Mining, Analysis, and Visualization of Human Activity Data

    ERIC Educational Resources Information Center

    Li, Xun

    2012-01-01

    This dissertation addresses the research challenge of developing efficient new methods for discovering useful patterns and knowledge in large volumes of electronically collected spatiotemporal activity data. I propose to analyze three types of such spatiotemporal activity data in a methodological framework that integrates spatial analysis, data…

  6. Spatiotemporal Data Mining, Analysis, and Visualization of Human Activity Data

    ERIC Educational Resources Information Center

    Li, Xun

    2012-01-01

    This dissertation addresses the research challenge of developing efficient new methods for discovering useful patterns and knowledge in large volumes of electronically collected spatiotemporal activity data. I propose to analyze three types of such spatiotemporal activity data in a methodological framework that integrates spatial analysis, data

  7. Interactome network analysis identifies multiple caspase-6 interactors involved in the pathogenesis of HD.

    PubMed

    Riechers, Sean-Patrick; Butland, Stefanie; Deng, Yu; Skotte, Niels; Ehrnhoefer, Dagmar E; Russ, Jenny; Laine, Jean; Laroche, Melissa; Pouladi, Mahmoud A; Wanker, Erich E; Hayden, Michael R; Graham, Rona K

    2016-04-15

    Caspase-6 (CASP6) has emerged as an important player in Huntington disease (HD), Alzheimer disease (AD) and cerebral ischemia, where it is activated early in the disease process. CASP6 also plays a key role in axonal degeneration, further underscoring the importance of this protease in neurodegenerative pathways. As a protein's function is modulated by its protein-protein interactions, we performed a high-throughput yeast-2-hybrid (Y2H) screen against ∼17 000 human proteins to gain further insight into the function of CASP6. We identified a high-confidence list of 87 potential CASP6 interactors. From this list, 61% are predicted to contain a CASP6 recognition site. Of nine candidate substrates assessed, six are cleaved by CASP6. Proteins that did not contain a predicted CASP6 recognition site were assessed using a LUMIER assay approach, and 51% were further validated as interactors by this method. Of note, 54% of the high-confidence interactors identified show alterations in human HD brain at the mRNA level, and there is a significant enrichment for previously validated huntingtin (HTT) interactors. One protein of interest, STK3, a pro-apoptotic kinase, was validated biochemically to be a CASP6 substrate. Furthermore, our results demonstrate that in striatal cells expressing mutant huntingtin (mHTT), an increase in full length and fragment levels of STK3 are observed. We further show that caspase-3 is not essential for the endogenous cleavage of STK3. Characterization of the interaction network provides important new information regarding key pathways of interactors of CASP6 and highlights potential novel therapeutic targets for HD, AD and cerebral ischemia. PMID:26908611

  8. Spatiotemporal chaos in coupled logistic maps

    NASA Astrophysics Data System (ADS)

    Varella Guedes, Andre; Amorim Savi, Marcelo

    2010-04-01

    The objective of this work is to investigate the spatiotemporal dynamics of coupled logistic maps. These maps are prototypes of high-dimensional dynamical systems and have been used to describe the evolution and pattern formation in different systems. Here, the logistic map lattice is coupled by a power law and, therefore, each map is influenced by other maps in its neighborhood. The Kolmogorov-Sinai entropy density is employed to quantify the complexity of system behavior, permitting a general qualitative understanding of different aspects of system dynamics. Three kinds of boundary conditions are treated and the influence of initial conditions is also of concern. Non-homogeneous maps are investigated, showing interesting aspects of spatiotemporal dynamics. The idea is to analyze the spatial interaction between two qualitative different types of behavior from a grid that is split into two parts. Numerical simulations show what types of conditions present a greater tendency to develop chaotic, periodic and synchronized responses. It should be highlighted that non-homogeneous grids have situations where a chaotic pattern can emerge from two periodic responses and also situations where a periodic pattern can emerge from chaos.

  9. Bilinearity in Spatiotemporal Integration of Synaptic Inputs

    PubMed Central

    Li, Songting; Liu, Nan; Zhang, Xiao-hui; Zhou, Douglas; Cai, David

    2014-01-01

    Neurons process information via integration of synaptic inputs from dendrites. Many experimental results demonstrate dendritic integration could be highly nonlinear, yet few theoretical analyses have been performed to obtain a precise quantitative characterization analytically. Based on asymptotic analysis of a two-compartment passive cable model, given a pair of time-dependent synaptic conductance inputs, we derive a bilinear spatiotemporal dendritic integration rule. The summed somatic potential can be well approximated by the linear summation of the two postsynaptic potentials elicited separately, plus a third additional bilinear term proportional to their product with a proportionality coefficient . The rule is valid for a pair of synaptic inputs of all types, including excitation-inhibition, excitation-excitation, and inhibition-inhibition. In addition, the rule is valid during the whole dendritic integration process for a pair of synaptic inputs with arbitrary input time differences and input locations. The coefficient is demonstrated to be nearly independent of the input strengths but is dependent on input times and input locations. This rule is then verified through simulation of a realistic pyramidal neuron model and in electrophysiological experiments of rat hippocampal CA1 neurons. The rule is further generalized to describe the spatiotemporal dendritic integration of multiple excitatory and inhibitory synaptic inputs. The integration of multiple inputs can be decomposed into the sum of all possible pairwise integration, where each paired integration obeys the bilinear rule. This decomposition leads to a graph representation of dendritic integration, which can be viewed as functionally sparse. PMID:25521832

  10. Responses of spatiotemporal chaos to oscillating forces

    NASA Astrophysics Data System (ADS)

    Iino, Misato; Hidaka, Yoshiki; Nugroho, Fahrudin; Anugraha, Rinto; Okabe, Hirotaka; Hara, Kazuhiro

    2015-07-01

    The responses of soft-mode turbulence, a kind of spatiotemporal chaos seen in electroconvection of a nematic liquid crystal, to alternating-current magnetic fields is investigated to uncover the dynamical properties of spatiotemporal chaos. The dynamical responses can be measured by an order parameter, Mp(t ) , which indicates ordering in the convective roll pattern induced by the magnetic field. Determined by properties of the liquid crystal in a magnetic field, Mp(t ) oscillates in accordance with the square of the magnetic field. The relaxation time of the system was obtained by fitting the frequency dependence of the complex susceptibility for the pattern obtained from the oscillation of Mp(t ) to the Debye-type relaxation spectra. However, for the high-frequency regime, the susceptibility deviates from the spectra because slow and large fluctuations of Mp(t ) contribute to the oscillation. The properties of this type of fluctuation were investigated by introducing a dynamic ordering parameter defined as the period average of Mp(t ) .

  11. Controllable spatiotemporal nonlinear effects in multimode fibres

    NASA Astrophysics Data System (ADS)

    Wright, Logan G.; Christodoulides, Demetrios N.; Wise, Frank W.

    2015-05-01

    Multimode fibres are of interest for next-generation telecommunications systems and the construction of high-energy fibre lasers. However, relatively little work has explored nonlinear pulse propagation in multimode fibres. Here, we consider highly nonlinear ultrashort pulse propagation in the anomalous-dispersion regime of a graded-index multimode fibre. Low modal dispersion and strong nonlinear coupling between the fibre's many spatial modes result in interesting behaviour. We observe spatiotemporal effects reminiscent of nonlinear optics in bulk mediaself-focusing and multiple filamentationat a fraction of the usual power. By adjusting the spatial initial conditions, we generate on-demand, megawatt, ultrashort pulses tunable between 1,550 and 2,200?nm dispersive waves over one octave; intense combs of visible light; and a multi-octave-spanning supercontinuum. Our results indicate that multimode fibres present unique opportunities for observing new spatiotemporal dynamics and phenomena. They also enable the realization of a new type of tunable, broadband fibre source that could be useful for many applications.

  12. Exploring Spatiotemporal Organization of SCN Circuits

    PubMed Central

    Yan, L.; Karatsoreos, I.; LeSauter, J.; Welsh, D.K.; Kay, S.; Foley, D.; Silver, R.

    2012-01-01

    Suprachiasmatic nucleus neuroanatomy has been a subject of intense interest since the discovery of the SCN’s function as a brain clock and subsequent studies revealing substantial heterogeneity of its component neurons. Understanding the network organization of the SCN has become increasingly relevant in the context of studies showing that its functional circuitry, evident in the spatial and temporal expression of clock genes, can be reorganized by inputs from the internal and external environment. Although multiple mechanisms have been proposed for coupling among SCN neurons, relatively little is known of the precise pattern of SCN circuitry. To explore SCN networks, we examine responses of the SCN to various photic conditions, using in vivo and in vitro studies with associated mathematical modeling to study spatiotemporal changes in SCN activity. We find an orderly and reproducible spatiotemporal pattern of oscillatory gene expression in the SCN, which requires the presence of the ventrolateral core region. Without the SCN core region, behavioral rhythmicity is abolished in vivo, whereas low-amplitude rhythmicity can be detected in SCN slices in vitro, but with loss of normal topographic organization. These studies reveal SCN circuit properties required to signal daily time. PMID:18419312

  13. CUTOFF: A spatio-temporal imputation method

    NASA Astrophysics Data System (ADS)

    Feng, Lingbing; Nowak, Gen; O'Neill, T. J.; Welsh, A. H.

    2014-11-01

    Missing values occur frequently in many different statistical applications and need to be dealt with carefully, especially when the data are collected spatio-temporally. We propose a method called CUTOFF imputation that utilizes the spatio-temporal nature of the data to accurately and efficiently impute missing values. The main feature of this method is that the estimate of a missing value is produced by incorporating similar observed temporal information from the value's nearest spatial neighbors. Extensions to this method are also developed to expand the method's ability to accommodate other data generating processes. We develop a cross-validation procedure that optimally chooses parameters for CUTOFF, which can be used by other imputation methods as well. We analyze some rainfall data from 78 gauging stations in the Murray-Darling Basin in Australia using the CUTOFF imputation method and compare its performance to four well-studied competing imputation methods, namely, k-nearest neighbors, singular value decomposition, multiple imputation and random forest. Empirical results show that our method captures the temporal patterns well and is effective at imputing large gaps in the data. Compared to the competing methods, CUTOFF is more accurate and much faster. We analyze further examples to demonstrate CUTOFF's applications to two different data sets and provide extra evidence of its validity and usefulness. We implement a simulation study based on the Murray-Darling Basin data to evaluate the method; the results show that our method performs well in both accuracy and computational efficiency.

  14. Spatiotemporal control of opioid signaling and behavior

    PubMed Central

    Siuda, Edward R.; Copits, Bryan A.; Schmidt, Martin J.; Baird, Madison A.; Al-Hasani, Ream; Planer, William J.; Funderburk, Samuel C.; McCall, Jordan G.; Gereau, Robert W.; Bruchas, Michael R.

    2015-01-01

    Summary Optogenetics is now a widely accepted tool for spatiotemporal manipulation of neuronal activity. However, a majority of optogenetic approaches use binary on/off control schemes. Here we extend the optogenetic toolset by developing a neuromodulatory approach using a rationale-based design to generate a Gi-coupled, optically-sensitive, mu-opioid-like receptor, we term opto-MOR. We demonstrate that opto-MOR engages canonical mu-opioid signaling through inhibition of adenylyl cyclase, activation of MAPK and G protein-gated inward rectifying potassium (GIRK) channels, and internalizes with similar kinetics as the mu-opioid receptor. To assess in vivo utility we expressed a Cre-dependent viral opto-MOR in RMTg/VTA GABAergic neurons, which led to a real-time place preference. In contrast, expression of opto-MOR in GABAergic neurons of the ventral pallidum hedonic cold spot, led to real-time place aversion. This tool has generalizable application for spatiotemporal control of opioid signaling and, furthermore, can be used broadly for mimicking endogenous neuronal inhibition pathways. PMID:25937173

  15. The spatiotemporal dynamics of scene gist recognition.

    PubMed

    Larson, Adam M; Freeman, Tyler E; Ringer, Ryan V; Loschky, Lester C

    2014-04-01

    Viewers can rapidly extract a holistic semantic representation of a real-world scene within a single eye fixation, an ability called recognizing the gist of a scene, and operationally defined here as recognizing an image's basic-level scene category. However, it is unknown how scene gist recognition unfolds over both time and space-within a fixation and across the visual field. Thus, in 3 experiments, the current study investigated the spatiotemporal dynamics of basic-level scene categorization from central vision to peripheral vision over the time course of the critical first fixation on a novel scene. The method used a window/scotoma paradigm in which images were briefly presented and processing times were varied using visual masking. The results of Experiments 1 and 2 showed that during the first 100 ms of processing, there was an advantage for processing the scene category from central vision, with the relative contributions of peripheral vision increasing thereafter. Experiment 3 tested whether this pattern could be explained by spatiotemporal changes in selective attention. The results showed that manipulating the probability of information being presented centrally or peripherally selectively maintained or eliminated the early central vision advantage. Across the 3 experiments, the results are consistent with a zoom-out hypothesis, in which, during the first fixation on a scene, gist extraction extends from central vision to peripheral vision as covert attention expands outward. PMID:24245502

  16. targetTB: A target identification pipeline for Mycobacterium tuberculosis through an interactome, reactome and genome-scale structural analysis

    PubMed Central

    Raman, Karthik; Yeturu, Kalidas; Chandra, Nagasuma

    2008-01-01

    Background Tuberculosis still remains one of the largest killer infectious diseases, warranting the identification of newer targets and drugs. Identification and validation of appropriate targets for designing drugs are critical steps in drug discovery, which are at present major bottle-necks. A majority of drugs in current clinical use for many diseases have been designed without the knowledge of the targets, perhaps because standard methodologies to identify such targets in a high-throughput fashion do not really exist. With different kinds of 'omics' data that are now available, computational approaches can be powerful means of obtaining short-lists of possible targets for further experimental validation. Results We report a comprehensive in silico target identification pipeline, targetTB, for Mycobacterium tuberculosis. The pipeline incorporates a network analysis of the protein-protein interactome, a flux balance analysis of the reactome, experimentally derived phenotype essentiality data, sequence analyses and a structural assessment of targetability, using novel algorithms recently developed by us. Using flux balance analysis and network analysis, proteins critical for survival of M. tuberculosis are first identified, followed by comparative genomics with the host, finally incorporating a novel structural analysis of the binding sites to assess the feasibility of a protein as a target. Further analyses include correlation with expression data and non-similarity to gut flora proteins as well as 'anti-targets' in the host, leading to the identification of 451 high-confidence targets. Through phylogenetic profiling against 228 pathogen genomes, shortlisted targets have been further explored to identify broad-spectrum antibiotic targets, while also identifying those specific to tuberculosis. Targets that address mycobacterial persistence and drug resistance mechanisms are also analysed. Conclusion The pipeline developed provides rational schema for drug target identification that are likely to have high rates of success, which is expected to save enormous amounts of money, resources and time in the drug discovery process. A thorough comparison with previously suggested targets in the literature demonstrates the usefulness of the integrated approach used in our study, highlighting the importance of systems-level analyses in particular. The method has the potential to be used as a general strategy for target identification and validation and hence significantly impact most drug discovery programmes. PMID:19099550

  17. Spatio-temporal autocorrelation measures for nonstationary series: A new temporally detrended spatio-temporal Moran's index

    NASA Astrophysics Data System (ADS)

    Shen, Chenhua; Li, Chaoling; Si, Yali

    2016-01-01

    In order to measure the spatio-temporal autocorrelation's degree for spatio-temporal nonstationary series, the new temporally detrended global and local spatio-temporal Moran's indexes (TDGSTI and TDLSTI) are proposed. The implementation of the new Moran's indexes is illustrated through artificial and real examples. Analyses of the influencing factors on TDGSTI are performed. A statistical test of TDGSTI is taken. The Moran's scatter plot, which discloses the spatio-temporal cluster pattern's characteristics and pattern's change, is extended. TDGSTI is found to reveal the autocorrelation level of spatio-temporal objects. For a positive TDGSTI, the higher the TDGSTI, the higher the autocorrelation level, and vice versa. TDGSTI is closely related to time-scale s, time-lag h and spatio-temporal weight matrix. For s ? h, TDGSTI is significant, while for s ? h and s < h, TDGSTI is insignificant. TDGSTI has clear potential to test the spatio-temporal autocorrelation's degree for spatio-temporal nonstationary series in other research fields.

  18. Integrated interactions database: tissue-specific view of the human and model organism interactomes.

    PubMed

    Kotlyar, Max; Pastrello, Chiara; Sheahan, Nicholas; Jurisica, Igor

    2016-01-01

    IID (Integrated Interactions Database) is the first database providing tissue-specific protein-protein interactions (PPIs) for model organisms and human. IID covers six species (S. cerevisiae (yeast), C. elegans (worm), D. melonogaster (fly), R. norvegicus (rat), M. musculus (mouse) and H. sapiens (human)) and up to 30 tissues per species. Users query IID by providing a set of proteins or PPIs from any of these organisms, and specifying species and tissues where IID should search for interactions. If query proteins are not from the selected species, IID enables searches across species and tissues automatically by using their orthologs; for example, retrieving interactions in a given tissue, conserved in human and mouse. Interaction data in IID comprises three types of PPI networks: experimentally detected PPIs from major databases, orthologous PPIs and high-confidence computationally predicted PPIs. Interactions are assigned to tissues where their proteins pairs or encoding genes are expressed. IID is a major replacement of the I2D interaction database, with larger PPI networks (a total of 1,566,043 PPIs among 68,831 proteins), tissue annotations for interactions, and new query, analysis and data visualization capabilities. IID is available at http://ophid.utoronto.ca/iid. PMID:26516188

  19. cytoHubba: identifying hub objects and sub-networks from complex interactome

    PubMed Central

    2014-01-01

    Background Network is a useful way for presenting many types of biological data including protein-protein interactions, gene regulations, cellular pathways, and signal transductions. We can measure nodes by their network features to infer their importance in the network, and it can help us identify central elements of biological networks. Results We introduce a novel Cytoscape plugin cytoHubba for ranking nodes in a network by their network features. CytoHubba provides 11 topological analysis methods including Degree, Edge Percolated Component, Maximum Neighborhood Component, Density of Maximum Neighborhood Component, Maximal Clique Centrality and six centralities (Bottleneck, EcCentricity, Closeness, Radiality, Betweenness, and Stress) based on shortest paths. Among the eleven methods, the new proposed method, MCC, has a better performance on the precision of predicting essential proteins from the yeast PPI network. Conclusions CytoHubba provide a user-friendly interface to explore important nodes in biological networks. It computes all eleven methods in one stop shopping way. Besides, researchers are able to combine cytoHubba with and other plugins into a novel analysis scheme. The network and sub-networks caught by this topological analysis strategy will lead to new insights on essential regulatory networks and protein drug targets for experimental biologists. According to cytoscape plugin download statistics, the accumulated number of cytoHubba is around 6,700 times since 2010. PMID:25521941

  20. The Binary Protein Interactome of Treponema pallidum – The Syphilis Spirochete

    PubMed Central

    Goll, Johannes; Häuser, Roman; McKevitt, Matthew T.; Palzkill, Timothy; Uetz, Peter

    2008-01-01

    Protein interaction networks shed light on the global organization of proteomes but can also place individual proteins into a functional context. If we know the function of bacterial proteins we will be able to understand how these species have adapted to diverse environments including many extreme habitats. Here we present the protein interaction network for the syphilis spirochete Treponema pallidum which encodes 1,039 proteins, 726 (or 70%) of which interact via 3,649 interactions as revealed by systematic yeast two-hybrid screens. A high-confidence subset of 991 interactions links 576 proteins. To derive further biological insights from our data, we constructed an integrated network of proteins involved in DNA metabolism. Combining our data with additional evidences, we provide improved annotations for at least 18 proteins (including TP0004, TP0050, and TP0183 which are suggested to be involved in DNA metabolism). We estimate that this “minimal” bacterium contains on the order of 3,000 protein interactions. Profiles of functional interconnections indicate that bacterial proteins interact more promiscuously than eukaryotic proteins, reflecting the non-compartmentalized structure of the bacterial cell. Using our high-confidence interactions, we also predict 417,329 homologous interactions (“interologs”) for 372 completely sequenced genomes and provide evidence that at least one third of them can be experimentally confirmed. PMID:18509523

  1. Integrated interactions database: tissue-specific view of the human and model organism interactomes

    PubMed Central

    Kotlyar, Max; Pastrello, Chiara; Sheahan, Nicholas; Jurisica, Igor

    2016-01-01

    IID (Integrated Interactions Database) is the first database providing tissue-specific proteinprotein interactions (PPIs) for model organisms and human. IID covers six species (S. cerevisiae (yeast), C. elegans (worm), D. melonogaster (fly), R. norvegicus (rat), M. musculus (mouse) and H. sapiens (human)) and up to 30 tissues per species. Users query IID by providing a set of proteins or PPIs from any of these organisms, and specifying species and tissues where IID should search for interactions. If query proteins are not from the selected species, IID enables searches across species and tissues automatically by using their orthologs; for example, retrieving interactions in a given tissue, conserved in human and mouse. Interaction data in IID comprises three types of PPI networks: experimentally detected PPIs from major databases, orthologous PPIs and high-confidence computationally predicted PPIs. Interactions are assigned to tissues where their proteins pairs or encoding genes are expressed. IID is a major replacement of the I2D interaction database, with larger PPI networks (a total of 1,566,043 PPIs among 68,831 proteins), tissue annotations for interactions, and new query, analysis and data visualization capabilities. IID is available at http://ophid.utoronto.ca/iid. PMID:26516188

  2. The TOPLESS Interactome: A Framework for Gene Repression in Arabidopsis1[W][OA

    PubMed Central

    Causier, Barry; Ashworth, Mary; Guo, Wenjia; Davies, Brendan

    2012-01-01

    Transcription factors activate or repress target gene expression or switch between activation and repression. In animals and yeast, Groucho/Tup1 corepressor proteins are recruited by diverse transcription factors to induce context-specific transcriptional repression. Two groups of Groucho/Tup1-like corepressors have been described in plants. LEUNIG and LEUNIG_HOMOLOG constitute one group and TOPLESS (TPL) and the four TPL-related (TPR) corepressors form the other. To discover the processes in which TPL and the TPR corepressors operate, high-throughput yeast two-hybrid approaches were used to identify interacting proteins. We found that TPL/TPR corepressors predominantly interact directly with specific transcription factors, many of which were previously implicated in transcriptional repression. The interacting transcription factors reveal that the TPL/TPR family has been coopted multiple times to modulate gene expression in diverse processes, including hormone signaling, stress responses, and the control of flowering time, for which we also show biological validation. The interaction data suggest novel mechanisms for the involvement of TPL/TPR corepressors in auxin and jasmonic acid signaling. A number of short repression domain (RD) sequences have previously been identified in Arabidopsis (Arabidopsis thaliana) transcription factors. All known RD sequences were enriched among the TPL/TPR interactors, and novel TPL-RD interactions were identified. We show that the presence of RD sequences is essential for TPL/TPR recruitment. These data provide a framework for TPL/TPR-dependent transcriptional repression. They allow for predictions about new repressive transcription factors, corepressor interactions, and repression mechanisms and identify a wide range of plant processes that utilize TPL/TPR-mediated gene repression. PMID:22065421

  3. Spatiotemporal Stochastic Resonance:Theory and Experiment

    NASA Astrophysics Data System (ADS)

    Peter, Jung

    1996-03-01

    The amplification of weak periodic signals in bistable or excitable systems via stochastic resonance has been studied intensively over the last years. We are going one step further and ask: Can noise enhance spatiotemporal patterns in excitable media and can this effect be observed in nature? To this end, we are looking at large, two dimensional arrays of coupled excitable elements. Due to the coupling, excitation can propagate through the array in form of nonlinear waves. We observe target waves, rotating spiral waves and other wave forms. If the coupling between the elements is below a critical threshold, any excitational pattern will die out in the absence of noise. Below this threshold, large scale rotating spiral waves - as they are observed above threshold - can be maintained by a proper level of the noise[1]. Furthermore, their geometric features, such as the curvature can be controlled by the homogeneous noise level[2]. If the noise level is too large, break up of spiral waves and collisions with spontaneously nucleated waves yields spiral turbulence. Driving our array with a spatiotemporal pattern, e.g. a rotating spiral wave, we show that for weak coupling the excitational response of the array shows stochastic resonance - an effect we have termed spatiotemporal stochastic resonance. In the last part of the talk I'll make contact with calcium waves, observed in astrocyte cultures and hippocampus slices[3]. A. Cornell-Bell and collaborators[3] have pointed out the role of calcium waves for long-range glial signaling. We demonstrate the similarity of calcium waves with nonlinear waves in noisy excitable media. The noise level in the tissue is characterized by spontaneous activity and can be controlled by applying neuro-transmitter substances[3]. Noise effects in our model are compared with the effect of neuro-transmitters on calcium waves. [1]P. Jung and G. Mayer-Kress, CHAOS 5, 458 (1995). [2]P. Jung and G. Mayer-Kress, Phys. Rev. Lett.62, 2682 (1995). [3] A. Cornell-Bell, Steven M. Finkbeiner, Mark.S. Cooper and Stephen J. Smith, SCIENCE, 247, 373 (1990).

