Computational Modeling of Allosteric Regulation in the Hsp90 Chaperones: A Statistical Ensemble Analysis of Protein Structure Networks and Allosteric Communications

PubMed Central

Blacklock, Kristin; Verkhivker, Gennady M.

2014-01-01

A fundamental role of the Hsp90 chaperone in regulating functional activity of diverse protein clients is essential for the integrity of signaling networks. In this work we have combined biophysical simulations of the Hsp90 crystal structures with the protein structure network analysis to characterize the statistical ensemble of allosteric interaction networks and communication pathways in the Hsp90 chaperones. We have found that principal structurally stable communities could be preserved during dynamic changes in the conformational ensemble. The dominant contribution of the inter-domain rigidity to the interaction networks has emerged as a common factor responsible for the thermodynamic stability of the active chaperone form during the ATPase cycle. Structural stability analysis using force constant profiling of the inter-residue fluctuation distances has identified a network of conserved structurally rigid residues that could serve as global mediating sites of allosteric communication. Mapping of the conformational landscape with the network centrality parameters has demonstrated that stable communities and mediating residues may act concertedly with the shifts in the conformational equilibrium and could describe the majority of functionally significant chaperone residues. The network analysis has revealed a relationship between structural stability, global centrality and functional significance of hotspot residues involved in chaperone regulation. We have found that allosteric interactions in the Hsp90 chaperone may be mediated by modules of structurally stable residues that display high betweenness in the global interaction network. The results of this study have suggested that allosteric interactions in the Hsp90 chaperone may operate via a mechanism that combines rapid and efficient communication by a single optimal pathway of structurally rigid residues and more robust signal transmission using an ensemble of suboptimal multiple communication routes. This may be a universal requirement encoded in protein structures to balance the inherent tension between resilience and efficiency of the residue interaction networks. PMID:24922508

Computational modeling of allosteric regulation in the hsp90 chaperones: a statistical ensemble analysis of protein structure networks and allosteric communications.

PubMed

Blacklock, Kristin; Verkhivker, Gennady M

2014-06-01

A fundamental role of the Hsp90 chaperone in regulating functional activity of diverse protein clients is essential for the integrity of signaling networks. In this work we have combined biophysical simulations of the Hsp90 crystal structures with the protein structure network analysis to characterize the statistical ensemble of allosteric interaction networks and communication pathways in the Hsp90 chaperones. We have found that principal structurally stable communities could be preserved during dynamic changes in the conformational ensemble. The dominant contribution of the inter-domain rigidity to the interaction networks has emerged as a common factor responsible for the thermodynamic stability of the active chaperone form during the ATPase cycle. Structural stability analysis using force constant profiling of the inter-residue fluctuation distances has identified a network of conserved structurally rigid residues that could serve as global mediating sites of allosteric communication. Mapping of the conformational landscape with the network centrality parameters has demonstrated that stable communities and mediating residues may act concertedly with the shifts in the conformational equilibrium and could describe the majority of functionally significant chaperone residues. The network analysis has revealed a relationship between structural stability, global centrality and functional significance of hotspot residues involved in chaperone regulation. We have found that allosteric interactions in the Hsp90 chaperone may be mediated by modules of structurally stable residues that display high betweenness in the global interaction network. The results of this study have suggested that allosteric interactions in the Hsp90 chaperone may operate via a mechanism that combines rapid and efficient communication by a single optimal pathway of structurally rigid residues and more robust signal transmission using an ensemble of suboptimal multiple communication routes. This may be a universal requirement encoded in protein structures to balance the inherent tension between resilience and efficiency of the residue interaction networks.

Functional wiring of the yeast kinome revealed by global analysis of genetic network motifs

PubMed Central

Sharifpoor, Sara; van Dyk, Dewald; Costanzo, Michael; Baryshnikova, Anastasia; Friesen, Helena; Douglas, Alison C.; Youn, Ji-Young; VanderSluis, Benjamin; Myers, Chad L.; Papp, Balázs; Boone, Charles; Andrews, Brenda J.

2012-01-01

A combinatorial genetic perturbation strategy was applied to interrogate the yeast kinome on a genome-wide scale. We assessed the global effects of gene overexpression or gene deletion to map an integrated genetic interaction network of synthetic dosage lethal (SDL) and loss-of-function genetic interactions (GIs) for 92 kinases, producing a meta-network of 8700 GIs enriched for pathways known to be regulated by cognate kinases. Kinases most sensitive to dosage perturbations had constitutive cell cycle or cell polarity functions under standard growth conditions. Condition-specific screens confirmed that the spectrum of kinase dosage interactions can be expanded substantially in activating conditions. An integrated network composed of systematic SDL, negative and positive loss-of-function GIs, and literature-curated kinase–substrate interactions revealed kinase-dependent regulatory motifs predictive of novel gene-specific phenotypes. Our study provides a valuable resource to unravel novel functional relationships and pathways regulated by kinases and outlines a general strategy for deciphering mutant phenotypes from large-scale GI networks. PMID:22282571

A quantitative chaperone interaction network reveals the architecture of cellular protein homeostasis pathways

PubMed Central

Taipale, Mikko; Tucker, George; Peng, Jian; Krykbaeva, Irina; Lin, Zhen-Yuan; Larsen, Brett; Choi, Hyungwon; Berger, Bonnie; Gingras, Anne-Claude; Lindquist, Susan