  4. Spatio-Temporal Change Modeling of Lulc: a Semantic Kriging Approach

    NASA Astrophysics Data System (ADS)

    Bhattacharjee, S.; Ghosh, S. K.

    2015-07-01

    Spatio-temporal land-use/ land-cover (LULC) change modeling is important to forecast the future LULC distribution, which may facilitate natural resource management, urban planning, etc. The spatio-temporal change in LULC trend often exhibits non-linear behavior, due to various dynamic factors, such as, human intervention (e.g., urbanization), environmental factors, etc. Hence, proper forecasting of LULC distribution should involve the study and trend modeling of historical data. Existing literatures have reported that the meteorological attributes (e.g., NDVI, LST, MSI), are semantically related to the terrain. Being influenced by the terrestrial dynamics, the temporal changes of these attributes depend on the LULC properties. Hence, incorporating meteorological knowledge into the temporal prediction process may help in developing an accurate forecasting model. This work attempts to study the change in inter-annual LULC pattern and the distribution of different meteorological attributes of a region in Kolkata (a metropolitan city in India) during the years 2000-2010 and forecast the future spread of LULC using semantic kriging (SemK) approach. A new variant of time-series SemK is proposed, namely Rev-SemKts to capture the multivariate semantic associations between different attributes. From empirical analysis, it may be observed that the augmentation of semantic knowledge in spatio-temporal modeling of meteorological attributes facilitate more precise forecasting of LULC pattern.

  5. Spatiotemporal multifractal characteristics of electromagnetic radiation in response to deep coal rock bursts

    NASA Astrophysics Data System (ADS)

    Hu, S.; Wang, E.; Liu, X.

    2014-08-01

    Dynamic collapses of deeply mined coal rocks are severe threats to miners; in order to predict collapses more accurately using electromagnetic radiation (EMR), we investigate the spatiotemporal multifractal characteristics and formation mechanism of EMR induced by underground coal mining. Coal rock in the burst-prone zone often exchanges materials (gas, water and coal) and energy with its environment and gradually transitions from its original stable equilibrium structure to a nonequilibrium dissipative structure with implicit spatiotemporal complexity or multifractal structures, resulting in temporal variation in multifractal EMR. The inherent law of EMR time series during damage evolution was analyzed by using time-varying multifractal theory. Results show that the time-varying multifractal characteristics of EMR are determined by damage evolution processes. Moreover, the dissipated energy caused by the damage evolutions, such as crack propagation, fractal sliding and shearing, can be regarded as the fingerprint of various EMR micro-mechanics. The dynamic spatiotemporal multifractal spectrum of EMR considers both spatial (multiple fractures) and temporal (dynamic evolution) characteristics of coal rocks and records the dynamic evolution processes of rock bursts. Thus, it can be used to evaluate the coal deformation and fracture process. The study is of significance for us to understand the EMR mechanism in detail and to increase the accuracy of the EMR method in forecasting dynamic disasters.

  6. A Metascalable Computing Framework for Large Spatiotemporal-Scale Atomistic Simulations

    SciTech Connect

    Nomura, K; Seymour, R; Wang, W; Kalia, R; Nakano, A; Vashishta, P; Shimojo, F; Yang, L H

    2009-02-17

    A metascalable (or 'design once, scale on new architectures') parallel computing framework has been developed for large spatiotemporal-scale atomistic simulations of materials based on spatiotemporal data locality principles, which is expected to scale on emerging multipetaflops architectures. The framework consists of: (1) an embedded divide-and-conquer (EDC) algorithmic framework based on spatial locality to design linear-scaling algorithms for high complexity problems; (2) a space-time-ensemble parallel (STEP) approach based on temporal locality to predict long-time dynamics, while introducing multiple parallelization axes; and (3) a tunable hierarchical cellular decomposition (HCD) parallelization framework to map these O(N) algorithms onto a multicore cluster based on hybrid implementation combining message passing and critical section-free multithreading. The EDC-STEP-HCD framework exposes maximal concurrency and data locality, thereby achieving: (1) inter-node parallel efficiency well over 0.95 for 218 billion-atom molecular-dynamics and 1.68 trillion electronic-degrees-of-freedom quantum-mechanical simulations on 212,992 IBM BlueGene/L processors (superscalability); (2) high intra-node, multithreading parallel efficiency (nanoscalability); and (3) nearly perfect time/ensemble parallel efficiency (eon-scalability). The spatiotemporal scale covered by MD simulation on a sustained petaflops computer per day (i.e. petaflops {center_dot} day of computing) is estimated as NT = 2.14 (e.g. N = 2.14 million atoms for T = 1 microseconds).

  7. Spatiotemporal multifractal characteristics of electromagnetic radiation in response to deep coal rock bursts

    NASA Astrophysics Data System (ADS)

    Shaobin, H.; Enyuan, W.; Xiaofei, L.

    2014-04-01

    Dynamic collapses of deeply mined coal rocks are severe threats to miners, in order to predict the collapses more accurately using electromagnetic radiation (EMR), we investigate the spatiotemporal multifractal characteristics and formation mechanism of EMR induced by underground coal mining. Coal rock in the burst-prone zone often exchanges materials and energy with its environment and gradually transits from its original stable equilibrium structure to a non-equilibrium dissipative structure with implicit spatiotemporal complexity or multifractal structures, resulting in temporal variation in multifractal EMR. The inherent law of EMR time series during damage evolution was analyzed by using time-varying multifractal theory. Results show that the time-varying multifractal characteristics of EMR are determined by damage evolutions process, the dissipated energy caused by damage evolutions such as crack propagation, fractal sliding and shearing can be regarded as the fingerprint of various EMR micro-mechanics. Dynamic spatiotemporal multifractal spectrum of EMR considers both spatial (multiple fractures) and temporal (dynamic evolution) characteristics of coal rocks, and records the dynamic evolution processes of rock bursts. Thus, it can be used to evaluate the coal deformation and fracture process. The study is of significance for us to in-depth understand EMR mechanism and to increase the accuracy of applying the EMR method to forecast dynamic disasters.

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

    PubMed Central

    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. PMID:26465331

  9. Impact of spatiotemporal fluctuations in airborne chemical concentration on toxic hazard assessment.

    PubMed

    Bogen, K T; Gouveia, F J

    2008-03-21

    Models widely used to assess atmospheric chemical-dispersion hazards for emergency response rely on acute exposure guideline level (AEGL) or similar concentration guidelines to map geographic areas potentially affected by corresponding levels of toxic severity. By ignoring substantial, random variability in concentration over time and space, such standard methods routinely underestimate the size of potentially affected areas. Underestimation due to temporal fluctuation - applicable to chemicals like hydrogen cyanide (HCN) for which peak concentrations best predict acute toxicity - becomes magnified by spatial fluctuation, defined as heterogeneity in average concentration at each location relative to standard-method predictions. The combined impact of spatiotemporal fluctuation on size of assessed threat areas was studied using a statistical-simulation assessment method calibrated to Joint Urban 2003 Oklahoma City field-tracer data. For a hypothetical 60-min urban release scenario involving HCN gas, the stochastic method predicted that lethal/severe effects could occur in an area 18 or 25 times larger than was predicted by standard methods targeted to a 60-min AEGL, assuming wind speeds > or =2.0 or < or =1.5m/s, respectively. The underestimation doubled when the standard method was targeted to a 10-min AEGL. Further research and field data are needed for improved stochastic methods to assess spatiotemporal fluctuation effects. PMID:17706864

  10. Characterizing configurations of fire ignition points through spatiotemporal point processes

    NASA Astrophysics Data System (ADS)

    Comas, C.; Costafreda-Aumedes, S.; Vega-Garcia, C.

    2014-04-01

    Human-caused forest fires are usually regarded as unpredictable but often exhibit trends towards clustering in certain locations and periods. Characterizing such configurations is crucial for understanding spatiotemporal fire dynamics and implementing preventive actions. Our objectives were to analyse the spatiotemporal point configuration and to test for spatiotemporal interaction. We characterized the spatiotemporal structure of 984 fire ignition points in a study area of Galicia, Spain, during 2007-2011 by the K-Ripley's function. Our results suggest the presence of spatiotemporal structures for time lags of less than two years and ignition point distances in the range 0-12 km. Ignition centre points at time lags of less than 100 days are aggregated for any inter-event distance. This cluster structure loses strength as the time lag increases, and at time lags of more than 365 days this cluster structure is not significant for any lag distance. Our results also suggest spatiotemporal interdependencies at time lags of less than 100 days and inter-event distances of less than 10 km. At time lags of up to 365 days spatiotemporal components are independent for any point distance. These results suggest that risk conditions occur locally and are short-lived in this study area.

  11. Bayesian modeling and analysis for gradients in spatiotemporal processes.

    PubMed

    Quick, Harrison; Banerjee, Sudipto; Carlin, Bradley P

    2015-09-01

    Stochastic process models are widely employed for analyzing spatiotemporal datasets in various scientific disciplines including, but not limited to, environmental monitoring, ecological systems, forestry, hydrology, meteorology, and public health. After inferring on a spatiotemporal process for a given dataset, inferential interest may turn to estimating rates of change, or gradients, over space and time. This manuscript develops fully model-based inference on spatiotemporal gradients under continuous space, continuous time settings. Our contribution is to offer, within a flexible spatiotemporal process model setting, a framework to estimate arbitrary directional gradients over space at any given timepoint, temporal derivatives at any given spatial location and, finally, mixed spatiotemporal gradients that reflect rapid change in spatial gradients over time and vice-versa. We achieve such inference without compromising on rich and flexible spatiotemporal process models and use nonseparable covariance structures. We illustrate our methodology using a simulated data example and subsequently apply it to a dataset of daily PM2.5 concentrations in California, where the spatiotemporal gradient process reveals the effects of California's unique topography on pollution and detects the aftermath of a devastating series of wildfires. PMID:25898989

  12. Research on spatio-temporal ontology based on description logic

    NASA Astrophysics Data System (ADS)

    Huang, Yongqi; Ding, Zhimin; Zhao, Zhui; Ouyang, Fucheng

    2008-10-01

    DL, short for Description Logic, is aimed at getting a balance between describing ability and reasoning complexity. Users can adopt DL to write clear and formalized concept description for domain model, which makes ontology description possess well-defined syntax and semantics and helps to resolve the problem of spatio-temporal reasoning based on ontology. This paper studies on basic theory of DL and relationship between DL and OWL at first. By analyzing spatio-temporal concepts and relationship of spatio-temporal GIS, the purpose of this paper is adopting ontology language based on DL to express spatio-temporal ontology, and employing suitable ontology-building tool to build spatio-temporal ontology. With regard to existing spatio-temporal ontology based on first-order predicate logic, we need to transform it into spatio-temporal ontology based on DL so as to make the best of existing research fruits. This paper also makes a research on translating relationships between DL and first-order predicate logic.

  13. Bayesian Modeling and Analysis for Gradients in Spatiotemporal Processes

    PubMed Central

    Quick, Harrison; Banerjee, Sudipto; Carlin, Bradley P.

    2015-01-01

    Summary Stochastic process models are widely employed for analyzing spatiotemporal datasets in various scientific disciplines including, but not limited to, environmental monitoring, ecological systems, forestry, hydrology, meteorology and public health. After inferring on a spatiotemporal process for a given dataset, inferential interest may turn to estimating rates of change, or gradients, over space and time. This manuscript develops fully model-based inference on spatiotemporal gradients under continuous space, continuous time settings. Our contribution is to offer, within a exible spatiotemporal process model setting, a framework to estimate arbitrary directional gradients over space at any given timepoint, temporal derivatives at any given spatial location and, finally, mixed spatiotemporal gradients that reflect rapid change in spatial gradients over time and vice-versa. We achieve such inference without compromising on rich and exible spatiotemporal process models and use nonseparable covariance structures. We illustrate our methodology using a simulated data example and subsequently apply it to a dataset of daily PM2.5 concentrations in California, where the spatiotemporal gradient process reveals the effects of California’s unique topography on pollution and detects the aftermath of a devastating series of wildfires. PMID:25898989

  14. Concerning immune synapses: a spatiotemporal timeline.

    PubMed

    Ortega-Carrion, Alvaro; Vicente-Manzanares, Miguel

    2016-01-01

    The term "immune synapse" was originally coined to highlight the similarities between the synaptic contacts between neurons in the central nervous system and the cognate, antigen-dependent interactions between T cells and antigen-presenting cells. Here, instead of offering a comprehensive molecular catalogue of molecules involved in the establishment, stabilization, function, and resolution of the immune synapse, we follow a spatiotemporal timeline that begins at the initiation of exploratory contacts between the T cell and the antigen-presenting cell and ends with the termination of the contact. We focus on specific aspects that distinguish synapses established by cytotoxic and T helper cells as well as unresolved issues and controversies regarding the formation of this intercellular structure. PMID:27092248

  15. Cortical spatiotemporal dimensionality reduction for visual grouping.

    PubMed

    Cocci, Giacomo; Barbieri, Davide; Citti, Giovanna; Sarti, Alessandro

    2015-06-01

    The visual systems of many mammals, including humans, are able to integrate the geometric information of visual stimuli and perform cognitive tasks at the first stages of the cortical processing. This is thought to be the result of a combination of mechanisms, which include feature extraction at the single cell level and geometric processing by means of cell connectivity. We present a geometric model of such connectivities in the space of detected features associated with spatiotemporal visual stimuli and show how they can be used to obtain low-level object segmentation. The main idea is to define a spectral clustering procedure with anisotropic affinities over data sets consisting of embeddings of the visual stimuli into higher-dimensional spaces. Neural plausibility of the proposed arguments will be discussed. PMID:25826020

  16. Concerning immune synapses: a spatiotemporal timeline

    PubMed Central

    Ortega-Carrion, Alvaro; Vicente-Manzanares, Miguel

    2016-01-01

    The term “immune synapse” was originally coined to highlight the similarities between the synaptic contacts between neurons in the central nervous system and the cognate, antigen-dependent interactions between T cells and antigen-presenting cells. Here, instead of offering a comprehensive molecular catalogue of molecules involved in the establishment, stabilization, function, and resolution of the immune synapse, we follow a spatiotemporal timeline that begins at the initiation of exploratory contacts between the T cell and the antigen-presenting cell and ends with the termination of the contact. We focus on specific aspects that distinguish synapses established by cytotoxic and T helper cells as well as unresolved issues and controversies regarding the formation of this intercellular structure. PMID:27092248

  17. Spatiotemporal dynamics of counterpropagating Airy beams

    NASA Astrophysics Data System (ADS)

    Wiersma, Nomi; Marsal, Nicolas; Sciamanna, Marc; Wolfersberger, Delphine

    2015-08-01

    We analyse theoretically the spatiotemporal dynamics of two incoherent counterpropagating Airy beams interacting in a photorefractive crystal under focusing conditions. For a large enough nonlinearity strength the interaction between the two Airy beams leads to light-induced waveguiding. The stability of the waveguide is determined by the crystal length, the nonlinearity strength and the beams intensities and is improved when comparing to the situation using Gaussian beams. We further identify the threshold above which the waveguide is no longer static but evolves dynamically either time-periodically or even chaotically. Above the stability threshold, each Airy-soliton moves erratically between privileged output positions that correspond to the spatial positions of the lobes of the counterpropagating Airy beam. These results suggest new ways of creating dynamically varying waveguides, optical logic gates and chaos-based computing.

  18. Attention Modulates Spatio-temporal Grouping

    PubMed Central

    Ayd?n, Murat; Herzog, Michael H.; ?men, Haluk

    2011-01-01

    Dynamic stimuli are ubiquitous in natural viewing conditions implying that grouping operations need to operate, not only in space, but also jointly in space and time. Moreover, in natural viewing, attention plays an important role in controlling how resources are allocated. We investigated how attention interacts with spatiotemporal perceptual grouping by using a bistable stimulus, called the Ternus-Pikler display. Ternus-Pikler displays can give rise to two different motion percepts, called Element Motion (EM) and Group Motion (GM), the former dominating at short Inter-Stimulus Intervals (ISIs) and the latter at long ISIs. Our results indicate that GM grouping requires more attentional resources than EM grouping. Different theoretical accounts of perceptual grouping and attention are discussed and evaluated in the light of the current results. PMID:21266181

  19. Spatiotemporal dynamics of counterpropagating Airy beams

    PubMed Central

    Wiersma, Noémi; Marsal, Nicolas; Sciamanna, Marc; Wolfersberger, Delphine

    2015-01-01

    We analyse theoretically the spatiotemporal dynamics of two incoherent counterpropagating Airy beams interacting in a photorefractive crystal under focusing conditions. For a large enough nonlinearity strength the interaction between the two Airy beams leads to light-induced waveguiding. The stability of the waveguide is determined by the crystal length, the nonlinearity strength and the beam’s intensities and is improved when comparing to the situation using Gaussian beams. We further identify the threshold above which the waveguide is no longer static but evolves dynamically either time-periodically or even chaotically. Above the stability threshold, each Airy-soliton moves erratically between privileged output positions that correspond to the spatial positions of the lobes of the counterpropagating Airy beam. These results suggest new ways of creating dynamically varying waveguides, optical logic gates and chaos-based computing. PMID:26315530

  20. Secure communication based on spatiotemporal chaos

    NASA Astrophysics Data System (ADS)

    Ren, Hai-Peng; Bai, Chao

    2015-08-01

    In this paper, we propose a novel approach to secure communication based on spatiotemporal chaos. At the transmitter end, the state variables of the coupled map lattice system are divided into two groups: one is used as the key to encrypt the plaintext in the N-shift encryption function, and the other is used to mix with the output of the N-shift function to further confuse the information to transmit. At the receiver end, the receiver lattices are driven by the received signal to synchronize with the transmitter lattices and an inverse procedure of the encoding is conducted to decode the information. Numerical simulation and experiment based on the TI TMS320C6713 Digital Signal Processor (DSP) show the feasibility and the validity of the proposed scheme. Project supported by the National Natural Science Foundation of China (Grant No. 61172070) and the Funds from the Science and Technology Innovation Team of Shaanxi Province, China (Grant No. 2013CKT-04).

  1. Nonlinear Synchronization Analysis of Spatiotemporal Heart Data

    NASA Astrophysics Data System (ADS)

    Simonotto, Jennifer D.; Furman, Michael D.; Spano, Mark L.; Ditto, William L.; Liu, Gang; Kavanagh, Katherine M.

    2003-08-01

    A high-speed video camera and voltage-sensitive dyes were used to acquire high resolution (80×80 pixels) and high-speed (500 μs/frame) optical signals of ventricular fibrillation in a Langendorff-perfused porcine heart. The resulting spatiotemporal dynamics were recorded before and after the application of a defibrillation shock in order to study the mechanism of defibrillation failure. We calculate nonlinear synchronization index measures to qualify the evolution of different types of activity on the heart surface (focal, reentry). We observe changes with time in the spatial distribution of the first Fourier mode, showing that two main types of activity compete on the heart surface during a failed defibrillation.

  2. Spatio-temporal properties of letter crowding.

    PubMed

    Chung, Susana T L

    2016-04-01

    Crowding between adjacent letters has been investigated primarily as a spatial effect. The purpose of this study was to investigate the spatio-temporal properties of letter crowding. Specifically, we examined the systematic changes in the degradation effects in letter identification performance when adjacent letters were presented with a temporal asynchrony, as a function of letter separation and between the fovea and the periphery. We measured proportion-correct performance for identifying the middle target letter in strings of three lowercase letters at the fovea and 10° in the inferior visual field, for a range of center-to-center letter separations and a range of stimulus onset asynchronies (SOA) between the target and flanking letters (positive SOAs: target preceded flankers). As expected, the accuracy for identifying the target letters reduces with decreases in letter separation. This crowding effect shows a strong dependency on SOAs, such that crowding is maximal between 0 and ∼100 ms (depending on conditions) and diminishes for larger SOAs (positive or negative). Maximal crowding does not require the target and flanking letters to physically coexist for the entire presentation duration. Most importantly, crowding can be minimized even for closely spaced letters if there is a large temporal asynchrony between the target and flankers. The reliance of letter identification performance on SOAs and how it changes with letter separations imply that the crowding effect can be traded between space and time. Our findings are consistent with the notion that crowding should be considered as a spatio-temporal, and not simply a spatial, effect. PMID:27088895

  3. Spatiotemporal complexity of the aortic sinus vortex

    NASA Astrophysics Data System (ADS)

    Moore, Brandon; Dasi, Lakshmi Prasad

    2014-07-01

    The aortic sinus vortex is a classical flow structure of significant importance to aortic valve dynamics and the initiation and progression of calcific aortic valve disease. We characterize the spatiotemporal characteristics of aortic sinus vortex dynamics in relation to the viscosity of blood analog solution as well as heart rate. High-resolution time-resolved (2 kHz) particle image velocimetry was conducted to capture 2D particle streak videos and 2D instantaneous velocity and streamlines along the sinus midplane using a physiological but rigid aorta model fitted with a porcine bioprosthetic heart valve. Blood analog fluids used include a water-glycerin mixture and saline to elucidate the sensitivity of vortex dynamics to viscosity. Experiments were conducted to record 10 heart beats for each combination of blood analog and heart rate condition. Results show that the topological characteristics of the velocity field vary in timescales as revealed using time bin-averaged vectors and corresponding instantaneous streamlines. There exist small timescale vortices and a large timescale main vortex. A key flow structure observed is the counter vortex at the upstream end of the sinus adjacent to the base (lower half) of the leaflet. The spatiotemporal complexity of vortex dynamics is shown to be profoundly influenced by strong leaflet flutter during systole with a peak frequency of 200 Hz and peak amplitude of 4 mm observed in the saline case. While fluid viscosity influences the length and timescales as well as the introduction of leaflet flutter, heart rate influences the formation of counter vortex at the upstream end of the sinus. Higher heart rates are shown to reduce the strength of the counter vortex that can greatly influence the directionality and strength of shear stresses along the base of the leaflet. This study demonstrates the impact of heart rate and blood analog viscosity on aortic sinus hemodynamics.

  4. Spatiotemporal analysis of snow trends in Austria

    NASA Astrophysics Data System (ADS)

    Koch, Roland; Schöner, Wolfgang

    2015-04-01

    This study presents the spatiotemporal analysis of Austrian snow observations. A set of consistent and reliable long-term time series of snow depth on a daily scale from selected meteorological sites across Austria is used. The time series were collected by the Central Institute for Meteorology and Geodynamics (ZAMG) and the Hydrographical Central Bureau of Austria (HZB). The data cover a time period from the late nineteenth century until today. In the first part of the study spatiotemporal characteristics of seasonal snow depth observations were investigated by the method of principal component analysis (PCA). Furthermore, the spatial patterns of variability have been used for a regionalisation, identifying regions with similar conditions during the base period 1961 to 2010. The results show a clear separation of four major regions including various sub-regions. However, the regionalisation was limited due to sparse data coverage. The non-parametric Mann-Kendall statistical test had been used to assess the significance of trends in snow indices, e.g. snow depth, maximum snow depth, snow cover duration, at monthly and seasonal time scales. In order to remove the influence of the lag-1 serial correlation from the snow data, the trend-free pre-whitening approach was applied. In the monthly and seasonal time series during the period 1961-2010, negative trends in snow indices were significant at the 95% confidence level primarily at stations in the Western and Southern part of Austria. In addition, the correlation between snow observations and gridded HISTALP winter temperature and precipitation fields was investigated. The analysis has shown an increased temperature and decreased precipitation during the 1990s, yielding a pronounced reduction in snow depth and duration. As a matter of fact, the results indicate major shifts of the snow depth and snow cover duration around the 1970s and especially the 1990s, which are predominantly responsible for trends.

  5. Systemic risk and spatiotemporal dynamics of the US housing market

    NASA Astrophysics Data System (ADS)

    Meng, Hao; Xie, Wen-Jie; Jiang, Zhi-Qiang; Podobnik, Boris; Zhou, Wei-Xing; Stanley, H. Eugene

    2014-01-01

    Housing markets play a crucial role in economies and the collapse of a real-estate bubble usually destabilizes the financial system and causes economic recessions. We investigate the systemic risk and spatiotemporal dynamics of the US housing market (1975-2011) at the state level based on the Random Matrix Theory (RMT). We identify richer economic information in the largest eigenvalues deviating from RMT predictions for the housing market than for stock markets and find that the component signs of the eigenvectors contain either geographical information or the extent of differences in house price growth rates or both. By looking at the evolution of different quantities such as eigenvalues and eigenvectors, we find that the US housing market experienced six different regimes, which is consistent with the evolution of state clusters identified by the box clustering algorithm and the consensus clustering algorithm on the partial correlation matrices. We find that dramatic increases in the systemic risk are usually accompanied by regime shifts, which provide a means of early detection of housing bubbles.

  6. Systemic risk and spatiotemporal dynamics of the US housing market.

    PubMed

    Meng, Hao; Xie, Wen-Jie; Jiang, Zhi-Qiang; Podobnik, Boris; Zhou, Wei-Xing; Stanley, H Eugene

    2014-01-01

    Housing markets play a crucial role in economies and the collapse of a real-estate bubble usually destabilizes the financial system and causes economic recessions. We investigate the systemic risk and spatiotemporal dynamics of the US housing market (1975-2011) at the state level based on the Random Matrix Theory (RMT). We identify richer economic information in the largest eigenvalues deviating from RMT predictions for the housing market than for stock markets and find that the component signs of the eigenvectors contain either geographical information or the extent of differences in house price growth rates or both. By looking at the evolution of different quantities such as eigenvalues and eigenvectors, we find that the US housing market experienced six different regimes, which is consistent with the evolution of state clusters identified by the box clustering algorithm and the consensus clustering algorithm on the partial correlation matrices. We find that dramatic increases in the systemic risk are usually accompanied by regime shifts, which provide a means of early detection of housing bubbles. PMID:24413626

  7. Spatiotemporal characteristics of soil temperature memory in China from observation

    NASA Astrophysics Data System (ADS)

    Yang, Kai; Zhang, Jingyong

    2015-08-01

    Similar to soil moisture, soil temperature has a memory of atmospheric anomalies. However, soil temperature memory over China is still largely unclear, especially in observation. In this study, we investigate the spatiotemporal characteristics of soil temperature memory over China using subsurface (10-80 cm) and deep (160-320 cm) soil temperature data for 626 stations during the period of 1981 to 2005. The red noise method is adopted to estimate soil temperature memory. Results show that the soil temperature memory differs spatially and varies with soil depth and season. Influenced by climate regimes, soil temperature memory at all six layers (with depths of 10, 20, 40, 80, 160, and 320 cm) shows a similar spatial pattern dominated by a northwest to southeast gradient, with relatively high values over arid and semiarid areas of northwestern part of China and relatively low values over humid and semihumid areas of southeastern part of China. During all four seasons, memory lengths increase with soil depth. The average memory of subsurface soil over China can last several months, and for soil at 320 cm, it can be 1 year or more. We also find that seasonal and regional differences of soil temperature memory are stronger in deep soil layers than those in subsurface soil layers. Our findings suggest that soil temperature memory can offer potential for improving seasonal climate prediction over northwestern China. In the meanwhile, the limitations of the methods used in this study should be recognized.

  8. Systemic risk and spatiotemporal dynamics of the US housing market

    PubMed Central

    Meng, Hao; Xie, Wen-Jie; Jiang, Zhi-Qiang; Podobnik, Boris; Zhou, Wei-Xing; Stanley, H. Eugene

    2014-01-01

    Housing markets play a crucial role in economies and the collapse of a real-estate bubble usually destabilizes the financial system and causes economic recessions. We investigate the systemic risk and spatiotemporal dynamics of the US housing market (1975–2011) at the state level based on the Random Matrix Theory (RMT). We identify richer economic information in the largest eigenvalues deviating from RMT predictions for the housing market than for stock markets and find that the component signs of the eigenvectors contain either geographical information or the extent of differences in house price growth rates or both. By looking at the evolution of different quantities such as eigenvalues and eigenvectors, we find that the US housing market experienced six different regimes, which is consistent with the evolution of state clusters identified by the box clustering algorithm and the consensus clustering algorithm on the partial correlation matrices. We find that dramatic increases in the systemic risk are usually accompanied by regime shifts, which provide a means of early detection of housing bubbles. PMID:24413626

  9. Emergence of spatiotemporal dislocation chains in drifting patterns.

    PubMed

    Clerc, M G; Falcón, C; García-Ñustes, M A; Odent, V; Ortega, I

    2014-06-01

    One-dimensional patterns subjected to counter-propagative flows or speed jumps exhibit a rich and complex spatiotemporal dynamics, which is characterized by the perpetual emergence of spatiotemporal dislocation chains. Using a universal amplitude equation of drifting patterns, we show that this behavior is a result of a combination of a phase instability and an advection process caused by an inhomogeneous drift force. The emergence of spatiotemporal dislocation chains is verified in numerical simulations on an optical feedback system with a non-uniform intensity pump. Experimentally this phenomenon is also observed in a tilted quasi-one-dimensional fluidized shallow granular bed mechanically driven by a harmonic vertical vibration. PMID:24985447

  10. The spatiotemporal structure of control variables during catching.

    PubMed

    Polman, R C; Whiting, H T; Savelsbergh, G J

    1996-06-01

    The discrepancy between traditional (force scaling models) and the more recently conceived dynamic explanations of load compensation (lambda model) was the departure point for the present study. By using the complex "open" motor skill of catching a ball--rather than the traditional "closed" skills--under "normal" (baseline) conditions and under conditions where a spring load was applied to the catching hand (thereby changing the dynamics of the skeletomuscular system) it was hoped to provide further clarification of this issue. Traditional force scaling models, in this respect, would predict that maximal closing velocity of the grasp action, and movement time would not be significantly different between a control and a spring-load condition. In contrast, a dynamic system perspective would maintain that spring loading would be compensated for by a change in the rate of shift of the reciprocal command (R-command). The obtained results showed a significant difference for conditions with regard to the maximal closing velocity of the grasp action, the baseline condition being higher than the two spring-load conditions. Furthermore, a significant difference was found for the aperture at moment of catch, the aperture at moment of catch being smaller in the baseline condition than that under the two spring-load conditions. With regard to the temporal variables, no significant differences were obtained. A comprehensive overall explanation of the obtained data in terms of the force scaling models was not realisable. It may be that findings supporting such theories are task specific and that for constrained tasks--such as catching a ball--different underlying organisational principles apply. The lambda model, however, could explain adequately the obtained results. It was concluded that, except for the preparatory phase associated with load compensation before the onset of the movement of the ball, the spatiotemporal structure of the control pattern underlying catching remains the same (invariant) in both baseline and load conditions. Thereby, the spatiotemporal structure of the resulting movement changes under the influence of the load and thus is not the same for load and baseline condition. PMID:8817279

  11. Ambient Air Pollution and Preeclampsia: A Spatiotemporal Analysis

    PubMed Central

    Figueras, Francesc; Basagaña, Xavier; Beelen, Rob; Martinez, David; Cirach, Marta; Schembari, Anna; Hoek, Gerard; Brunekreef, Bert; Nieuwenhuijsen, Mark J

    2013-01-01

    Background: Available evidence concerning the association between air pollution and preeclampsia is limited, and specific associations with early- and late-onset preeclampsia have not been assessed. Objectives: We investigated the association, if any, between preeclampsia (all, early-, and late-onset) and exposure to nitrogen dioxide, nitrogen oxides, particulate matter with aerodynamic diameter ≤ 2.5 μm (PM2.5; fine particles), ≤ 10 μm, and 2.5–10 μm, and PM2.5 light absorption (a proxy for elemental carbon) during the entire pregnancy and during the first, second, and third trimesters. Methods: This study was based on 8,398 pregnancies (including 103 cases of preeclampsia) among women residing in Barcelona, Spain (2000–2005). We applied a spatiotemporal exposure assessment framework using land use regression models to predict ambient pollutant levels during each week of pregnancy at the geocoded residence address of each woman at the time of birth. Logistic and conditional logistic regression models were used to estimate unadjusted and adjusted associations. Results: We found positive associations for most of our evaluated outcome–exposure pairs, with the strongest associations observed for preeclampsia and late-onset preeclampsia in relation to the third-trimester exposure to fine particulate pollutants, and for early-onset preeclampsia in relation to the first-trimester exposure to fine particulate pollutants. Among our investigated associations, those of first- and third-trimester exposures to PM2.5 and third-trimester exposure to PM2.5 absorbance and all preeclampsia, and third-trimester PM2.5 exposure and late-onset preeclampsia attained statistical significance. Conclusion: We observed increased risk of preeclampsia associated with exposure to fine particulate air pollution. Our findings, in combination with previous evidence suggesting distinct pathogenic mechanisms for early- and late-onset preeclampsia, support additional research on this topic. Citation: Dadvand P, Figueras F, Basagaña X, Beelen R, Martinez D, Cirach M, Schembari A, Hoek G, Brunekreef B, Nieuwenhuijsen MJ. 2013. Ambient air pollution and preeclampsia: a spatiotemporal analysis. Environ Health Perspect 121:1365–1371; http://dx.doi.org/10.1289/ehp.1206430 PMID:24021707

  12. Analysis of the Rab GTPase Interactome in Dendritic Cells Reveals Anti-microbial Functions of the Rab32 Complex in Bacterial Containment.

    PubMed

    Li, Yuanyuan; Wang, Yu; Zou, Liyun; Tang, Xiangyu; Yang, Yi; Ma, Li; Jia, Qingzhu; Ni, Qingshan; Liu, Siqi; Tang, Lizhang; Lin, Regina; Wong, Elizabeth; Sun, Wei; Wang, Liting; Wei, Quanfang; Ran, Haiying; Zhang, Liqun; Lian, Hengning; Huang, Wei; Wu, Yuzhang; Li, Qi-Jing; Wan, Ying

    2016-02-16

    Dendritic cells (DCs) orchestrate complex membrane trafficking through an interconnected transportation network linked together by Rab GTPases. Through a tandem affinity purification strategy and mass spectrometry, we depicted an interactomic landscape of major members of the mammalian Rab GTPase family. When complemented with imaging tools, this proteomic analysis provided a global view of intracellular membrane organization. Driven by this analysis, we investigated dynamic changes to the Rab32 subnetwork in DCs induced by L. monocytogenes infection and uncovered an essential role of this subnetwork in controlling the intracellular proliferation of L. monocytogenes. Mechanistically, Rab32 formed a persistent complex with two interacting proteins, PHB and PHB2, to encompass bacteria both during early phagosome formation and after L. monocytogenes escaped the original containment vacuole. Collectively, we have provided a functional compartmentalization overview and an organizational framework of intracellular Rab-mediated vesicle trafficking that can serve as a resource for future investigations. PMID:26885862

  13. The nuclear basket proteins Mlp1p and Mlp2p are part of a dynamic interactome including Esc1p and the proteasome

    PubMed Central

    Niepel, Mario; Molloy, Kelly R.; Williams, Rosemary; Farr, Julia C.; Meinema, Anne C.; Vecchietti, Nicholas; Cristea, Ileana M.; Chait, Brian T.; Rout, Michael P.; Strambio-De-Castillia, Caterina

    2013-01-01

    The basket of the nuclear pore complex (NPC) is generally depicted as a discrete structure of eight protein filaments that protrude into the nucleoplasm and converge in a ring distal to the NPC. We show that the yeast proteins Mlp1p and Mlp2p are necessary components of the nuclear basket and that they also embed the NPC within a dynamic protein network, whose extended interactome includes the spindle organizer, silencing factors, the proteasome, and key components of messenger ribonucleoproteins (mRNPs). Ultrastructural observations indicate that the basket reduces chromatin crowding around the central transporter of the NPC and might function as a docking site for mRNP during nuclear export. In addition, we show that the Mlps contribute to NPC positioning, nuclear stability, and nuclear envelope morphology. Our results suggest that the Mlps are multifunctional proteins linking the nuclear transport channel to multiple macromolecular complexes involved in the regulation of gene expression and chromatin maintenance. PMID:24152732

  14. The use of spatio-temporal correlation to forecast critical transitions

    NASA Astrophysics Data System (ADS)

    Karssenberg, Derek; Bierkens, Marc F. P.

    2010-05-01

    Complex dynamical systems may have critical thresholds at which the system shifts abruptly from one state to another. Such critical transitions have been observed in systems ranging from the human body system to financial markets and the Earth system. Forecasting the timing of critical transitions before they are reached is of paramount importance because critical transitions are associated with a large shift in dynamical regime of the system under consideration. However, it is hard to forecast critical transitions, because the state of the system shows relatively little change before the threshold is reached. Recently, it was shown that increased spatio-temporal autocorrelation and variance can serve as alternative early warning signal for critical transitions. However, thus far these second order statistics have not been used for forecasting in a data assimilation framework. Here we show that the use of spatio-temporal autocorrelation and variance in the state of the system reduces the uncertainty in the predicted timing of critical transitions compared to classical approaches that use the value of the system state only. This is shown by assimilating observed spatio-temporal autocorrelation and variance into a dynamical system model using a Particle Filter. We adapt a well-studied distributed model of a logistically growing resource with a fixed grazing rate. The model describes the transition from an underexploited system with high resource biomass to overexploitation as grazing pressure crosses the critical threshold, which is a fold bifurcation. To represent limited prior information, we use a large variance in the prior probability distributions of model parameters and the system driver (grazing rate). First, we show that the rate of increase in spatio-temporal autocorrelation and variance prior to reaching the critical threshold is relatively consistent across the uncertainty range of the driver and parameter values used. This indicates that an increase in spatio-temporal autocorrelation and variance are consistent predictors of a critical transition, even under the condition of a poorly defined system. Second, we perform data assimilation experiments using an artificial exhaustive data set generated by one realization of the model. To mimic real-world sampling, an observational data set is created from this exhaustive data set. This is done by sampling on a regular spatio-temporal grid, supplemented by sampling locations at a short distance. Spatial and temporal autocorrelation in this observational data set is calculated for different spatial and temporal separation (lag) distances. To assign appropriate weights to observations (here, autocorrelation values and variance) in the Particle Filter, the covariance matrix of the error in these observations is required. This covariance matrix is estimated using Monte Carlo sampling, selecting a different random position of the sampling network relative to the exhaustive data set for each realization. At each update moment in the Particle Filter, observed autocorrelation values are assimilated into the model and the state of the model is updated. Using this approach, it is shown that the use of autocorrelation reduces the uncertainty in the forecasted timing of a critical transition compared to runs without data assimilation. The performance of the use of spatial autocorrelation versus temporal autocorrelation depends on the timing and number of observational data. This study is restricted to a single model only. However, it is becoming increasingly clear that spatio-temporal autocorrelation and variance can be used as early warning signals for a large number of systems. Thus, it is expected that spatio-temporal autocorrelation and variance are valuable in data assimilation frameworks in a large number of dynamical systems.

  15. Using atmospheric observations to evaluate the spatiotemporal variability of CO2 fluxes simulated by terrestrial biospheric models

    NASA Astrophysics Data System (ADS)

    Fang, Y.; Michalak, A. M.; Shiga, Y. P.; Yadav, V.

    2014-12-01

    Terrestrial biospheric models (TBMs) are used to extrapolate local observations and process-level understanding of land-atmosphere carbon exchange to larger regions, and serve as predictive tools for examining carbon-climate interactions. Understanding the performance of TBMs is thus crucial to the carbon cycle and climate science communities. In this study, we present and assess an approach to evaluating the spatiotemporal patterns, rather than aggregated magnitudes, of net ecosystem exchange (NEE) simulated by TBMs using atmospheric CO2 measurements. The approach is based on statistical model selection implemented within a high-resolution atmospheric inverse model. Using synthetic data experiments, we find that current atmospheric observations are sensitive to the underlying spatiotemporal flux variability at sub-biome scales for a large portion of North America, and that atmospheric observations can therefore be used to evaluate simulated spatiotemporal flux patterns as well as to differentiate between multiple competing TBMs. Experiments using real atmospheric observations and four prototypical TBMs further confirm the applicability of the method, and demonstrate that the performance of TBMs in simulating the spatiotemporal patterns of NEE varies substantially across seasons, with best performance during the growing season and more limited skill during transition seasons. This result is consistent with previous work showing that the ability of TBMs to model flux magnitudes is also seasonally-dependent. Overall, the proposed approach provides a new avenue for evaluating TBM performance based on sub-biome-scale flux patterns, presenting an opportunity for assessing and informing model development using atmospheric observations.

  16. Spatiotemporal symmetry in rings of coupled biological oscillators of Physarum plasmodial slime mold.

    PubMed

    Takamatsu, A; Tanaka, R; Yamada, H; Nakagaki, T; Fujii, T; Endo, I

    2001-08-13

    Spatiotemporal patterns in rings of coupled biological oscillators of the plasmodial slime mold, Physarum polycephalum, were investigated by comparing with results analyzed by the symmetric Hopf bifurcation theory based on group theory. In three-, four-, and five-oscillator systems, all types of oscillation modes predicted by the theory were observed including a novel oscillation mode, a half period oscillation, which has not been reported anywhere in practical systems. Our results support the effectiveness of the symmetric Hopf bifurcation theory in practical systems. PMID:11497921

  17. Faster P300 Classifier Training Using Spatiotemporal Beamforming.

    PubMed

    Wittevrongel, Benjamin; Van Hulle, Marc M

    2016-05-01

    The linearly-constrained minimum-variance (LCMV) beamformer is traditionally used as a spatial filter for source localization, but here we consider its spatiotemporal extension for P300 classification. We compare two variants and show that the spatiotemporal LCMV beamformer is at par with state-of-the-art P300 classifiers, but several orders of magnitude faster in training the classifier. PMID:26971787

  18. Different routes from a matter wavepacket to spatiotemporal chaos

    SciTech Connect

    Rong Shiguang; Hai Wenhua; Xie Qiongtao; Zhong Honghua

    2012-09-15

    We investigate the dynamics of a quasi-one-dimensional Bose-Einstein condensate confined in a double-well potential with spatiotemporally modulated interaction. A variety of phenomena is identified in different frequency regimes, including the self-compression, splitting, breathing-like, and near-fidelity of the matter wavepacket, which are associated with different routes for the onset of spatiotemporal chaos. The results also reveal that chaos can retain space-inversion symmetry of the system.

  19. Regionalised spatiotemporal rainfall and temperature models for flood studies in the Basque Country, Spain

    NASA Astrophysics Data System (ADS)

    Cowpertwait, P.; Ocio, D.; Collazos, G.; de Cos, O.; Stocker, C.

    2013-02-01

    A spatiotemporal point process model of rainfall is fitted to data taken from three homogeneous regions in the Basque Country, Spain. The model is the superposition of two spatiotemporal Neyman-Scott processes, in which rain cells are modelled as discs with radii that follow exponential distributions. In addition, the model includes a parameter for the radius of storm discs, so that rain only occurs when both a cell and a storm disc overlap a point. The model is fitted to data for each month, taken from each of the three homogeneous regions, using a modified method of moments procedure that ensures a smooth seasonal variation in the parameter estimates. Daily temperature data from 23 sites are used to fit a stochastic temperature model. A principal component analysis of the maximum daily temperatures across the sites indicates that 92% of the variance is explained by the first component, implying that this component can be used to account for spatial variation. A harmonic equation with autoregressive error terms is fitted to the first principal component. The temperature model is obtained by regressing the maximum daily temperature on the first principal component, an indicator variable for the region, and altitude. This, together with scaling and a regression model of temperature range, enables hourly temperatures to be predicted. Rainfall is included as an explanatory variable but has only a marginal influence when predicting temperatures. A distributed model (TETIS; Francés et al., 2007) is calibrated for a selected catchment. Five hundred years of data are simulated using the rainfall and temperature models and used as input to the calibrated TETIS model to obtain simulated discharges to compare with observed discharges. Kolmogorov-Smirnov tests indicate that there is no significant difference in the distributions of observed and simulated maximum flows at the same sites, thus supporting the use of the spatiotemporal models for the intended application.

  20. Spatiotemporal characteristics of cusp latitude spectra

    NASA Astrophysics Data System (ADS)

    Szuberla, Curt A. L.; Olson, John V.; Engebretson, Mark J.; McHarg, M. Geoff; Hughes, W. Jeffrey

    2000-04-01

    In this study we analyze the spatiotemporal characteristics of spectra generated from 754 days of cusp latitude magnetometer data (Longyearbyen and selected Magnetometer Array for Cusp and Cleft Studies (MACCS) stations). In order to distinguish between the presence of spatial (fixed in magnetic local time) and temporal (fixed in universal time) signatures in cusp latitude spectra we develop a simple test using trace power, polarization, and ellipticity spectra. On the basis of this test we find evidence for both spatial and temporal signatures in cusp latitude spectra. We find that the trace power spectrum is dominated by temporal information; however, the polarization and ellipticity spectra contain unambiguous spatial structure. Temporal information in cusp latitude spectra is carried primarily by broadband Pc3 (10-50 mHz) noise, while spatial information is carried by polarized Pc5 (1-10 mHz) pulsations. Additionally, we establish a state-space measure as a quantitative means of discriminating the spatial passage of the cusp and boundary regions by ground-based magnetic means. The measure is based on the difference between daily polarization spectra (centered on local magnetic noon) and the mean polarization spectra for a given station. This procedure replaces previous determinations which were made from spectra ``by-eye.''

  1. Automatic spatiotemporal matching of detected pleural thickenings

    NASA Astrophysics Data System (ADS)

    Chaisaowong, Kraisorn; Keller, Simon Kai; Kraus, Thomas

    2014-01-01

    Pleural thickenings can be found in asbestos exposed patient's lung. Non-invasive diagnosis including CT imaging can detect aggressive malignant pleural mesothelioma in its early stage. In order to create a quantitative documentation of automatic detected pleural thickenings over time, the differences in volume and thickness of the detected thickenings have to be calculated. Physicians usually estimate the change of each thickening via visual comparison which provides neither quantitative nor qualitative measures. In this work, automatic spatiotemporal matching techniques of the detected pleural thickenings at two points of time based on the semi-automatic registration have been developed, implemented, and tested so that the same thickening can be compared fully automatically. As result, the application of the mapping technique using the principal components analysis turns out to be advantageous than the feature-based mapping using centroid and mean Hounsfield Units of each thickening, since the resulting sensitivity was improved to 98.46% from 42.19%, while the accuracy of feature-based mapping is only slightly higher (84.38% to 76.19%).

  2. Spatiotemporal video deinterlacing using control grid interpolation

    NASA Astrophysics Data System (ADS)

    Venkatesan, Ragav; Zwart, Christine M.; Frakes, David H.; Li, Baoxin

    2015-03-01

    With the advent of progressive format display and broadcast technologies, video deinterlacing has become an important video-processing technique. Numerous approaches exist in the literature to accomplish deinterlacing. While most earlier methods were simple linear filtering-based approaches, the emergence of faster computing technologies and even dedicated video-processing hardware in display units has allowed higher quality but also more computationally intense deinterlacing algorithms to become practical. Most modern approaches analyze motion and content in video to select different deinterlacing methods for various spatiotemporal regions. We introduce a family of deinterlacers that employs spectral residue to choose between and weight control grid interpolation based spatial and temporal deinterlacing methods. The proposed approaches perform better than the prior state-of-the-art based on peak signal-to-noise ratio, other visual quality metrics, and simple perception-based subjective evaluations conducted by human viewers. We further study the advantages of using soft and hard decision thresholds on the visual performance.

  3. Multisensory control of hippocampal spatiotemporal selectivity.

    PubMed

    Ravassard, Pascal; Kees, Ashley; Willers, Bernard; Ho, David; Aharoni, Daniel; Cushman, Jesse; Aghajan, Zahra M; Mehta, Mayank R

    2013-06-14

    The hippocampal cognitive map is thought to be driven by distal visual cues and self-motion cues. However, other sensory cues also influence place cells. Hence, we measured rat hippocampal activity in virtual reality (VR), where only distal visual and nonvestibular self-motion cues provided spatial information, and in the real world (RW). In VR, place cells showed robust spatial selectivity; however, only 20% were track active, compared with 45% in the RW. This indicates that distal visual and nonvestibular self-motion cues are sufficient to provide selectivity, but vestibular and other sensory cues present in RW are necessary to fully activate the place-cell population. In addition, bidirectional cells preferentially encoded distance along the track in VR, while encoding absolute position in RW. Taken together, these results suggest the differential contributions of these sensory cues in shaping the hippocampal population code. Theta frequency was reduced, and its speed dependence was abolished in VR, but phase precession was unaffected, constraining mechanisms governing both hippocampal theta oscillations and temporal coding. These results reveal cooperative and competitive interactions between sensory cues for control over hippocampal spatiotemporal selectivity and theta rhythm. PMID:23641063

  4. 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. PMID:25247712

  5. 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 Central

    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 funtional 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. PMID:25247712

  6. Spatio-temporal change modeling with array data

    NASA Astrophysics Data System (ADS)

    Lu, Meng; Pebesma, Edzer

    2015-04-01

    Spatio-temporal change modeling of our ecosystems is critical for environmental conservation. Open access to remote sensing satellite image archives provides new opportunities for change modeling, such as near real-time change monitoring with long term image time series. Newly developed time series analysis methods allow the detection of quantitative changes in trend and seasonality for each pixel of the image. A drawback of pure time series analysis is that spatial dependence is neglected. There are several spatio-temporal statistical approaches to incorporate spatial context. One method is to build hierarchical models with spatial effects for time series parameters. Other methods include representing regression parameters as spatially correlated random fields, or integrating spatial autoregressive models to time series analysis. Apart from spatio-temporal statistical modeling, the results can be further improved by qualification of detected change points with their spatio-temporal neighbors. Spatio-temporal modeling approaches are typically complex and large in scale, and call for new data management and analysis tools. Remote sensing satellite images, which are continuous and regular in space and time, can naturally be represented as three- or four-dimensional arrays for spatio-temporal data management and analysis. The developed spatio-temporal statistical algorithms can be flexibly applied within array partitions that span the relevant array-based dimensions. This study investigates the potential of array-based Data Data Management and Analytic Software (DMAS) for fast data access, data integration and large-scale complex spatio-temporal analysis. A study case is developed in near-real time deforestation monitoring in Amazonian rainforest with long-term 250 m, 8-day resolution MODIS image time series. A novel spatio-temporal change modeling process is being developed and implemented in DMAS to realize rapid and automated analysis of satellite image time series for forest disturbance detection. The study expects results that improve over a pure time series analysis approach, and that is practically applicable to massive complex spatio-temporal data.

  7. Autophagy-related gene 12 (ATG12) is a novel determinant of primary resistance to HER2-targeted therapies: Utility of transcriptome analysis of the autophagy interactome to guide breast cancer treatment

    PubMed Central

    Corominas-Faja, Bruna; Urruticoechea, Ander; Martin-Castillo, Begoña; Menendez, Javier A.

    2012-01-01

    The autophagic process, which can facilitate breast cancer resistance to endocrine, cytotoxic, and molecularly targeted agents, is mainly regulated at the post-translational level. Although recent studies have suggested a possible transcriptome regulation of the autophagic genes, little is known about either the analysis tools that can be applied or the functional importance of putative candidate genes emerging from autophagy-dedicated transcriptome studies. In this context, we evaluated whether the constitutive activation of the autophagy machinery, as revealed by a transcriptome analysis using an autophagy-focused polymerase chain reaction (PCR) array, might allow for the identification of novel autophagy-specific biomarkers for intrinsic (primary) resistance to HER2-targeted therapies. Quantitative real-time PCR (qRT-PCR)-based profiling of 84 genes involved in autophagy revealed that, when compared to trastuzumab-sensitive SKBR3 cells, the positive regulator of autophagic vesicle formation ATG12 (autophagy-related gene 12) was the most differentially up-regulated gene in JIMT1 cells, a model of intrinsic cross-resistance to trastuzumab and other HER1/2-targeting drugs. An analysis of the transcriptional status of ATG12 in > 50 breast cancer cell lines suggested that the ATG12 transcript is commonly upregulated in trastuzumab-unresponsive HER2-overexpressing breast cancer cells. A lentiviral-delivered small hairpin RNA stable knockdown of the ATG12 gene fully suppressed the refractoriness of JIMT1 cells to trastuzumab, erlotinib, gefitinib, and lapatinib in vitro. ATG12 silencing significantly reduced JIMT1 tumor growth induced by subcutaneous injection in nude mice. Remarkably, the outgrowth of trastuzumab-unresponsive tumors was prevented completely when trastuzumab treatment was administered in an ATG12-silenced genetic background. We demonstrate for the first time the usefulness of low-density, autophagy-dedicated qRT-PCR-based platforms for monitoring primary resistance to HER2-targeted therapies by transcriptionally screening the autophagy interactome. The degree of predictive accuracy warrants further investigation in the clinical situation. PMID:23307622

  8. Spatiotemporal patterns of induced resistance and susceptibility linking diverse plant parasites.

    PubMed

    Mouttet, Raphaëlle; Kaplan, Ian; Bearez, Philippe; Amiens-Desneux, Edwige; Desneux, Nicolas

    2013-12-01

    Induced defenses mediate interactions between parasites sharing the same host plant, but the outcomes of these interactions are challenging to predict because of spatiotemporal variation in plant responses and differences in defense pathways elicited by herbivores or pathogens. Dissecting these mediating factors necessitates an approach that encompasses a diversity of parasitic feeding styles and tracks interactions over space and time. We tested indirect plant-mediated relationships across three tomato (Solanum lycopersicum) consumers: (1) the fungal pathogen-powdery mildew, Oidium neolycopersici; (2) a sap-feeding insect-silverleaf whitefly, Bemisia tabaci; and (3) a chewing insect-the leaf miner, Tuta absoluta. Further, we evaluated insect/pathogen responses on local vs. systemic leaves and over short (1 day) vs. long (4 days) time scales. Overall, we documented: (1) a bi-directional negative effect between O. neolycopersici and B. tabaci; (2) an asymmetrical negative effect of B. tabaci on T. absoluta; and (3) an asymmetrical positive effect of T. absoluta on O. neolycopersici. Spatiotemporal patterns varied depending on the species pair (e.g., whitefly effects on leaf miner performance were highly localized to the induced leaf, whereas effects on pathogen growth were both local and systemic). These results highlight the context-dependent effects of induced defenses on a diverse community of tomato parasites. Notably, the outcomes correspond to those predicted by phytohormonal theory based on feeding guild differences with key implications for the recent European invasion by T. absoluta. PMID:23851986

  9. Spatio-Temporal Dynamics of Hypoxia during Radiotherapy

    PubMed Central

    Kempf, Harald; Bleicher, Marcus; Meyer-Hermann, Michael

    2015-01-01

    Tumour hypoxia plays a pivotal role in cancer therapy for most therapeutic approaches from radiotherapy to immunotherapy. The detailed and accurate knowledge of the oxygen distribution in a tumour is necessary in order to determine the right treatment strategy. Still, due to the limited spatial and temporal resolution of imaging methods as well as lacking fundamental understanding of internal oxygenation dynamics in tumours, the precise oxygen distribution map is rarely available for treatment planing. We employ an agent-based in silico tumour spheroid model in order to study the complex, localized and fast oxygen dynamics in tumour micro-regions which are induced by radiotherapy. A lattice-free, 3D, agent-based approach for cell representation is coupled with a high-resolution diffusion solver that includes a tissue density-dependent diffusion coefficient. This allows us to assess the space- and time-resolved reoxygenation response of a small subvolume of tumour tissue in response to radiotherapy. In response to irradiation the tumour nodule exhibits characteristic reoxygenation and re-depletion dynamics which we resolve with high spatio-temporal resolution. The reoxygenation follows specific timings, which should be respected in treatment in order to maximise the use of the oxygen enhancement effects. Oxygen dynamics within the tumour create windows of opportunity for the use of adjuvant chemotherapeutica and hypoxia-activated drugs. Overall, we show that by using modelling it is possible to follow the oxygenation dynamics beyond common resolution limits and predict beneficial strategies for therapy and in vitro verification. Models of cell cycle and oxygen dynamics in tumours should in the future be combined with imaging techniques, to allow for a systematic experimental study of possible improved schedules and to ultimately extend the reach of oxygenation monitoring available in clinical treatment. PMID:26273841

  10. Spatio-temporal coupling of EEG signals in epilepsy

    NASA Astrophysics Data System (ADS)

    Senger, Vanessa; Müller, Jens; Tetzlaff, Ronald

    2011-05-01

    Approximately 1% of the world's population suffer from epileptic seizures throughout their lives that mostly come without sign or warning. Thus, epilepsy is the most common chronical disorder of the neurological system. In the past decades, the problem of detecting a pre-seizure state in epilepsy using EEG signals has been addressed in many contributions by various authors over the past two decades. Up to now, the goal of identifying an impending epileptic seizure with sufficient specificity and reliability has not yet been achieved. Cellular Nonlinear Networks (CNN) are characterized by local couplings of dynamical systems of comparably low complexity. Thus, they are well suited for an implementation as highly parallel analogue processors. Programmable sensor-processor realizations of CNN combine high computational power comparable to tera ops of digital processors with low power consumption. An algorithm allowing an automated and reliable detection of epileptic seizure precursors would be a"huge step" towards the vision of an implantable seizure warning device that could provide information to patients and for a time/event specific treatment directly in the brain. Recent contributions have shown that modeling of brain electrical activity by solutions of Reaction-Diffusion-CNN as well as the application of a CNN predictor taking into account values of neighboring electrodes may contribute to the realization of a seizure warning device. In this paper, a CNN based predictor corresponding to a spatio-temporal filter is applied to multi channel EEG data in order to identify mutual couplings for different channels which lead to a enhanced prediction quality. Long term EEG recordings of different patients are considered. Results calculated for these recordings with inter-ictal phases as well as phases with seizures will be discussed in detail.

  11. Spatiotemporally Defining Biomolecule Preconcentration by Merging Ion Concentration Polarization.

    PubMed

    Kwak, Rhokyun; Kang, Ji Yoon; Kim, Tae Song

    2016-01-01

    The ion concentration polarization (ICP) phenomenon at micronanofluidic interfaces has been extensively utilized to preconcentrate low-abundance biological samples. Although preconcentration by ICP is robust, its multiphysics phenomenon does not permit a clear prediction of the preconcentration conditions and sites. Here, we present a new method for spatiotemporally defining preconcentration, which can generate target-condensed plugs in a very specific region (<100 μm) regardless of the operating conditions (time, applied voltage, ionic strength, and pH). In contrast to previous devices that use only ion depletion, this device uses merged ICP zones with opposite polarity, i.e., ion depletion and ion enrichment. In this regard, ICP is initiated between two line-patterned cation exchange membranes. When voltage is applied across two membranes, an ion depletion (enrichment) zone occurs on the anodic (cathodic) side of the membranes. Two ICP zones are then merged and confined between the membranes. Consequently, the preconcentration action is also confined between the membranes. We demonstrate that fluorescent dyes are always preconcentrated at the designated location at all lengths of operating time and at broad voltage (0.5-100 V), ionic strength (1-100 mM KCl), and pH (3.7-10.3) ranges. This device successfully condenses proteins up to 10000-fold in a specific region of the channel (100 × 50 × 10 μm(3)) in 10 min. This work not only characterizes the unique scientific phenomenon of ICP overlapping but also opens the possibility of integrating ICP preconcentrators into commercial analysis equipment, which requires a known, stationary preconcentration site. PMID:26642086

  12. Combining Land-Use Regression and Chemical Transport Modeling in a Spatiotemporal Geostatistical Model for Ozone and PM2.5.

    PubMed

    Wang, Meng; Sampson, Paul D; Hu, Jianlin; Kleeman, Michael; Keller, Joshua P; Olives, Casey; Szpiro, Adam A; Vedal, Sverre; Kaufman, Joel D

    2016-05-17

    Assessments of long-term air pollution exposure in population studies have commonly employed land-use regression (LUR) or chemical transport modeling (CTM) techniques. Attempts to incorporate both approaches in one modeling framework are challenging. We present a novel geostatistical modeling framework, incorporating CTM predictions into a spatiotemporal LUR model with spatial smoothing to estimate spatiotemporal variability of ozone (O3) and particulate matter with diameter less than 2.5 μm (PM2.5) from 2000 to 2008 in the Los Angeles Basin. The observations include over 9 years' data from more than 20 routine monitoring sites and specific monitoring data at over 100 locations to provide more comprehensive spatial coverage of air pollutants. Our composite modeling approach outperforms separate CTM and LUR models in terms of root-mean-square error (RMSE) assessed by 10-fold cross-validation in both temporal and spatial dimensions, with larger improvement in the accuracy of predictions for O3 (RMSE [ppb] for CTM, 6.6; LUR, 4.6; composite, 3.6) than for PM2.5 (RMSE [μg/m(3)] CTM: 13.7, LUR: 3.2, composite: 3.1). Our study highlights the opportunity for future exposure assessment to make use of readily available spatiotemporal modeling methods and auxiliary gridded data that takes chemical reaction processes into account to improve the accuracy of predictions in a single spatiotemporal modeling framework. PMID:27074524

  13. Spatiotemporal grid flow for video retargeting.

    PubMed

    Li, Bing; Duan, Ling-Yu; Wang, Jinqiao; Ji, Rongrong; Lin, Chia-Wen; Gao, Wen

    2014-04-01

    Video retargeting is a useful technique to adapt a video to a desired display resolution. It aims to preserve the information contained in the original video and the shapes of salient objects while maintaining the temporal coherence of contents in the video. Existing video retargeting schemes achieve temporal coherence via constraining each region/pixel to be deformed consistently with its corresponding region/pixel in neighboring frames. However, these methods often distort the shapes of salient objects, since they do not ensure the content consistency for regions/pixels constrained to be coherently deformed along time axis. In this paper, we propose a video retargeting scheme to simultaneously meet the two requirements. Our method first segments a video clip into spatiotemporal grids called grid flows, where the consistency of the content associated with a grid flow is maintained while retargeting the grid flow. After that, due to the coarse granularity of grid, there still may exist content inconsistency in some grid flows. We exploit the temporal redundancy in a grid flow to avoid that the grids with inconsistent content be incorrectly constrained to be coherently deformed. In particular, we use grid flows to select a set of key-frames which summarize a video clip, and resize subgrid-flows in these key-frames. We then resize the remaining nonkey-frames by simply interpolating their grid contents from the two nearest retargeted key-frames. With the key-frame-based scheme, we only need to solve a small-scale quadratic programming problem to resize subgrid-flows and perform grid interpolation, leading to low computation and memory costs. The experimental results demonstrate the superior performance of our scheme. PMID:24577196

  14. Sequence matching using spatiotemporal wavelet decomposition

    NASA Astrophysics Data System (ADS)

    Corghi, A.; Leonardi, Riccardo

    1997-01-01

    Indexing and retrieval of image sequences are fundamental steps in video editing and film analysis. Correlation-based matching methods are known to be very expensive when used with large amounts of data. As the size of sequence database grows, traditional retrieval methods fail. Exhaustive search quickly breaks down as an efficient strategy for sequence databases. Moreover, traditional indexing with labels has a lot of drawbacks since it requires a human intervention. New advanced correlation filters are being proposed so as to decrease the computational load of the task. A new method for retrieval of images sequences in large database based on a spatio-temporal wavelet decomposition is proposed here. It will be shown how the use of the multiresolution approach can lead to good results in terms of computationally efficiency and robustness to noise. We will assume that the query sequence may not be contained in the database for different reasons: the presence of a noise signal on the query, or different digitation process, or the query is only similar to sequences in the database. As a consequence we are providing have developed a new efficient retrieval strategy that analyses the database in order to extract the most similar sequences to a given query. The wavelet transform has been chose as the framework to implement the multiresolution formalism, because of its good compression capabilities, especially for embedded schemes. And the good features it provides for signal analysis. This paper describes the principles of a multiresolution sequence matching strategy and outlines its performance through a series of experimental simulations.

  15. Spatio-temporal variability in ventricular fibrillation

    NASA Astrophysics Data System (ADS)

    Hastings, Harold M.; Evans, Steven J.; Fenton, Flavio H.; Garfinkel, Alan

    2001-03-01

    It is widely believed that reentrant ventricular tachycardia arises when a spiral wave of activation takes over and drives the ventricle at a rate significantly faster than sinus rhythm, and that ventricular fibrillation (VF), a spatio-temporally disorganized form of cardiac activity leading to sudden cardiac death, arises when this spiral breaks down into multiple offspring. Many authors have found that VF displays significant spatial and temporal organization. The purpose of this research is to quantify time scales and temporal and spatial variability in VF. Surface electrograms were obtained from a stable canine model of VF (cf. Nwasokwa and Bodenheimer, Am. J. Physiol. 253, H643 (1987)). These electrograms were analyzed to identify activation times to an accuracy of 1 ms (cf. Garfinkel et al., J. Clin. Invest. 99, 305 (1997)), yielded eighteen usable series, each containing over 1024 intervactivation intervals, two or three from widely spaced sites per episode of VF, 7 total episodes in 4 animals. Spatial and long-term (60 - 120 sec) temporal variability were analyzed and compared by ANOVA techniques (Evans et al., Proc. Royal Soc. B265, 2167 (1998)). In 6 of 7 episodes, spatial variability among sites was statistically more significant than variability between the first and second halves of each series. More recently, Fourier analysis of these series found three distinct scaling regions, with power law dynamics in each and break points of ca. 1 sec and 4 sec. Finally, there was significant variability in the fraction of "short" interactivation intervals (lasting < 60 of 125 ms) among sites. Together these results suggest variability in physiological properties among sites and consequent variability in spiral wave dynamics among sites.

  16. 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

  17. Spatio-temporal chaos in a chemotaxis model

    NASA Astrophysics Data System (ADS)

    Painter, Kevin J.; Hillen, Thomas

    2011-02-01

    In this paper we explore the dynamics of a one-dimensional Keller-Segel type model for chemotaxis incorporating a logistic cell growth term. We demonstrate the capacity of the model to self-organise into multiple cellular aggregations which, according to position in parameter space, either form a stationary pattern or undergo a sustained spatio-temporal sequence of merging (two aggregations coalesce) and emerging (a new aggregation appears). This spatio-temporal patterning can be further subdivided into either a time-periodic or time-irregular fashion. Numerical explorations into the latter indicate a positive Lyapunov exponent (sensitive dependence to initial conditions) together with a rich bifurcation structure. In particular, we find stationary patterns that bifurcate onto a path of periodic patterns which, prior to the onset of spatio-temporal irregularity, undergo a “periodic-doubling” sequence. Based on these results and comparisons with other systems, we argue that the spatio-temporal irregularity observed here describes a form of spatio-temporal chaos. We discuss briefly our results in the context of previous applications of chemotaxis models, including tumour invasion, embryonic development and ecology.

  18. Identification of the hypoxia-inducible factor 2α nuclear interactome in melanoma cells reveals master proteins involved in melanoma development.

    PubMed

    Steunou, Anne-Lise; Ducoux-Petit, Manuelle; Lazar, Ikrame; Monsarrat, Bernard; Erard, Monique; Muller, Catherine; Clottes, Eric; Burlet-Schiltz, Odile; Nieto, Laurence

    2013-03-01

    Hypoxia-inducible factors (HIFs) are heterodimeric transcription factors that play a key role in cellular adaptation to hypoxia. HIF proteins are composed of an α subunit regulated by oxygen pressure (essentially HIF1α or HIF2α) and a constitutively expressed β subunit. These proteins are often overexpressed in cancer cells, and HIF overexpression frequently correlates with poor prognosis, making HIF proteins promising therapeutic targets. HIF proteins are involved in melanoma initiation and progression; however, the specific function of HIF2 in melanoma has not yet been studied comprehensively. Identifying protein complexes is a valuable way to uncover protein function, and affinity purification coupled with mass spectrometry and label-free quantification is a reliable method for this approach. We therefore applied quantitative interaction proteomics to identify exhaustively the nuclear complexes containing HIF2α in a human melanoma cell line, 501mel. We report, for the first time, a high-throughput analysis of the interactome of an HIF subunit. Seventy proteins were identified that interact with HIF2α, including some well-known HIF partners and some new interactors. The new HIF2α partners microphthalmia-associated transcription factor, SOX10, and AP2α, which are master actors of melanoma development, were confirmed via co-immunoprecipitation experiments. Their ability to bind to HIF1α was also tested: microphthalmia-associated transcription factor and SOX10 were confirmed as HIF1α partners, but the transcription factor AP2α was not. AP2α expression correlates with low invasive capacities. Interestingly, we demonstrated that when HIF2α was overexpressed, only cells expressing large amounts of AP2α exhibited decreased invasive capacities in hypoxia relative to normoxia. The simultaneous presence of both transcription factors therefore reduces cells' invasive properties. Knowledge of the HIF2α interactome is thus a useful resource for investigating the general mechanisms of HIF function and regulation, and here we reveal unexpected, distinct roles for the HIF1 and HIF2 isoforms in melanoma progression. PMID:23275444

  19. 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. PMID:26772433

  20. Spatio-temporal propagation of cascading overload failures in spatially embedded networks

    PubMed Central

    Zhao, Jichang; Li, Daqing; Sanhedrai, Hillel; Cohen, Reuven; Havlin, Shlomo

    2016-01-01

    Different from the direct contact in epidemics spread, overload failures propagate through hidden functional dependencies. Many studies focused on the critical conditions and catastrophic consequences of cascading failures. However, to understand the network vulnerability and mitigate the cascading overload failures, the knowledge of how the failures propagate in time and space is essential but still missing. Here we study the spatio-temporal propagation behaviour of cascading overload failures analytically and numerically on spatially embedded networks. The cascading overload failures are found to spread radially from the centre of the initial failure with an approximately constant velocity. The propagation velocity decreases with increasing tolerance, and can be well predicted by our theoretical framework with one single correction for all the tolerance values. This propagation velocity is found similar in various model networks and real network structures. Our findings may help to predict the dynamics of cascading overload failures in realistic systems. PMID:26754065

  1. Spatio-temporal propagation of cascading overload failures in spatially embedded networks.

    PubMed

    Zhao, Jichang; Li, Daqing; Sanhedrai, Hillel; Cohen, Reuven; Havlin, Shlomo

    2016-01-01

    Different from the direct contact in epidemics spread, overload failures propagate through hidden functional dependencies. Many studies focused on the critical conditions and catastrophic consequences of cascading failures. However, to understand the network vulnerability and mitigate the cascading overload failures, the knowledge of how the failures propagate in time and space is essential but still missing. Here we study the spatio-temporal propagation behaviour of cascading overload failures analytically and numerically on spatially embedded networks. The cascading overload failures are found to spread radially from the centre of the initial failure with an approximately constant velocity. The propagation velocity decreases with increasing tolerance, and can be well predicted by our theoretical framework with one single correction for all the tolerance values. This propagation velocity is found similar in various model networks and real network structures. Our findings may help to predict the dynamics of cascading overload failures in realistic systems. PMID:26754065

  2. Spatio-temporal propagation of cascading overload failures in spatially embedded networks

    NASA Astrophysics Data System (ADS)

    Zhao, Jichang; Li, Daqing; Sanhedrai, Hillel; Cohen, Reuven; Havlin, Shlomo

    2016-01-01

    Different from the direct contact in epidemics spread, overload failures propagate through hidden functional dependencies. Many studies focused on the critical conditions and catastrophic consequences of cascading failures. However, to understand the network vulnerability and mitigate the cascading overload failures, the knowledge of how the failures propagate in time and space is essential but still missing. Here we study the spatio-temporal propagation behaviour of cascading overload failures analytically and numerically on spatially embedded networks. The cascading overload failures are found to spread radially from the centre of the initial failure with an approximately constant velocity. The propagation velocity decreases with increasing tolerance, and can be well predicted by our theoretical framework with one single correction for all the tolerance values. This propagation velocity is found similar in various model networks and real network structures. Our findings may help to predict the dynamics of cascading overload failures in realistic systems.

  3. Assessment of soil organic carbon distribution in Europe scale by spatio-temporal data and geostatistics

    NASA Astrophysics Data System (ADS)

    Aksoy, Ece; Panagos, Panos; Montanarella, Luca

    2013-04-01

    Accuracy in assessing the distribution of soil organic carbon (SOC) is an important issue because SOC is an important soil component that plays key roles in the functions of both natural ecosystems and agricultural systems. The SOC content varies from place to place and it is strongly related with climate variables (temperature and rainfall), terrain features, soil texture, parent material, vegetation, land-use types, and human management (management and degradation) at different spatial scales. Geostatistical techniques allow for the prediction of soil properties using soil information and environmental covariates. In this study, assessment of SOC distribution has been predicted using combination of LUCAS soil samples with local soil data and ten spatio-temporal predictors (slope, aspect, elevation, CTI, CORINE land-cover classification, parent material, texture, WRB soil classification, average temperature and precipitation) with Regression-Kriging method in Europe scale. Significant correlation between the covariates and the organic carbon dependent variable was found.

  4. Spatiotemporal dynamics of optogenetically induced and spontaneous seizure transitions in primary generalized epilepsy

    PubMed Central

    Truccolo, Wilson; Wang, Jing; Nurmikko, Arto V.

    2014-01-01

    Transitions into primary generalized epileptic seizures occur abruptly and synchronously across the brain. Their potential triggers remain unknown. We used optogenetics to causally test the hypothesis that rhythmic population bursting of excitatory neurons in a local neocortical region can rapidly trigger absence seizures. Most previous studies have been purely correlational, and it remains unclear whether epileptiform events induced by rhythmic stimulation (e.g., sensory/electrical) mimic actual spontaneous seizures, especially regarding their spatiotemporal dynamics. In this study, we used a novel combination of intracortical optogenetic stimulation and microelectrode array recordings in freely moving WAG/Rij rats, a model of absence epilepsy with a cortical focus in the somatosensory cortex (SI). We report three main findings: 1) Brief rhythmic bursting, evoked by optical stimulation of neocortical excitatory neurons at frequencies around 10 Hz, induced seizures consisting of self-sustained spike-wave discharges (SWDs) for about 10% of stimulation trials. The probability of inducing seizures was frequency-dependent, reaching a maximum at 10 Hz. 2) Local field potential power before stimulation and response amplitudes during stimulation both predicted seizure induction, demonstrating a modulatory effect of brain states and neural excitation levels. 3) Evoked responses during stimulation propagated as cortical waves, likely reaching the cortical focus, which in turn generated self-sustained SWDs after stimulation was terminated. Importantly, SWDs during induced and spontaneous seizures propagated with the same spatiotemporal dynamics. Our findings demonstrate that local rhythmic bursting of excitatory neurons in neocortex at particular frequencies, under susceptible ongoing brain states, is sufficient to trigger primary generalized seizures with stereotypical spatiotemporal dynamics. PMID:25552645

  5. Spatiotemporal probability of vent opening at Mt Etna volcano (Sicily, Italy)

    NASA Astrophysics Data System (ADS)

    Cappello, A.; Bilotta, G.; Neri, M.; Acocella, V.; Gallo, G.; Del Negro, C.

    2012-04-01

    We produced a spatiotemporal probability map of vent opening at Mt Etna, using a statistical analysis of structural features of the flank eruptions of the last 2000 years. The methodology is based on the hypothesis that the location and frequency of future events will have the same causal factors as the eruptions occurring in the past. The study is supported by a detailed knowledge of the volcano structures, including the modalities of shallow magma transfer deriving from dike and dike-fed fissure eruptions analysis on historical eruptions. The geological and structural data are converted in distinct and weighted probability density functions (PDFs), exploiting both spatial and temporal recurrence rates. The spatiotemporal probability map is obtained through a non-homogeneous Poisson process, where the expected recurrence rate per unit area is calculated as the weighted sum of the PDFs, with the weights derived from a backward/forward analysis to highlight the presence of temporal trends in the history of the volcano. The highest probability of new eruptive vents opening at Mt Etna falls within a N-S aligned area passing through the Summit Craters down to about 2000 m a.s.l. on the southern flank. Four other zones of high probability follow respectively the North-East, East-North-East, West and South Rifts, the latter reaching low altitudes (~400 m). Less susceptible areas prone to the opening of new vents were found around the faults cutting the upper portions of Mt Etna, including the western portion of the Pernicana fault system and the northern extent of the Ragalna fault system. The spatiotemporal probability map of vent opening provides detailed recurrence rates (events expected per unit area per unit time) and will hence be an important resource to predict the future timing and location of Etna eruptions. This structural-based map is the first and perhaps most important step in assessing lava flow hazards at Mt Etna, and thus represents a support tool for decision makers.

  6. Spatiotemporal localized modes in PT-symmetric optical media

    SciTech Connect

    Wang, Yue-Yue; Dai, Chao-Qing Wang, Xiao-Gang

    2014-09-15

    We firstly obtain spatiotemporal localized mode solutions of a (3+1)-dimensional nonlinear Schrödinger equation in PT-symmetric potentials, and then discuss the linear stability of LMs, which are also tested by means of direct simulations. Moreover, phase switches and transverse power-flow density associated with these localized modes have also been examined. At last, we investigate the dynamical behaviors of spatiotemporal LMs in three kinds of inhomogeneous media. - Highlights: • Spatiotemporal LMs of a (3+1)-dimensional NLSE in PT-symmetric potentials are obtained. • Phase switches and transverse power-flow density of LM are examined. • Dynamical behaviors of LMs in three kinds of inhomogeneous media are studied.

  7. Pattern formation and spatiotemporal behavior of adhesive in peeling

    NASA Astrophysics Data System (ADS)

    Yamazaki, Yoshihiro; Toda, Akihiko

    2006-02-01

    We examined various spatiotemporal patterns evolving in deformed adhesives during peeling. The patterns are regarded as a spatiotemporal distribution of a tunnel structure formed by the deformed adhesive, and are classified into the following four types: (A) uniform pattern with tunnel structure, (B) uniform pattern without tunnel structure, (C) striped pattern alternating between A and B in time, and (D) spatiotemporal pattern made by the coexistence of two regions with and without the tunnel structure. We are able to reproduce these patterns and the mechanical and statistical behaviors by constructing a model with a state variable representing the stability of the tunnel structure. The essential factor of the pattern formation is the competition between a local asymmetric interaction and a global coupling of the state variables.

  8. Reaction diffusion equation with spatio-temporal delay

    NASA Astrophysics Data System (ADS)

    Zhao, Zhihong; Rong, Erhua

    2014-07-01

    We investigate reaction-diffusion equation with spatio-temporal delays, the global existence, uniqueness and asymptotic behavior of solutions for which in relation to constant steady-state solution, included in the region of attraction of a stable steady solution. It is shown that if the delay reaction function satisfies some conditions and the system possesses a pair of upper and lower solutions then there exists a unique global solution. In terms of the maximal and minimal constant solutions of the corresponding steady-state problem, we get the asymptotic stability of reaction-diffusion equation with spatio-temporal delay. Applying this theory to Lotka-Volterra model with spatio-temporal delay, we get the global solution asymptotically tend to the steady-state problem's steady-state solution.

  9. Spatiotemporal evolution and nonlinear kinetic simulations of stimulated Brillouin scattering

    NASA Astrophysics Data System (ADS)

    Giacone, Rodolfo E.

    The spatiotemporal evolution of stimulated Brillouin scattering (SBS) in homogeneous plasmas and some aspects of the influence that nonlinear and kinetic effects have on the evolution of SBS were studied. A one-dimensional analytical linear model based on a fluid description of the plasma was developed initially. It was found that the threshold intensity of the absolute instability and the steady-state spatial growth rate of the convective instability are both independent of the scattering angle. However, the saturation time of the convective instability exhibits a strong inverse dependence on the scattering angle. The basic model was improved by extending the one- dimensional analysis to include two spatial dimensions and time. In order to assess the effects that the finite size of the laser beam has on SBS, wide and narrow laser- beam geometries were considered. Detailed comparisons were made between the predictions of reduced one- and two-dimensional models, which can be solved analytically, and the results of two-dimensional numerical simulations. It was found that the linear evolution of SBS was characterized by three parameters: the spatial growth rate in the direction of the Stokes wave, the spatial damping rate of the ion-acoustic wave in the direction of the Stokes wave and the normalized width of the interaction region. SBS can be saturated by the damping or the lateral convection of the ion-acoustic wave, both of which limit the growth of the ion- acoustic wave (directly) and the Stokes wave (indirectly). For most scattering angles the predicted saturation mechanism, and the corresponding saturation time and gain factor agree with the simulation results. The influence that nonlinear and kinetic effects have on SBS was investigated by performing particle-in-cell (PIC) simulations. The results of these PIC simulations were compared against fluid simulations, and good agreement was obtained for weak laser intensities. When the laser intensity is strong enough, PIC and fluid simulations differ substantially. It was shown that among various saturation mechanisms such as pump depletion, wavebreaking and generation of ion-acoustic wave harmonics, ion-trapping is the mechanism responsible for the observed differences. The SBS reflectivity is shown to depend sensitively on the frequency mismatch between the light wave used to seed the instability and the incident laser.

  10. Light-filament dynamics and the spatiotemporal instability of the Townes profile

    SciTech Connect

    Porras, Miguel A.; Parola, Alberto; Faccio, Daniele; Couairon, Arnaud; Di Trapani, Paolo

    2007-07-15

    The origin of the spatiotemporal filament dynamics of ultrashort pulses in nonlinear media, including axial-conical emission coupling, temporal splitting, and X waves, is explained by the spatiotemporal instability of spatially localized nonlinear modes. Our experiments support this interpretation.

  11. Routes to spatiotemporal chaos in Kerr optical frequency combs

    SciTech Connect

    Coillet, Aurélien; Chembo, Yanne K.

    2014-03-15

    We investigate the various routes to spatiotemporal chaos in Kerr optical frequency combs, obtained through pumping an ultra-high Q-factor whispering-gallery mode resonator with a continuous-wave laser. The Lugiato–Lefever model is used to build bifurcation diagrams with regards to the parameters that are externally controllable, namely, the frequency and the power of the pumping laser. We show that the spatiotemporal chaos emerging from Turing patterns and solitons display distinctive dynamical features. Experimental spectra of chaotic Kerr combs are also presented for both cases, in excellent agreement with theoretical spectra.

  12. Routes to spatiotemporal chaos in Kerr optical frequency combs.

    PubMed

    Coillet, Aurélien; Chembo, Yanne K

    2014-03-01

    We investigate the various routes to spatiotemporal chaos in Kerr optical frequency combs, obtained through pumping an ultra-high Q-factor whispering-gallery mode resonator with a continuous-wave laser. The Lugiato-Lefever model is used to build bifurcation diagrams with regards to the parameters that are externally controllable, namely, the frequency and the power of the pumping laser. We show that the spatiotemporal chaos emerging from Turing patterns and solitons display distinctive dynamical features. Experimental spectra of chaotic Kerr combs are also presented for both cases, in excellent agreement with theoretical spectra. PMID:24697375

  13. Artificial neural network does better spatiotemporal compressive sampling

    NASA Astrophysics Data System (ADS)

    Lee, Soo-Young; Hsu, Charles; Szu, Harold

    2012-06-01

    Spatiotemporal sparseness is generated naturally by human visual system based on artificial neural network modeling of associative memory. Sparseness means nothing more and nothing less than the compressive sensing achieves merely the information concentration. To concentrate the information, one uses the spatial correlation or spatial FFT or DWT or the best of all adaptive wavelet transform (cf. NUS, Shen Shawei). However, higher dimensional spatiotemporal information concentration, the mathematics can not do as flexible as a living human sensory system. The reason is obviously for survival reasons. The rest of the story is given in the paper.

  14. Male reproductive strategy explains spatiotemporal segregation in brown bears

    PubMed Central

    Steyaert, Sam MJG; Kindberg, Jonas; Swenson, Jon E; Zedrosser, Andreas

    2013-01-01

    1. Spatiotemporal segregation is often explained by the risk for offspring predation or by differences in physiology, predation risk vulnerability or competitive abilities related to size dimorphism. 2. Most large carnivores are size dimorphic and offspring predation is often intraspecific and related to nonparental infanticide (NPI). NPI can be a foraging strategy, a strategy to reduce competition, or a male reproductive strategy. Spatiotemporal segregation is widespread among large carnivores, but its nature remains poorly understood. 3. We evaluated three hypotheses to explain spatiotemporal segregation in the brown bear, a size-dimorphic large carnivore in which NPI is common; the ‘NPI – foraging/competition hypothesis', i.e. NPI as a foraging strategy or a strategy to reduce competition, the ‘NPI – sexual selection hypothesis’, i.e. infanticide as a male reproductive strategy and the ‘body size hypothesis’, i.e. body-size-related differences in physiology, predation risk vulnerability or competitive ability causes spatiotemporal segregation. To test these hypotheses, we quantified spatiotemporal segregation among adult males, lone adult females and females with cubs-of-the-year, based on GPS-relocation data (2006–2010) and resource selection functions in a Scandinavian population. 4. We found that spatiotemporal segregation was strongest between females with cubs-of-the-year and adult males during the mating season. During the mating season, females with cubs-of-the-year selected their resources, in contrast to adult males, in less rugged landscapes in relative close proximity to certain human-related variables, and in more open habitat types. After the mating season, females with cubs-of-the-year markedly shifted their resource selection towards a pattern more similar to that of their conspecifics. No strong spatiotemporal segregation was apparent between females with cubs-of-the-year and conspecifics during the mating and the postmating season. 5. The ‘NPI – sexual selection hypothesis’ best explained spatiotemporal segregation in our study system. We suggest that females with cubs-of-the-year alter their resource selection to avoid infanticidal males. In species exhibiting NPI as a male reproductive strategy, female avoidance of infanticidal males is probably more common than observed or reported, and may come with a fitness cost if females trade safety for optimal resources. PMID:23461483

  15. Time reversal and the spatio-temporal matched filter

    SciTech Connect

    Lehman, S K; Poggio, A J; Kallman, J S; Meyer, A W; Candy, J V

    2004-03-08

    It is known that focusing of an acoustic field by a time-reversal mirror (TRM) is equivalent to a spatio-temporal matched filter under conditions where the Green's function of the field satisfies reciprocity and is time invariant, i.e. the Green's function is independent of the choice of time origin. In this letter, it is shown that both reciprocity and time invariance can be replaced by a more general constraint on the Green's function that allows a TRM to implement the spatio-temporal matched filter even when conditions are time varying.

  16. Male reproductive strategy explains spatiotemporal segregation in brown bears.

    PubMed

    Steyaert, Sam M J G; Kindberg, Jonas; Swenson, Jon E; Zedrosser, Andreas

    2013-07-01

    Spatiotemporal segregation is often explained by the risk for offspring predation or by differences in physiology, predation risk vulnerability or competitive abilities related to size dimorphism. Most large carnivores are size dimorphic and offspring predation is often intraspecific and related to nonparental infanticide (NPI). NPI can be a foraging strategy, a strategy to reduce competition, or a male reproductive strategy. Spatiotemporal segregation is widespread among large carnivores, but its nature remains poorly understood. We evaluated three hypotheses to explain spatiotemporal segregation in the brown bear, a size-dimorphic large carnivore in which NPI is common; the 'NPI - foraging/competition hypothesis', i.e. NPI as a foraging strategy or a strategy to reduce competition, the 'NPI - sexual selection hypothesis', i.e. infanticide as a male reproductive strategy and the 'body size hypothesis', i.e. body-size-related differences in physiology, predation risk vulnerability or competitive ability causes spatiotemporal segregation. To test these hypotheses, we quantified spatiotemporal segregation among adult males, lone adult females and females with cubs-of-the-year, based on GPS-relocation data (2006-2010) and resource selection functions in a Scandinavian population. We found that spatiotemporal segregation was strongest between females with cubs-of-the-year and adult males during the mating season. During the mating season, females with cubs-of-the-year selected their resources, in contrast to adult males, in less rugged landscapes in relative close proximity to certain human-related variables, and in more open habitat types. After the mating season, females with cubs-of-the-year markedly shifted their resource selection towards a pattern more similar to that of their conspecifics. No strong spatiotemporal segregation was apparent between females with cubs-of-the-year and conspecifics during the mating and the postmating season. The 'NPI - sexual selection hypothesis' best explained spatiotemporal segregation in our study system. We suggest that females with cubs-of-the-year alter their resource selection to avoid infanticidal males. In species exhibiting NPI as a male reproductive strategy, female avoidance of infanticidal males is probably more common than observed or reported, and may come with a fitness cost if females trade safety for optimal resources. PMID:23461483

  17. Improving transverse resolution of confocal microscopy through spatiotemporal modulation

    NASA Astrophysics Data System (ADS)

    Wang, Baokai; Zou, Limin; Zhang, Su; Tan, Jiubin

    2015-11-01

    A new method is proposed in this paper to improve transverse resolution of a confocal microscope. By setting up the model of a confocal microscope system through spatiotemporal modulation with moving gratings or acousto-optical modulation without defocus distance under coherent light illumination and deducing two-dimensional coherent image formula and transfer function, simulation tests are run with or without spatiotemporal modulation to prove the effectiveness of the proposed method. Simulation results indicate the proposed method can be used to improve the transverse resolution of a confocal microscope system.

  18. Routes to spatiotemporal chaos in Kerr optical frequency combs

    SciTech Connect

    Coillet, Aurlien; Chembo, Yanne K.

    2014-03-15

    We investigate the various routes to spatiotemporal chaos in Kerr optical frequency combs, obtained through pumping an ultra-high Q-factor whispering-gallery mode resonator with a continuous-wave laser. The LugiatoLefever model is used to build bifurcation diagrams with regards to the parameters that are externally controllable, namely, the frequency and the power of the pumping laser. We show that the spatiotemporal chaos emerging from Turing patterns and solitons display distinctive dynamical features. Experimental spectra of chaotic Kerr combs are also presented for both cases, in excellent agreement with theoretical spectra.

  19. Light-Activated Proteolysis for the Spatiotemporal Control of Proteins.

    PubMed

    Delacour, Quentin; Li, Chenge; Plamont, Marie-Aude; Billon-Denis, Emmanuelle; Aujard, Isabelle; Le Saux, Thomas; Jullien, Ludovic; Gautier, Arnaud

    2015-07-17

    The regulation of proteolysis is an efficient way to control protein function in cells. Here, we present a general strategy enabling to increase the spatiotemporal resolution of conditional proteolysis by using light activation as trigger. Our approach relies on the auxin-inducible degradation system obtained by transposing components of the plant auxin-dependent degradation pathway in mammalian cells. We developed a photoactivatable auxin that acts as a photoactivatable inducer of degradation. Upon local and short light illumination, auxin is released in cells and triggers the degradation of a protein of interest with spatiotemporal control. PMID:25938742

  20. Spatiotemporal focusing dynamics in plasmas at X-ray wavelength

    SciTech Connect

    Sharma, A. Tibai, Z.; Hebling, J.; Szentagothai Research Centre, University of Pecs, Pecs-7624 ; Mishra, S. K.

    2014-03-15

    Using a finite curvature beam, we investigate here the spatiotemporal focusing dynamics of a laser pulse in plasmas at X-ray wavelength. We trace the dependence of curvature parameter on the focusing of laser pulse and recognize that the self-focusing in plasma is more intense for the X-ray laser pulse with curved wavefront than with flat wavefront. The simulation results demonstrate that spatiotemporal focusing dynamics in plasmas can be controlled with the appropriate choice of beam-plasma parameters to explore the high intensity effects in X-ray regime.

  1. Toward understanding the multiple spatiotemporal dynamics of chlorophyll fluorescence

    PubMed Central

    Iwai, Masakazu; Yokono, Makio; Nakano, Akihiko

    2015-01-01

    Dynamic reorganization of photosystems I and II is suggested to occur in chloroplast thylakoid membranes to maintain the efficiency of photosynthesis under fluctuating light conditions. To directly observe the process in action, live-cell imaging techniques are necessary. Using live-cell imaging, we have shown that the fine thylakoid structures in the moss Physcomitrella patens are flexible in time. However, the spatiotemporal resolution of a conventional confocal microscopy limits more precise visualization of entire thylakoid structures and understanding of the structural dynamics. Here, we discuss the issues related to observing chlorophyll fluorescence at multiple spatiotemporal scales in vivo and in vitro. PMID:26176900

  2. Tensor analysis methods for activity characterization in spatiotemporal data

    SciTech Connect

    Haass, Michael Joseph; Van Benthem, Mark Hilary; Ochoa, Edward M.

    2014-03-01

    Tensor (multiway array) factorization and decomposition offers unique advantages for activity characterization in spatio-temporal datasets because these methods are compatible with sparse matrices and maintain multiway structure that is otherwise lost in collapsing for regular matrix factorization. This report describes our research as part of the PANTHER LDRD Grand Challenge to develop a foundational basis of mathematical techniques and visualizations that enable unsophisticated users (e.g. users who are not steeped in the mathematical details of matrix algebra and mulitway computations) to discover hidden patterns in large spatiotemporal data sets.

  3. Predictability of Conversation Partners

    NASA Astrophysics Data System (ADS)

    Takaguchi, Taro; Nakamura, Mitsuhiro; Sato, Nobuo; Yano, Kazuo; Masuda, Naoki

    2011-08-01

    Recent developments in sensing technologies have enabled us to examine the nature of human social behavior in greater detail. By applying an information-theoretic method to the spatiotemporal data of cell-phone locations, [C. Song , ScienceSCIEAS0036-8075 327, 1018 (2010)] found that human mobility patterns are remarkably predictable. Inspired by their work, we address a similar predictability question in a different kind of human social activity: conversation events. The predictability in the sequence of one’s conversation partners is defined as the degree to which one’s next conversation partner can be predicted given the current partner. We quantify this predictability by using the mutual information. We examine the predictability of conversation events for each individual using the longitudinal data of face-to-face interactions collected from two company offices in Japan. Each subject wears a name tag equipped with an infrared sensor node, and conversation events are marked when signals are exchanged between sensor nodes in close proximity. We find that the conversation events are predictable to a certain extent; knowing the current partner decreases the uncertainty about the next partner by 28.4% on average. Much of the predictability is explained by long-tailed distributions of interevent intervals. However, a predictability also exists in the data, apart from the contribution of their long-tailed nature. In addition, an individual’s predictability is correlated with the position of the individual in the static social network derived from the data. Individuals confined in a community—in the sense of an abundance of surrounding triangles—tend to have low predictability, and those bridging different communities tend to have high predictability.

  4. 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

  5. Proteomic Analysis of the EWS-Fli-1 Interactome Reveals the Role of the Lysosome in EWS-Fli-1 Turnover

    PubMed Central

    2015-01-01

    Ewing sarcoma is a cancer of bone and soft tissue in children that is characterized by a chromosomal translocation involving EWS and an Ets family transcription factor, most commonly Fli-1. EWS-Fli-1 fusion accounts for 85% of cases. The growth and survival of Ewing sarcoma cells are critically dependent on EWS-Fli-1. A large body of evidence has established that EWS-Fli-1 functions as a DNA-binding transcription factor that regulates the expression of a number of genes important for cell proliferation and transformation. However, little is known about the biochemical properties of the EWS-Fli-1 protein. We undertook a series of proteomic analyses to dissect the EWS-Fli-1 interactome. Employing a proximity-dependent biotinylation technique, BioID, we identified cation-independent mannose 6-phosphate receptor (CIMPR) as a protein located in the vicinity of EWS-Fli-1 within a cell. CIMPR is a cargo that mediates the delivery of lysosomal hydrolases from the trans-Golgi network to the endosome, which are subsequently transferred to the lysosomes. Further molecular cell biological analyses uncovered a role for lysosomes in the turnover of the EWS-Fli-1 protein. We demonstrate that an mTORC1 active-site inhibitor, torin 1, which stimulates the TFEB-lysosome pathway, can induce the degradation of EWS-Fli-1, suggesting a potential therapeutic approach to target EWS-Fli-1 for degradation. PMID:24999758

  6. Interactome analysis of AMP-activated protein kinase (AMPK)-α1 and -β1 in INS-1 pancreatic beta-cells by affinity purification-mass spectrometry

    PubMed Central

    Moon, Sungyoon; Han, Dohyun; Kim, Yikwon; Jin, Jonghwa; Ho, Won-Kyung; Kim, Youngsoo

    2014-01-01

    The heterotrimeric enzyme AMP-activated protein kinase (AMPK) is a major metabolic factor that regulates the homeostasis of cellular energy. In particular, AMPK mediates the insulin resistance that is associated with type 2 diabetes. Generally, cellular processes require tight regulation of protein kinases, which is effected through their formation of complex with other proteins and substrates. Despite their critical function in regulation and pathogenesis, there are limited data on the interaction of protein kinases. To identify proteins that interact with AMPK, we performed large-scale affinity purification (AP)-mass spectrometry (MS) of the AMPK-α1 and -β1 subunits. Through a comprehensive analysis, using a combination of immunoprecipitaion and ion trap mass spectrometry, we identified 381 unique proteins in the AMPKα/β interactomes: 325 partners of AMPK-α1 and 243 for AMPK-β1. Further, we identified 196 novel protein-protein interactions with AMPK-α1 and AMPK-β1. Notably, in our bioinformatics analysis, the novel interaction partners mediated functions that are related to the regulation of actin organization. Specifically, several such proteins were linked to pancreatic beta-cell functions, including glucose-stimulated insulin secretion, beta-cell development, beta-cell differentiation, and cell-cell communication. PMID:24625528

  7. Diffusion of Information throughout the Host Interactome Reveals Gene Expression Variations in Network Proximity to Target Proteins of Hepatitis C Virus

    PubMed Central

    Milanesi, Luciano

    2014-01-01

    Hepatitis C virus infection is one of the most common and chronic in the world, and hepatitis associated with HCV infection is a major risk factor for the development of cirrhosis and hepatocellular carcinoma (HCC). The rapidly growing number of viral-host and host protein-protein interactions is enabling more and more reliable network-based analyses of viral infection supported by omics data. The study of molecular interaction networks helps to elucidate the mechanistic pathways linking HCV molecular activities and the host response that modulates the stepwise hepatocarcinogenic process from preneoplastic lesions (cirrhosis and dysplasia) to HCC. Simulating the impact of HCV-host molecular interactions throughout the host protein-protein interaction (PPI) network, we ranked the host proteins in relation to their network proximity to viral targets. We observed that the set of proteins in the neighborhood of HCV targets in the host interactome is enriched in key players of the host response to HCV infection. In opposition to HCV targets, subnetworks of proteins in network proximity to HCV targets are significantly enriched in proteins reported as differentially expressed in preneoplastic and neoplastic liver samples by two independent studies. Using multi-objective optimization, we extracted subnetworks that are simultaneously “guilt-by-association” with HCV proteins and enriched in proteins differentially expressed. These subnetworks contain established, recently proposed and novel candidate proteins for the regulation of the mechanisms of liver cells response to chronic HCV infection. PMID:25461596

  8. Quantitative proteomics of the yeast Hsp70/Hsp90 interactomes during DNA damage reveals chaperone-dependent regulation of ribonucleotide reductase

    PubMed Central

    Truman, Andrew W.; Kristjansdottir, Kolbrun; Wolfgeher, Donald; Ricco, Natalia; Mayampurath, Anoop; Volchenboum, Samuel L.; Clotet, Josep; Kron, Stephen J.

    2015-01-01

    The highly conserved molecular chaperones Hsp90 and Hsp70 are indispensible for folding and maturation of a significant fraction of the proteome, including many proteins involved in signal transduction and stress response. To examine the dynamics of chaperone-client interactions after DNA damage, we applied quantitative affinity-purification mass spectrometry (AP-MS) proteomics to characterize interactomes of the yeast Hsp70 isoform Ssa1 and Hsp90 isoform Hsp82 before and after exposure to methyl methanesulfonate. Of 256 proteins identified and quantified via 16O/18O labeling and LC-MS/MS, 142 are novel Hsp70/90 interactors. Nearly all interactions remained unchanged or decreased after DNA damage, but 5 proteins increased interactions with Ssa1 and/or Hsp82, including the ribonucleotide reductase (RNR) subunit Rnr4. Inhibiting Hsp70 or 90 chaperone activity destabilized Rnr4 in yeast and its vertebrate homolog hRMM2 in breast cancer cells. In turn, pre-treatment of cancer cells with chaperone inhibitors sensitized cells to the RNR inhibitor gemcitabine, suggesting a novel chemotherapy strategy. All MS data have been deposited in the ProteomeXchange with identifier PXD001284. PMID:25452130

  9. Spatiotemporal monthly rainfall forecasting for south-eastern and eastern Australia using climatic indices

    NASA Astrophysics Data System (ADS)

    Montazerolghaem, Maryam; Vervoort, Willem; Minasny, Budiman; McBratney, Alex

    2014-05-01

    Knowledge about future rainfall would significantly benefit land, water resources and agriculture management, as this assists with planning and management decisions. Forecasting spatiotemporal monthly rainfall is difficult, especially in Australia where there is a complex interaction between topography and the effect of Indian and Pacific Ocean. This study describes a method for spatiotemporal monthly rainfall forecasting in south-eastern and eastern part of Australia using climatic and non-climatic variables. Rainfall data were obtained from Bureau of Meteorology (BoM) from 136 high quality weather stations from the south-eastern and eastern part of Australia with monthly rainfall records from 1879 to 2012. To reduce spatial complexity of the area and improve model accuracy, spatial classification (regionalization) was considered as first step. Significant predictors for each sub-region among lagged climatic input variables were selected using Fuzzy Ranking Algorithm (FRA). Climate classification: 1) discovered homogenous sub-regions with a similar rainfall patterns and investigated spatiotemporal rainfall variations in the area, 2) allowed selection of significant predictors with a fine resolution for each area, 3) improved the prediction model and increased model accuracy. PCA was used to reduce the dimensions of the dataset and to remove the rainfall time series correlation. K-means clustering was used on the loadings of PCs describing 93% of long-term monthly rainfall variations. The analysis was repeated for different numbers of sub-regions (3 - 8) to identify the best number of clusters to improve the forecast model performance. Subsequently, a Fuzzy Ranking Algorithm (FRA) was applied to the lagged climatic predictors and monthly rainfall in each sub-region to identify the best predictors. After these two stages of pre-processing, a Neural Network model was developed and optimized for each of the sub-regions as well as for the entire area. It is concluded from the result of this study that climate classification can improve the result of monthly spatiotemporal rainfall forecast models in South-eastern and eastern Australia. Also, the number of sub-regions is one of the important parameters in ranking predictors at the modeling stage, and allows elucidation of climate influences for different sub regions. Classification of stations helps FRA to capture variations in Australian rainfall in space without influence of the rainfall seasonal cycle and regimes.

  10. A general science-based framework for dynamical spatio-temporal models

    USGS Publications Warehouse

    Wikle, C.K.; Hooten, M.B.

    2010-01-01

    Spatio-temporal statistical models are increasingly being used across a wide variety of scientific disciplines to describe and predict spatially-explicit processes that evolve over time. Correspondingly, in recent years there has been a significant amount of research on new statistical methodology for such models. Although descriptive models that approach the problem from the second-order (covariance) perspective are important, and innovative work is being done in this regard, many real-world processes are dynamic, and it can be more efficient in some cases to characterize the associated spatio-temporal dependence by the use of dynamical models. The chief challenge with the specification of such dynamical models has been related to the curse of dimensionality. Even in fairly simple linear, first-order Markovian, Gaussian error settings, statistical models are often over parameterized. Hierarchical models have proven invaluable in their ability to deal to some extent with this issue by allowing dependency among groups of parameters. In addition, this framework has allowed for the specification of science based parameterizations (and associated prior distributions) in which classes of deterministic dynamical models (e. g., partial differential equations (PDEs), integro-difference equations (IDEs), matrix models, and agent-based models) are used to guide specific parameterizations. Most of the focus for the application of such models in statistics has been in the linear case. The problems mentioned above with linear dynamic models are compounded in the case of nonlinear models. In this sense, the need for coherent and sensible model parameterizations is not only helpful, it is essential. Here, we present an overview of a framework for incorporating scientific information to motivate dynamical spatio-temporal models. First, we illustrate the methodology with the linear case. We then develop a general nonlinear spatio-temporal framework that we call general quadratic nonlinearity and demonstrate that it accommodates many different classes of scientific-based parameterizations as special cases. The model is presented in a hierarchical Bayesian framework and is illustrated with examples from ecology and oceanography. ?? 2010 Sociedad de Estad??stica e Investigaci??n Operativa.

  11. Hierarchical Bayesian spatio-temporal modeling and entropy-based network design

    NASA Astrophysics Data System (ADS)

    Wu, Y.; Jin, B.; Chan, E.

    2012-12-01

    Typical spatio-temporal data include temperature, precipitation, atmospheric pressure, ozone concentration, personal income, infection prevalence, mosquito populations, among others. To model such data in a given region by hierarchical Bayesian kriging is undertaken in this paper. In addition, an environmental network design problem is also explored. For demonstration, we consider the ozone concentrations in the Toronto region of Ontario, Canada. There are many missing observations in the data. To proceed, we first formulate the hierarchical spatio-temporal model in terms of observed data. We then fill in some missing observations such that the data has the staircase structure. Thus, in light of Le and Zidek (2006), we model the ozone concentrations in Toronto region by hierarchical Bayesian kriging and derive a conditional predictive distribution of the ozone concentrations over unknown locations. To decide if a new monitoring station needs to be added or an existing station can be closed down, we solve this environmental network design problem by using the principle of maximum entropy.

  12. Spatiotemporal Spike Coding of Behavioral Adaptation in the Dorsal Anterior Cingulate Cortex

    PubMed Central

    Logiaco, Laureline; Quilodran, René; Procyk, Emmanuel; Arleo, Angelo

    2015-01-01

    The frontal cortex controls behavioral adaptation in environments governed by complex rules. Many studies have established the relevance of firing rate modulation after informative events signaling whether and how to update the behavioral policy. However, whether the spatiotemporal features of these neuronal activities contribute to encoding imminent behavioral updates remains unclear. We investigated this issue in the dorsal anterior cingulate cortex (dACC) of monkeys while they adapted their behavior based on their memory of feedback from past choices. We analyzed spike trains of both single units and pairs of simultaneously recorded neurons using an algorithm that emulates different biologically plausible decoding circuits. This method permits the assessment of the performance of both spike-count and spike-timing sensitive decoders. In response to the feedback, single neurons emitted stereotypical spike trains whose temporal structure identified informative events with higher accuracy than mere spike count. The optimal decoding time scale was in the range of 70–200 ms, which is significantly shorter than the memory time scale required by the behavioral task. Importantly, the temporal spiking patterns of single units were predictive of the monkeys’ behavioral response time. Furthermore, some features of these spiking patterns often varied between jointly recorded neurons. All together, our results suggest that dACC drives behavioral adaptation through complex spatiotemporal spike coding. They also indicate that downstream networks, which decode dACC feedback signals, are unlikely to act as mere neural integrators. PMID:26266537

  13. Intrinsic Islet Heterogeneity and Gap Junction Coupling Determine Spatiotemporal Ca2+ Wave Dynamics

    PubMed Central

    Benninger, Richard K.P.; Hutchens, Troy; Head, W. Steven; McCaughey, Michael J.; Zhang, Min; Le Marchand, Sylvain J.; Satin, Leslie S.; Piston, David W.

    2014-01-01

    Insulin is released from the islets of Langerhans in discrete pulses that are linked to synchronized oscillations of intracellular free calcium ([Ca2+]i). Associated with each synchronized oscillation is a propagating calcium wave mediated by Connexin36 (Cx36) gap junctions. A computational islet model predicted that waves emerge due to heterogeneity in β-cell function throughout the islet. To test this, we applied defined patterns of glucose stimulation across the islet using a microfluidic device and measured how these perturbations affect calcium wave propagation. We further investigated how gap junction coupling regulates spatiotemporal [Ca2+]i dynamics in the face of heterogeneous glucose stimulation. Calcium waves were found to originate in regions of the islet having elevated excitability, and this heterogeneity is an intrinsic property of islet β-cells. The extent of [Ca2+]i elevation across the islet in the presence of heterogeneity is gap-junction dependent, which reveals a glucose dependence of gap junction coupling. To better describe these observations, we had to modify the computational islet model to consider the electrochemical gradient between neighboring β-cells. These results reveal how the spatiotemporal [Ca2+]i dynamics of the islet depend on β-cell heterogeneity and cell-cell coupling, and are important for understanding the regulation of coordinated insulin release across the islet. PMID:25468351

  14. Application of Geostatistical Methods and Machine Learning for spatio-temporal Earthquake Cluster Analysis

    NASA Astrophysics Data System (ADS)

    Schaefer, A. M.; Daniell, J. E.; Wenzel, F.

    2014-12-01

    Earthquake clustering tends to be an increasingly important part of general earthquake research especially in terms of seismic hazard assessment and earthquake forecasting and prediction approaches. The distinct identification and definition of foreshocks, aftershocks, mainshocks and secondary mainshocks is taken into account using a point based spatio-temporal clustering algorithm originating from the field of classic machine learning. This can be further applied for declustering purposes to separate background seismicity from triggered seismicity. The results are interpreted and processed to assemble 3D-(x,y,t) earthquake clustering maps which are based on smoothed seismicity records in space and time. In addition, multi-dimensional Gaussian functions are used to capture clustering parameters for spatial distribution and dominant orientations. Clusters are further processed using methodologies originating from geostatistics, which have been mostly applied and developed in mining projects during the last decades. A 2.5D variogram analysis is applied to identify spatio-temporal homogeneity in terms of earthquake density and energy output. The results are mitigated using Kriging to provide an accurate mapping solution for clustering features. As a case study, seismic data of New Zealand and the United States is used, covering events since the 1950s, from which an earthquake cluster catalogue is assembled for most of the major events, including a detailed analysis of the Landers and Christchurch sequences.

  15. Value-at-Risk forecasts by a spatiotemporal model in Chinese stock market

    NASA Astrophysics Data System (ADS)

    Gong, Pu; Weng, Yingliang

    2016-01-01

    This paper generalizes a recently proposed spatial autoregressive model and introduces a spatiotemporal model for forecasting stock returns. We support the view that stock returns are affected not only by the absolute values of factors such as firm size, book-to-market ratio and momentum but also by the relative values of factors like trading volume ranking and market capitalization ranking in each period. This article studies a new method for constructing stocks' reference groups; the method is called quartile method. Applying the method empirically to the Shanghai Stock Exchange 50 Index, we compare the daily volatility forecasting performance and the out-of-sample forecasting performance of Value-at-Risk (VaR) estimated by different models. The empirical results show that the spatiotemporal model performs surprisingly well in terms of capturing spatial dependences among individual stocks, and it produces more accurate VaR forecasts than the other three models introduced in the previous literature. Moreover, the findings indicate that both allowing for serial correlation in the disturbances and using time-varying spatial weight matrices can greatly improve the predictive accuracy of a spatial autoregressive model.

  16. Plastic response of fearful prey to the spatiotemporal dynamics of predator distribution.

    PubMed

    Basille, Mathieu; Fortin, Daniel; Dussault, Christian; Bastille-Rousseau, Guillaume; Ouellet, Jean-pierre; Courtois, Rthaume

    2015-10-01

    Ecological theory predicts that the intensity of antipredator responses is dependent upon the spatiotemporal context of predation risk (the risk allocation hypothesis). However, most studies to date have been conducted over small spatial extents, and did not fully take into account gradual responses to predator proximity. We simultaneously collected spatially explicit data on predator and prey to investigate acute responses of a threatened forest ungulate, the boreal caribou (Rangifer tarandus), to the spatiotemporal dynamics of wolf (Canis lupus) distribution during spring. Movement analysis of GPS-collared individuals from both species revealed high plasticity in habitat-selection decisions of caribou. Female caribou avoided open areas and deciduous forests and moved relatively fast and toward foraging areas when wolves were closer than 2.5 km. Caribou also avoided food-rich areas only when wolves were within 1 km. Our results bridge the gap between long-term perceived risk and immediate flight responses by revealing dynamic antipredator tactics in response to predator proximity. PMID:26649384

  17. The role of climate and socioeconomic factors on the spatiotemporal variability of cholera in Nigeria

    NASA Astrophysics Data System (ADS)

    Abdussalam, Auwal; Thornes, John; Leckebusch, Gregor

    2015-04-01

    Nigeria has a number of climate-sensitive infectious diseases; one of the most important of these diseases that remains a threat to public health is cholera. This study investigates the influences of both meteorological and socioeconomic factors on the spatiotemporal variability of cholera in Nigeria. A stepwise multiple regression models are used to estimate the influence of the year-to-year variations of cholera cases and deaths for individual states in the country and as well for three groups of states that are classified based on annual rainfall amount. Specifically, seasonal mean maximum and minimum temperatures and annual rainfall totals were analysed with annual aggregate count of cholera cases and deaths, taking into account of the socioeconomic factors that are potentially enhancing vulnerability such as: absolute poverty, adult literacy, access to pipe borne water and population density. Result reveals that the most important explanatory meteorological and socioeconomic variables in explaining the spatiotemporal variability of the disease are rainfall totals, seasonal mean maximum temperature, absolute poverty, and accessibility to pipe borne water. The influences of socioeconomic factors appeared to be more pronounced in the northern part of the country, and vice-versa in the case of meteorological factors. Also, cross validated models output suggests a strong possibility of disease prediction, which will help authorities to put effective control measures in place which depend on prevention, and or efficient response.

  18. Functional Principal Component Analysis of Spatio-Temporal Point Processes with Applications in Disease Surveillance

    PubMed Central

    Li, Yehua; Guan, Yongtao

    2014-01-01

    In disease surveillance applications, the disease events are modeled by spatio-temporal point processes. We propose a new class of semiparametric generalized linear mixed model for such data, where the event rate is related to some known risk factors and some unknown latent random effects. We model the latent spatio-temporal process as spatially correlated functional data, and propose Poisson maximum likelihood and composite likelihood methods based on spline approximations to estimate the mean and covariance functions of the latent process. By performing functional principal component analysis to the latent process, we can better understand the correlation structure in the point process. We also propose an empirical Bayes method to predict the latent spatial random effects, which can help highlight hot areas with unusually high event rates. Under an increasing domain and increasing knots asymptotic framework, we establish the asymptotic distribution for the parametric components in the model and the asymptotic convergence rates for the functional principal component estimators. We illustrate the methodology through a simulation study and an application to the Connecticut Tumor Registry data. PMID:25368436

  19. Predicting whole genome protein interaction networks from primary sequence data in model and non-model organisms using ENTS

    PubMed Central

    2013-01-01

    Background The large-scale identification of physical protein-protein interactions (PPIs) is an important step toward understanding how biological networks evolve and generate emergent phenotypes. However, experimental identification of PPIs is a laborious and error-prone process, and current methods of PPI prediction tend to be highly conservative or require large amounts of functional data that may not be available for newly-sequenced organisms. Results In this study we demonstrate a random-forest based technique, ENTS, for the computational prediction of protein-protein interactions based only on primary sequence data. Our approach is able to efficiently predict interactions on a whole-genome scale for any eukaryotic organism, using pairwise combinations of conserved domains and predicted subcellular localization of proteins as input features. We present the first predicted interactome for the forest tree Populus trichocarpa in addition to the predicted interactomes for Saccharomyces cerevisiae, Homo sapiens, Mus musculus, and Arabidopsis thaliana. Comparing our approach to other PPI predictors, we find that ENTS performs comparably to or better than a number of existing approaches, including several that utilize a variety of functional information for their predictions. We also find that the predicted interactions are biologically meaningful, as indicated by similarity in functional annotations and enrichment of co-expressed genes in public microarray datasets. Furthermore, we demonstrate some of the biological insights that can be gained from these predicted interaction networks. We show that the predicted interactions yield informative groupings of P. trichocarpa metabolic pathways, literature-supported associations among human disease states, and theory-supported insight into the evolutionary dynamics of duplicated genes in paleopolyploid plants. Conclusion We conclude that the ENTS classifier will be a valuable tool for the de novo annotation of genome sequences, providing initial clues about regulatory and metabolic network topology, and revealing relationships that are not immediately obvious from traditional homology-based annotations. PMID:24015873

  20. New model diagnostics for spatio-temporal systems in epidemiology and ecology

    PubMed Central

    Lau, Max S. Y.; Marion, Glenn; Streftaris, George; Gibson, Gavin J.

    2014-01-01

    A cardinal challenge in epidemiological and ecological modelling is to develop effective and easily deployed tools for model assessment. The availability of such methods would greatly improve understanding, prediction and management of disease and ecosystems. Conventional Bayesian model assessment tools such as Bayes factors and the deviance information criterion (DIC) are natural candidates but suffer from important limitations because of their sensitivity and complexity. Posterior predictive checks, which use summary statistics of the observed process simulated from competing models, can provide a measure of model fit but appropriate statistics can be difficult to identify. Here, we develop a novel approach for diagnosing mis-specifications of a general spatio-temporal transmission model by embedding classical ideas within a Bayesian analysis. Specifically, by proposing suitably designed non-centred parametrization schemes, we construct latent residuals whose sampling properties are known given the model specification and which can be used to measure overall fit and to elicit evidence of the nature of mis-specifications of spatial and temporal processes included in the model. This model assessment approach can readily be implemented as an addendum to standard estimation algorithms for sampling from the posterior distributions, for example Markov chain Monte Carlo. The proposed methodology is first tested using simulated data and subsequently applied to data describing the spread of Heracleum mantegazzianum (giant hogweed) across Great Britain over a 30-year period. The proposed methods are compared with alternative techniques including posterior predictive checking and the DIC. Results show that the proposed diagnostic tools are effective in assessing competing stochastic spatio-temporal transmission models and may offer improvements in power to detect model mis-specifications. Moreover, the latent-residual framework introduced here extends readily to a broad range of ecological and epidemiological models. PMID:24522782

  1. Spatiotemporal Coupling of the Tongue in Amyotrophic Lateral Sclerosis

    ERIC Educational Resources Information Center

    Kuruvilla, Mili S.; Green, Jordan R.; Yunusova, Yana; Hanford, Kathy

    2012-01-01

    Purpose: The primary aim of the investigation was to identify deficits in spatiotemporal coupling between tongue regions in amyotrophic lateral sclerosis (ALS). The relations between disease-related changes in tongue movement patterns and speech intelligibility were also determined. Methods: The authors recorded word productions from 11

  2. Robust visual tracking with dual spatio-temporal context trackers

    NASA Astrophysics Data System (ADS)

    Sun, Shiyan; Zhang, Hong; Yuan, Ding

    2015-12-01

    Visual tracking is a challenging problem in computer vision. Recent years, significant numbers of trackers have been proposed. Among these trackers, tracking with dense spatio-temporal context has been proved to be an efficient and accurate method. Other than trackers with online trained classifier that struggle to meet the requirement of real-time tracking task, a tracker with spatio-temporal context can run at hundreds of frames per second with Fast Fourier Transform (FFT). Nevertheless, the performance of the tracker with Spatio-temporal context relies heavily on the learning rate of the context, which restricts the robustness of the tracker. In this paper, we proposed a tracking method with dual spatio-temporal context trackers that hold different learning rate during tracking. The tracker with high learning rate could track the target smoothly when the appearance of target changes, while the tracker with low learning rate could percepts the occlusion occurring and continues to track when the target starts to emerge again. To find the target among the candidates from these two trackers, we adopt Normalized Correlation Coefficient (NCC) to evaluate the confidence of each sample. Experimental results show that the proposed algorithm performs robustly against several state-of-the-art tracking methods.

  3. Spatiotemporal modeling of irregularly spaced Aerosol Optical Depth data

    PubMed Central

    Oleson, Jacob J.; Kumar, Naresh; Smith, Brian J.

    2012-01-01

    Many advancements have been introduced to tackle spatial and temporal structures in data. When the spatial and/or temporal domains are relatively large, assumptions must be made to account for the sheer size of the data. The large data size, coupled with realities that come with observational data, make it difficult for all of these assumptions to be met. In particular, air quality data are very sparse across geographic space and time, due to a limited air pollution monitoring network. These “missing” values make it diffcult to incorporate most dimension reduction techniques developed for high-dimensional spatiotemporal data. This article examines aerosol optical depth (AOD), an indirect measure of radiative forcing, and air quality. The spatiotemporal distribution of AOD can be influenced by both natural (e.g., meteorological conditions) and anthropogenic factors (e.g., emission from industries and transport). After accounting for natural factors influencing AOD, we examine the spatiotemporal relationship in the remaining human influenced portion of AOD. The presented data cover a portion of India surrounding New Delhi from 2000 – 2006. The proposed method is demonstrated showing how it can handle the large spatiotemporal structure containing so much missing data for both meteorologic conditions and AOD over time and space. PMID:24470786

  4. Recovering metric properties of objects through spatiotemporal interpolation.

    PubMed

    Ghose, Tandra; Liu, Janelle; Kellman, Philip J

    2014-09-01

    Spatiotemporal interpolation (STI) refers to perception of complete objects from fragmentary information across gaps in both space and time. It differs from static interpolation in that requirements for interpolation are not met in any static frame. It has been found that STI produced objective performance advantages in a shape discrimination paradigm for both illusory and occluded objects when contours met conditions of spatiotemporal relatability. Here we report psychophysical studies testing whether spatiotemporal interpolation allows recovery of metric properties of objects. Observers viewed virtual triangles specified only by sequential partial occlusions of background elements by their vertices (the STI condition) and made forced choice judgments of the object's size relative to a reference standard. We found that length could often be accurately recovered for conditions where fragments were relatable and formed illusory triangles. In the first control condition, three moving dots located at the vertices provided the same spatial and timing information as the virtual object in the STI condition but did not induce perception of interpolated contours or a coherent object. In the second control condition oriented line segments were added to the dots and mid-points between the dots in a way that did not induce perception of interpolated contours. Control stimuli did not lead to accurate size judgments. We conclude that spatiotemporal interpolation can produce representations, from fragmentary information, of metric properties in addition to shape. PMID:25111311

  5. Finding Spatio-Temporal Patterns in Large Sensor Datasets

    ERIC Educational Resources Information Center

    McGuire, Michael Patrick

    2010-01-01

    Spatial or temporal data mining tasks are performed in the context of the relevant space, defined by a spatial neighborhood, and the relevant time period, defined by a specific time interval. Furthermore, when mining large spatio-temporal datasets, interesting patterns typically emerge where the dataset is most dynamic. This dissertation is

  6. Fast Spatio-Temporal Data Mining from Large Geophysical Datasets

    NASA Technical Reports Server (NTRS)

    Stolorz, P.; Mesrobian, E.; Muntz, R.; Santos, J. R.; Shek, E.; Yi, J.; Mechoso, C.; Farrara, J.

    1995-01-01

    Use of the UCLA CONQUEST (CONtent-based Querying in Space and Time) is reviewed for performance of automatic cyclone extraction and detection of spatio-temporal blocking conditions on MPP. CONQUEST is a data analysis environment for knowledge and data mining to aid in high-resolution modeling of climate modeling.

  7. Intelligence and Spatiotemporal Patterns of Event-Related Desynchronization (ERD).

    ERIC Educational Resources Information Center

    Neubauer, Aljoscha; And Others

    1995-01-01

    The relationship between psychometric intelligence, determined by Raven's Advanced Progressive Matrices, and spatiotemporal patterns of cortical activation, determined by quantifying event-related desynchronization, was studied in 17 college students. Findings support the hypothesis of a more efficient use of the brain in higher IQ individuals.…

  8. Spatio-Temporal Saliency Perception via Hypercomplex Frequency Spectral Contrast

    PubMed Central

    Li, Ce; Xue, Jianru; Zheng, Nanning; Lan, Xuguang; Tian, Zhiqiang

    2013-01-01

    Salient object perception is the process of sensing the salient information from the spatio-temporal visual scenes, which is a rapid pre-attention mechanism for the target location in a visual smart sensor. In recent decades, many successful models of visual saliency perception have been proposed to simulate the pre-attention behavior. Since most of the methods usually need some ad hoc parameters or high-cost preprocessing, they are difficult to rapidly detect salient object or be implemented by computing parallelism in a smart sensor. In this paper, we propose a novel spatio-temporal saliency perception method based on spatio-temporal hypercomplex spectral contrast (HSC). Firstly, the proposed HSC algorithm represent the features in the HSV (hue, saturation and value) color space and features of motion by a hypercomplex number. Secondly, the spatio-temporal salient objects are efficiently detected by hypercomplex Fourier spectral contrast in parallel. Finally, our saliency perception model also incorporates with the non-uniform sampling, which is a common phenomenon of human vision that directs visual attention to the logarithmic center of the image/video in natural scenes. The experimental results on the public saliency perception datasets demonstrate the effectiveness of the proposed approach compared to eleven state-of-the-art approaches. In addition, we extend the proposed model to moving object extraction in dynamic scenes, and the proposed algorithm is superior to the traditional algorithms. PMID:23482090

  9. Spatiotemporal Coupling of the Tongue in Amyotrophic Lateral Sclerosis

    ERIC Educational Resources Information Center

    Kuruvilla, Mili S.; Green, Jordan R.; Yunusova, Yana; Hanford, Kathy

    2012-01-01

    Purpose: The primary aim of the investigation was to identify deficits in spatiotemporal coupling between tongue regions in amyotrophic lateral sclerosis (ALS). The relations between disease-related changes in tongue movement patterns and speech intelligibility were also determined. Methods: The authors recorded word productions from 11…

  10. Spatio-temporal evaluation matrices for geospatial data

    NASA Astrophysics Data System (ADS)

    Triglav, Joc; Petrovič, Dušan; Stopar, Bojan

    2011-02-01

    The global geospatial community is investing substantial effort in providing tools for geospatial data-quality information analysis and systematizing the criteria for geospatial data quality. The importance of these activities is increasing, especially in the last decade, which has witnessed an enormous expansion of geospatial data use in general and especially among mass users. Although geospatial data producers are striving to define and present data-quality standards to users and users increasingly need to assess the fitness for use of the data, the success of these activities is still far from what is expected or required. As a consequence, neglect or misunderstanding of data quality among users results in misuse or risks. This paper presents an aid in spatio-temporal quality evaluation through the use of spatio-temporal evaluation matrices (STEM) and the index of spatio-temporal anticipations (INSTANT) matrices. With the help of these two simple tools, geospatial data producers can systematically categorize and visualize the granularity of their spatio-temporal data, and users can present their requirements in the same way using business intelligence principles and a Web 2.0 approach. The basic principles and some examples are presented in the paper, and potential further applied research activities are briefly described.

  11. Supporting user-defined granularities in a spatiotemporal conceptual model

    USGS Publications Warehouse

    Khatri, V.; Ram, S.; Snodgrass, R.T.; O'Brien, G. M.

    2002-01-01

    Granularities are integral to spatial and temporal data. A large number of applications require storage of facts along with their temporal and spatial context, which needs to be expressed in terms of appropriate granularities. For many real-world applications, a single granularity in the database is insufficient. In order to support any type of spatial or temporal reasoning, the semantics related to granularities needs to be embedded in the database. Specifying granularities related to facts is an important part of conceptual database design because under-specifying the granularity can restrict an application, affect the relative ordering of events and impact the topological relationships. Closely related to granularities is indeterminacy, i.e., an occurrence time or location associated with a fact that is not known exactly. In this paper, we present an ontology for spatial granularities that is a natural analog of temporal granularities. We propose an upward-compatible, annotation-based spatiotemporal conceptual model that can comprehensively capture the semantics related to spatial and temporal granularities, and indeterminacy without requiring new spatiotemporal constructs. We specify the formal semantics of this spatiotemporal conceptual model via translation to a conventional conceptual model. To underscore the practical focus of our approach, we describe an on-going case study. We apply our approach to a hydrogeologic application at the United States Geologic Survey and demonstrate that our proposed granularity-based spatiotemporal conceptual model is straightforward to use and is comprehensive.

  12. Location, Location, Location: Development of Spatiotemporal Sequence Learning in Infancy

    ERIC Educational Resources Information Center

    Kirkham, Natasha Z.; Slemmer, Jonathan A.; Richardson, Daniel C.; Johnson, Scott P.

    2007-01-01

    We investigated infants' sensitivity to spatiotemporal structure. In Experiment 1, circles appeared in a statistically defined spatial pattern. At test 11-month-olds, but not 8-month-olds, looked longer at a novel spatial sequence. Experiment 2 presented different color/shape stimuli, but only the location sequence was violated during test;…

  13. On the security of a spatiotemporal chaotic cryptosystem

    NASA Astrophysics Data System (ADS)

    Rhouma, Rhouma; Safya, Belghith

    2007-09-01

    Recently, Tang et al. [Phys Lett. A 318, 388 (2003)] proposed a spatiotemporal cryptosystem based on one-way coupled map lattices. They claim that it has high security, fast encryption speed, and short synchronization transient. This work proves that this scheme has some security weaknesses. Indeed, we propose an attack which the system cannot withstand.

  14. Spatiotemporal characterization of Sclerotinia crown rot epidemics in pyrethrum

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Sclerotinia crown rot, caused by Sclerotinia minor and S. sclerotiorum is a disease of pyrethrum in Australia that may cause substantial decline in plant density. The spatiotemporal characteristics of the disease were quantified in 14 fields spread across three growing seasons. Fitting the binary ...

  15. Spatiotemporal information during unsupervised learning enhances viewpoint invariant object recognition

    PubMed Central

    Tian, Moqian; Grill-Spector, Kalanit

    2015-01-01

    Recognizing objects is difficult because it requires both linking views of an object that can be different and distinguishing objects with similar appearance. Interestingly, people can learn to recognize objects across views in an unsupervised way, without feedback, just from the natural viewing statistics. However, there is intense debate regarding what information during unsupervised learning is used to link among object views. Specifically, researchers argue whether temporal proximity, motion, or spatiotemporal continuity among object views during unsupervised learning is beneficial. Here, we untangled the role of each of these factors in unsupervised learning of novel three-dimensional (3-D) objects. We found that after unsupervised training with 24 object views spanning a 180° view space, participants showed significant improvement in their ability to recognize 3-D objects across rotation. Surprisingly, there was no advantage to unsupervised learning with spatiotemporal continuity or motion information than training with temporal proximity. However, we discovered that when participants were trained with just a third of the views spanning the same view space, unsupervised learning via spatiotemporal continuity yielded significantly better recognition performance on novel views than learning via temporal proximity. These results suggest that while it is possible to obtain view-invariant recognition just from observing many views of an object presented in temporal proximity, spatiotemporal information enhances performance by producing representations with broader view tuning than learning via temporal association. Our findings have important implications for theories of object recognition and for the development of computational algorithms that learn from examples. PMID:26024454

  16. Nonequilibrium pattern formation and spatiotemporal chaos in fluid convection

    SciTech Connect

    Michael Cross

    2006-09-13

    The final report for grant number DE-FG03-98ER14891 summarizes the application of the unique simulation capabilities developed under DOE support to investigations of important issues in pattern formation and spatiotemporal chaos in Rayleigh-Benard convection, particularly emphasizing quantitative contact with the active experimental programs.

  17. Spatio-temporal Laplacian pyramid coding for action recognition.

    PubMed

    Shao, Ling; Zhen, Xiantong; Tao, Dacheng; Li, Xuelong

    2014-06-01

    We present a novel descriptor, called spatio-temporal Laplacian pyramid coding (STLPC), for holistic representation of human actions. In contrast to sparse representations based on detected local interest points, STLPC regards a video sequence as a whole with spatio-temporal features directly extracted from it, which prevents the loss of information in sparse representations. Through decomposing each sequence into a set of band-pass-filtered components, the proposed pyramid model localizes features residing at different scales, and therefore is able to effectively encode the motion information of actions. To make features further invariant and resistant to distortions as well as noise, a bank of 3-D Gabor filters is applied to each level of the Laplacian pyramid, followed by max pooling within filter bands and over spatio-temporal neighborhoods. Since the convolving and pooling are performed spatio-temporally, the coding model can capture structural and motion information simultaneously and provide an informative representation of actions. The proposed method achieves superb recognition rates on the KTH, the multiview IXMAS, the challenging UCF Sports, and the newly released HMDB51 datasets. It outperforms state of the art methods showing its great potential on action recognition. PMID:23912503

  18. Mapping and spatiotemporal analysis tool for hydrological data: Spellmap

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Lack of data management and analyses tools is one of the major limitations to effectively evaluate and use large datasets of high-resolution atmospheric, surface, and subsurface observations. High spatial and temporal resolution datasets better represent the spatiotemporal variability of hydrologica...

  19. Finding Spatio-Temporal Patterns in Large Sensor Datasets

    ERIC Educational Resources Information Center

    McGuire, Michael Patrick

    2010-01-01

    Spatial or temporal data mining tasks are performed in the context of the relevant space, defined by a spatial neighborhood, and the relevant time period, defined by a specific time interval. Furthermore, when mining large spatio-temporal datasets, interesting patterns typically emerge where the dataset is most dynamic. This dissertation is…

  20. Cubic map algebra functions for spatio-temporal analysis

    USGS Publications Warehouse

    Mennis, J.; Viger, R.; Tomlin, C.D.

    2005-01-01

    We propose an extension of map algebra to three dimensions for spatio-temporal data handling. This approach yields a new class of map algebra functions that we call "cube functions." Whereas conventional map algebra functions operate on data layers representing two-dimensional space, cube functions operate on data cubes representing two-dimensional space over a third-dimensional period of time. We describe the prototype implementation of a spatio-temporal data structure and selected cube function versions of conventional local, focal, and zonal map algebra functions. The utility of cube functions is demonstrated through a case study analyzing the spatio-temporal variability of remotely sensed, southeastern U.S. vegetation character over various land covers and during different El Nin??o/Southern Oscillation (ENSO) phases. Like conventional map algebra, the application of cube functions may demand significant data preprocessing when integrating diverse data sets, and are subject to limitations related to data storage and algorithm performance. Solutions to these issues include extending data compression and computing strategies for calculations on very large data volumes to spatio-temporal data handling.

  1. Kernel Averaged Predictors for Spatio-Temporal Regression Models.

    PubMed

    Heaton, Matthew J; Gelfand, Alan E

    2012-12-01

    In applications where covariates and responses are observed across space and time, a common goal is to quantify the effect of a change in the covariates on the response while adequately accounting for the spatio-temporal structure of the observations. The most common approach for building such a model is to confine the relationship between a covariate and response variable to a single spatio-temporal location. However, oftentimes the relationship between the response and predictors may extend across space and time. In other words, the response may be affected by levels of predictors in spatio-temporal proximity to the response location. Here, a flexible modeling framework is proposed to capture such spatial and temporal lagged effects between a predictor and a response. Specifically, kernel functions are used to weight a spatio-temporal covariate surface in a regression model for the response. The kernels are assumed to be parametric and non-stationary with the data informing the parameter values of the kernel. The methodology is illustrated on simulated data as well as a physical data set of ozone concentrations to be explained by temperature. PMID:24010051

  2. Online identification of nonlinear spatiotemporal systems using kernel learning approach.

    PubMed

    Ning, Hanwen; Jing, Xingjian; Cheng, Li

    2011-09-01

    The identification of nonlinear spatiotemporal systems is of significance to engineering practice, since it can always provide useful insight into the underlying nonlinear mechanism and physical characteristics under study. In this paper, nonlinear spatiotemporal system models are transformed into a class of multi-input-multi-output (MIMO) partially linear systems (PLSs), and an effective online identification algorithm is therefore proposed by using a pruning error minimization principle and least square support vector machines. It is shown that many benchmark physical and engineering systems can be transformed into MIMO-PLSs which keep some important physical spatiotemporal relationships and are very helpful in the identification and analysis of the underlying system. Compared with several existing methods, the advantages of the proposed method are that it can make full use of some prior structural information about system physical models, can realize online estimation of the system dynamics, and achieve accurate characterization of some important nonlinear physical characteristics of the system. This would provide an important basis for state estimation, control, optimal analysis, and design of nonlinear distributed parameter systems. The proposed algorithm can also be applied to identification problems of stochastic spatiotemporal dynamical systems. Numeral examples and comparisons are given to demonstrate our results. PMID:21788186

  3. Effects of spatiotemporal consistencies on visual learning dynamics and transfer.

    PubMed

    Harris, Hila; Sagi, Dov

    2015-04-01

    Spatiotemporal interactions affect visual performance under repeated stimulation conditions, showing both incremental (commonly related to learning) and decremental (possibly sensory adaptation) effects. Here we examined the role of spatiotemporal consistencies on learning dynamics and transfer. The backward-masked texture-discrimination paradigm was used, with stimulus onset asynchrony (SOA) controlling the observers' performance level. Temporal consistencies were examined by modifying the order in which SOA was varied during a training session: gradually reduced SOA (high consistencies) versus randomized SOA (low consistencies). Spatial consistencies were reduced by interleaving standard target trials with oriented 'dummy' trials containing only the background texture (no target, oriented 45° relative to the target's orientation). Our results showed reduced improvement following training with gradual SOA, as compared with random SOA. However, this difference was eliminated by randomizing SOA only at the initial and final segments of training, revealing a contaminating effect of temporal consistencies on threshold estimation rather than on learning. Inserting the 'dummy' trials (reduced spatial consistencies) facilitated both the learning and the subsequent transfer of learning, but only when sufficient pre-training was provided. These results indicate that visual sensitivity depends on a balance between two opposing processes, perceptual learning and sensory adaptation, both of which depend on spatiotemporal consistencies. Reducing spatiotemporal consistencies during training reduces the short-term spatiotemporal interactions that interfere with threshold estimation, learning, and generalization of learning. We consider the results within a theoretical framework, assuming an adaptable low-level network and a readout mechanism, with orientation and location-specific low-level adaptation interfering with the readout learning. PMID:25737285

  4. Spatiotemporal Analysis of Normal and Pathological Human Vocal Fold Vibrations

    PubMed Central

    Krausert, Christopher R.; Liang, Yufang; Zhang, Yu; Rieves, Adam L.; Geurink, Kyle R.; Jiang, Jack J.

    2012-01-01

    Purpose In order for spatiotemporal analysis to become a relevant clinical tool, it must be applied to human vocal fold vibration. Receiver operating characteristic (ROC) analysis will help assess the ability of spatiotemporal parameters to detect pathological vibration. Materials and Methods Spatiotemporal parameters of correlation length and entropy were extracted from high speed videos of 124 subjects, 67 without vocal fold pathology and 57 with either vocal fold polyps or nodules. Mann-Whitney rank sum tests were performed to compare normal vocal fold vibrations to pathological vibrations, and ROC analysis was used to assess the diagnostic value of spatiotemporal analysis. Results A statistically significant difference was found between the normal and pathological groups in both correlation length (P < 0.001) and entropy (P < 0.001). ROC analysis showed area under the curve (AUC) of 0.85 for correlation length, 0.87 for entropy, and 0.92 when the two parameters were combined. A statistically significant difference was not found between the nodules and polyps groups in either correlation length (P = 0.227) or entropy (P = 0.943). ROC analysis showed AUC of 0.63 for correlation length and 0.51 for entropy. Conclusions Although they could not effectively distinguish vibration of vocal folds with nodules from those with polyps, the spatiotemporal parameters correlation length and entropy exhibit the ability to differentiate normal and pathological vocal fold vibration, and may represent a diagnostic tool for objectively detecting abnormal vibration in the future, especially in neurological voice disorders and vocal folds without a visible lesion. PMID:22841342

  5. Spatio-temporal soil moisture distribution in a Maize field

    NASA Astrophysics Data System (ADS)

    Beff, Laure; Couvreur, Valentin; Javaux, Mathieu

    2010-05-01

    The spatio-temporal distribution of water content is important for predicting water flow and solute transport in the unsaturated zone. In a cropped field, this distribution is affected by the interception and redistribution of water by the plants, by surface runoff, by root water uptake, and by the distribution of soil hydraulic properties and boundary conditions of the system. This study was conducted to investigate the relationship between plant root water uptake, soil structure and flow field variability. An experimental plot in a Maize field was installed in July 2009 and measurements were performed between the 23 of July and the 21 of September 2009. Upper boundary conditions were followed with a weather station, while drainage was estimated with deep tensiometers (1.4 m). Four TDR profiles (14 TDR probes at 10, 30, 70 and 125 cm depth) perpendicular to two maize rows were monitored every hour. In addition, a square grid of 76 surface electrodes and 8 boreholes each with 7 electrodes (5, 15, 30, 50, 75, 105 and 140 cm deep) were inserted in the maize field to evaluate the 3-D distribution of the electrical conductivity by ERT. Weekly ERT measurements were performed. Subsequently, the ERT and TDR data were used to estimate the soil moisture dynamics based on petrophysical relationships. We performed root profiles at four times during the experiment to quantify the root distribution. This allowed us to investigate the relationship between plant root water uptake and soil moisture dynamics. After the growing season, a dye tracer experiment was conducted on a 1.4 m-side square, to assess the influence of roots and macropores in water infiltration. The results show the importance of using depth electrodes to estimate the vertical distribution of water content accurately. A high measurement resolution allowed us to observe the 3-D soil water content variability. During the growing season, we observed an increase in the coefficient of variation of soil water content when the soil becomes drier. This is in agreement with the results obtained by Hupet and Vanclooster (2005). Water dynamics in the topsoil was higher than in the lower layer. It seems that the distribution of water content at the end of the growing season was significantly influenced by the row / inter-row of maize and therefore by root water uptake. This highlights the importance of seeding patterns on soil moisture distribution in a field. Reference: F. Hupet and A. Vanclooster. Micro-variability of hydrological processes at the maize row scale: implications for soil water content measurements and evapotranspiration estimates. Journal Of Hydrology, 303(1-4):247-270, March 2005.

  6. Spatiotemporal Dynamics of Vibrio spp. within the Sydney Harbour Estuary

    PubMed Central

    Siboni, Nachshon; Balaraju, Varunan; Carney, Richard; Labbate, Maurizio; Seymour, Justin R.

    2016-01-01

    Vibrio are a genus of marine bacteria that have substantial environmental and human health importance, and there is evidence that their impact may be increasing as a consequence of changing environmental conditions. We investigated the abundance and composition of the Vibrio community within the Sydney Harbour estuary, one of the most densely populated coastal areas in Australia, and a region currently experiencing rapidly changing environmental conditions. Using quantitative PCR (qPCR) and Vibrio-specific 16S rRNA amplicon sequencing approaches we observed significant spatial and seasonal variation in the abundance and composition of the Vibrio community. Total Vibrio spp. abundance, derived from qPCR analysis, was higher during the late summer than winter and within locations with mid-range salinity (5–26 ppt). In addition we targeted three clinically important pathogens: Vibrio cholerae, V. Vulnificus, and V. parahaemolyticus. While toxigenic strains of V. cholerae were not detected in any samples, non-toxigenic strains were detected in 71% of samples, spanning a salinity range of 0–37 ppt and were observed during both late summer and winter. In contrast, pathogenic V. vulnificus was only detected in 14% of samples, with its occurrence restricted to the late summer and a salinity range of 5–26 ppt. V. parahaemolyticus was not observed at any site or time point. A Vibrio-specific 16S rRNA amplicon sequencing approach revealed clear shifts in Vibrio community composition across sites and between seasons, with several Vibrio operational taxonomic units (OTUs) displaying marked spatial patterns and seasonal trends. Shifts in the composition of the Vibrio community between seasons were primarily driven by changes in temperature, salinity and NO2, while a range of factors including pH, salinity, dissolved oxygen (DO) and NOx (Nitrogen Oxides) explained the observed spatial variation. Our evidence for the presence of a spatiotemporally dynamic Vibrio community within Sydney Harbour is notable given the high levels of human use of this waterway, and the significant increases in seawater temperature predicted for this region. PMID:27148171

  7. Using atmospheric observations to evaluate the spatiotemporal variability of CO2 fluxes simulated by terrestrial biospheric models

    NASA Astrophysics Data System (ADS)

    Fang, Y.; Michalak, A. M.; Shiga, Y. P.; Yadav, V.

    2014-06-01

    Terrestrial biospheric models (TBMs) are used to extrapolate local observations and process-level understanding of land-atmosphere carbon exchange to larger regions, and serve as a predictive tool for examining carbon-climate interactions. Understanding the performance of TBMs is thus crucial to the carbon cycle and climate science. In this study, we propose a statistical model selection approach for evaluating the spatiotemporal patterns of net ecosystem exchange (NEE) simulated by TBMs using atmospheric CO2 measurements. We find that current atmospheric observations are sensitive to the underlying spatiotemporal flux variability at sub-biome scales for a large portion of the North American continent, and that atmospheric observations can therefore be used to evaluate simulated spatiotemporal flux patterns, rather than focusing solely on flux magnitudes at aggregated scales. Results show that the proposed approach can be used to assess whether a TBM represents a substantial portion of the underlying flux variability as well as to differentiate among multiple competing TBMs. When applying the proposed approach to four prototypical TBMs, we find that the performance of TBMs varies substantially across seasons, with best performance during the growing season and limited skill during transition seasons. This seasonal difference in the ability of TBMs to represent the spatiotemporal flux variability may reflect the models' capability to represent the seasonally-varying influence of environmental drivers on fluxes. While none of the TBMs consistently outperforms the others, differences among the examined models are at least partially attributable to their internal structures. Overall, the proposed approach provides a new avenue for evaluating TBM performance based on sub-biome scale flux patterns, presenting an opportunity for assessing and informing model development using atmospheric observations.

  8. Asymmetric spatiotemporal chaos induced by a polypoid mass in the excised larynx

    NASA Astrophysics Data System (ADS)

    Zhang, Yu; Jiang, Jack J.

    2008-12-01

    In this paper, asymmetric spatiotemporal chaos induced by a polypoid mass simulating the laryngeal pathology of a vocal polyp is experimentally observed using high-speed imaging in an excised larynx. Spatiotemporal analysis reveals that the normal vocal folds show spatiotemporal correlation and symmetry. Normal vocal fold vibrations are dominated mainly by the first vibratory eigenmode. However, pathological vocal folds with a polypoid mass show broken symmetry and spatiotemporal irregularity. The spatial correlation is decreased. The pathological vocal folds spread vibratory energy across a large number of eigenmodes and induce asymmetric spatiotemporal chaos. High-order eigenmodes show complicated dynamics. Spatiotemporal analysis provides a valuable biomedical application for investigating the spatiotemporal chaotic dynamics of pathological vocal fold systems with a polypoid mass and may represent a valuable clinical tool for the detection of laryngeal mass lesion using high-speed imaging.

  9. catRAPID omics: a web server for large-scale prediction of protein–RNA interactions

    PubMed Central

    Agostini, Federico; Zanzoni, Andreas; Klus, Petr; Marchese, Domenica; Cirillo, Davide; Tartaglia, Gian Gaetano

    2013-01-01

    Summary: Here we introduce catRAPID omics, a server for large-scale calculations of protein–RNA interactions. Our web server allows (i) predictions at proteomic and transcriptomic level; (ii) use of protein and RNA sequences without size restriction; (iii) analysis of nucleic acid binding regions in proteins; and (iv) detection of RNA motifs involved in protein recognition. Results: We developed a web server to allow fast calculation of ribonucleoprotein associations in Caenorhabditis elegans, Danio rerio, Drosophila melanogaster, Homo sapiens, Mus musculus, Rattus norvegicus, Saccharomyces cerevisiae and Xenopus tropicalis (custom libraries can be also generated). The catRAPID omics was benchmarked on the recently published RNA interactomes of Serine/arginine-rich splicing factor 1 (SRSF1), Histone-lysine N-methyltransferase EZH2 (EZH2), TAR DNA-binding protein 43 (TDP43) and RNA-binding protein FUS (FUS) as well as on the protein interactomes of U1/U2 small nucleolar RNAs, X inactive specific transcript (Xist) repeat A region (RepA) and Crumbs homolog 3 (CRB3) 3′-untranslated region RNAs. Our predictions are highly significant (P < 0.05) and will help the experimentalist to identify candidates for further validation. Availability: catRAPID omics can be freely accessed on the Web at http://s.tartaglialab.com/catrapid/omics. Documentation, tutorial and FAQs are available at http://s.tartaglialab.com/page/catrapid_group. Contact: gian.tartaglia@crg.eu PMID:23975767

  10. MVL spatiotemporal analysis for model intercomparison in EPS: application to the DEMETER multi-model ensemble

    NASA Astrophysics Data System (ADS)

    Fernández, J.; Primo, C.; Cofiño, A. S.; Gutiérrez, J. M.; Rodríguez, M. A.

    2009-08-01

    In a recent paper, Gutiérrez et al. (Nonlinear Process Geophys 15(1):109-114, 2008) introduced a new characterization of spatiotemporal error growth—the so called mean-variance logarithmic (MVL) diagram—and applied it to study ensemble prediction systems (EPS); in particular, they analyzed single-model ensembles obtained by perturbing the initial conditions. In the present work, the MVL diagram is applied to multi-model ensembles analyzing also the effect of model formulation differences. To this aim, the MVL diagram is systematically applied to the multi-model ensemble produced in the EU-funded DEMETER project. It is shown that the shared building blocks (atmospheric and ocean components) impose similar dynamics among different models and, thus, contribute to poorly sampling the model formulation uncertainty. This dynamical similarity should be taken into account, at least as a pre-screening process, before applying any objective weighting method.

  11. Spatiotemporal Evolution of Erythema Migrans, the Hallmark Rash of Lyme Disease

    PubMed Central

    Vig, Dhruv K.; Wolgemuth, Charles W.

    2014-01-01

    To elucidate pathogen-host interactions during early Lyme disease, we developed a mathematical model that explains the spatiotemporal dynamics of the characteristic first sign of the disease, a large (≥5-cm diameter) rash, known as an erythema migrans. The model predicts that the bacterial replication and dissemination rates are the primary factors controlling the speed that the rash spreads, whereas the rate that active macrophages are cleared from the dermis is the principle determinant of rash morphology. In addition, the model supports the clinical observations that antibiotic treatment quickly clears spirochetes from the dermis and that the rash appearance is not indicative of the efficacy of the treatment. The quantitative agreement between our results and clinical data suggest that this model could be used to develop more efficient drug treatments and may form a basis for modeling pathogen-host interactions in other emerging infectious diseases. PMID:24507617

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

    SciTech Connect

    Uehara, Takeki; Minowa, Yohsuke; Morikawa, Yuji; Kondo, Chiaki; Maruyama, Toshiyuki; Kato, Ikuo; Nakatsu, Noriyuki; Igarashi, Yoshinobu; Ono, Atsushi; Hayashi, Hitomi; Mitsumori, Kunitoshi; Yamada, Hiroshi; Ohno, Yasuo; Urushidani, Tetsuro

    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% specificity 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.

  13. Challenges for modelling spatio-temporal variations of malaria risk in Malawi

    NASA Astrophysics Data System (ADS)

    Lowe, R.; Chirombo, J.; Tompkins, A. M.

    2012-04-01

    Malaria is the leading cause of morbidity and mortality in Malawi with more than 6 million episodes reported each year. Malaria poses a huge economic burden to Malawi in terms of the direct cost of treating malaria patients and also indirect costs resulting from workdays lost in agriculture and industry and absenteeism from school. Malawi implements malaria control activities within the Roll Back Malaria framework, with the objective to provide those most at risk (i.e. children under five years, pregnant woman and individuals with suppressed immune systems) access to personal and community protective measures. However, at present there is no mechanism by which to target the most 'at risk' populations ahead of an impending epidemic. Malaria transmission is influenced by variations in meteorological conditions, which impact the biology of the mosquito and the availability of breeding sites, but also socio-economic conditions such as levels of urbanisation, poverty and education, which influence human vulnerability and vector habitat. The many potential drivers of malaria, both extrinsic, such as climate, and intrinsic, such as population immunity are often difficult to disentangle. This presents a challenge for modelling of malaria risk in space and time. Using an age-stratified spatio-temporal dataset of malaria cases at the district level from July 2004 - June 2011, we use a spatio-temporal modelling framework to model variations in malaria risk in Malawi. Climatic and topographic variations are accounted for using an interpolation method to relate gridded products to administrative districts. District level data is tested in the model to account for confounding factors, including the proportion of the population living in urban areas; residing in traditional housing; with no toilet facilities; who do not attend school, etc, the number of health facilities per population and yearly estimates of insecticide-treated mosquito net distribution. In order to account for the unobserved confounding factors that influence malaria, which are not accounted for using measured covariates, a negative binomial generalised linear mixed model (GLMM) is adopted, which includes structured and unstructured spatial and temporal random effects. The parameters in this spatio-temporal Bayesian hierarchical model are estimated using Markov Chain Monte Carlo (MCMC). This allows posterior predictive distributions for disease risk to be derived for each spatial location and time period. A novel visualisation technique is then used to display seasonal probabilistic forecasts of malaria risk, derived from the developed model using pre-defined risk category thresholds, on a map. This technique allows decision makers to identify areas where the model predicts with certainty a particular malaria risk category (high, medium or low); in order to effectively target limited resources to those districts most at risk for a given season.

  14. Assessment of protein domain fusions in human protein interaction networks prediction: application to the human kinetochore model.

    PubMed

    Morilla, Ian; Lees, Jon G; Reid, Adam J; Orengo, Christine; Ranea, Juan A G

    2010-12-31

    In order to understand how biological systems function it is necessary to determine the interactions and associations between proteins. Some proteins, involved in a common biological process and encoded by separate genes in one organism, can be found fused within a single protein chain in other organisms. By detecting these triplets, a functional relationship can be established between the unfused proteins. Here we use a domain fusion prediction method to predict these protein interactions for the hu