2014-01-01

Chaperones are abundant cellular proteins that promote the folding and function of their substrate proteins (clients). In vivo, chaperones also associate with a large and diverse set of co-factors (co-chaperones) that regulate their specificity and function. However, how these co-chaperones regulate protein folding and whether they have chaperone-independent biological functions is largely unknown. We have combined mass spectrometry and quantitative high-throughput LUMIER assays to systematically characterize the chaperone/co-chaperone/client interaction network in human cells. We uncover hundreds of novel chaperone clients, delineate their participation in specific co-chaperone complexes, and establish a surprisingly distinct network of protein/protein interactions for co-chaperones. As a salient example of the power of such analysis, we establish that NUDC family co-chaperones specifically associate with structurally related but evolutionarily distinct β-propeller folds. We provide a framework for deciphering the proteostasis network, its regulation in development and disease, and expand the use of chaperones as sensors for drug/target engagement. PMID:25036637

Using protein-protein interactions for refining gene networks estimated from microarray data by Bayesian networks.

PubMed

Nariai, N; Kim, S; Imoto, S; Miyano, S

2004-01-01

We propose a statistical method to estimate gene networks from DNA microarray data and protein-protein interactions. Because physical interactions between proteins or multiprotein complexes are likely to regulate biological processes, using only mRNA expression data is not sufficient for estimating a gene network accurately. Our method adds knowledge about protein-protein interactions to the estimation method of gene networks under a Bayesian statistical framework. In the estimated gene network, a protein complex is modeled as a virtual node based on principal component analysis. We show the effectiveness of the proposed method through the analysis of Saccharomyces cerevisiae cell cycle data. The proposed method improves the accuracy of the estimated gene networks, and successfully identifies some biological facts.

Neural network regulation driven by autonomous neural firings

NASA Astrophysics Data System (ADS)

Cho, Myoung Won

2016-07-01

Biological neurons naturally fire spontaneously due to the existence of a noisy current. Such autonomous firings may provide a driving force for network formation because synaptic connections can be modified due to neural firings. Here, we study the effect of autonomous firings on network formation. For the temporally asymmetric Hebbian learning, bidirectional connections lose their balance easily and become unidirectional ones. Defining the difference between reciprocal connections as new variables, we could express the learning dynamics as if Ising model spins interact with each other in magnetism. We present a theoretical method to estimate the interaction between the new variables in a neural system. We apply the method to some network systems and find some tendencies of autonomous neural network regulation.

Regulatory network rewiring for secondary metabolism in Arabidopsis thaliana under various conditions

PubMed Central

2014-01-01

Background Plant secondary metabolites are critical to various biological processes. However, the regulations of these metabolites are complex because of regulatory rewiring or crosstalk. To unveil how regulatory behaviors on secondary metabolism reshape biological processes, we constructed and analyzed a dynamic regulatory network of secondary metabolic pathways in Arabidopsis. Results The dynamic regulatory network was constructed through integrating co-expressed gene pairs and regulatory interactions. Regulatory interactions were either predicted by conserved transcription factor binding sites (TFBSs) or proved by experiments. We found that integrating two data (co-expression and predicted regulatory interactions) enhanced the number of highly confident regulatory interactions by over 10% compared with using single data. The dynamic changes of regulatory network systematically manifested regulatory rewiring to explain the mechanism of regulation, such as in terpenoids metabolism, the regulatory crosstalk of RAV1 (AT1G13260) and ATHB1 (AT3G01470) on HMG1 (hydroxymethylglutaryl-CoA reductase, AT1G76490); and regulation of RAV1 on epoxysqualene biosynthesis and sterol biosynthesis. Besides, we investigated regulatory rewiring with expression, network topology and upstream signaling pathways. Regulatory rewiring was revealed by the variability of genes’ expression: pathway genes and transcription factors (TFs) were significantly differentially expressed under different conditions (such as terpenoids biosynthetic genes in tissue experiments and E2F/DP family members in genotype experiments). Both network topology and signaling pathways supported regulatory rewiring. For example, we discovered correlation among the numbers of pathway genes, TFs and network topology: one-gene pathways (such as δ-carotene biosynthesis) were regulated by a fewer TFs, and were not critical to metabolic network because of their low degrees in topology. Upstream signaling pathways of 50 TFs were identified to comprehend the underlying mechanism of TFs’ regulatory rewiring. Conclusion Overall, this dynamic regulatory network largely improves the understanding of perplexed regulatory rewiring in secondary metabolism in Arabidopsis. PMID:24993737

TP53 regulates miRNA association with AGO2 to remodel the miRNA-mRNA interaction network.

PubMed

Krell, Jonathan; Stebbing, Justin; Carissimi, Claudia; Dabrowska, Aleksandra F; de Giorgio, Alexander; Frampton, Adam E; Harding, Victoria; Fulci, Valerio; Macino, Giuseppe; Colombo, Teresa; Castellano, Leandro

2016-03-01

DNA damage activates TP53-regulated surveillance mechanisms that are crucial in suppressing tumorigenesis. TP53 orchestrates these responses directly by transcriptionally modulating genes, including microRNAs (miRNAs), and by regulating miRNA biogenesis through interacting with the DROSHA complex. However, whether the association between miRNAs and AGO2 is regulated following DNA damage is not yet known. Here, we show that, following DNA damage, TP53 interacts with AGO2 to induce or reduce AGO2's association of a subset of miRNAs, including multiple let-7 family members. Furthermore, we show that specific mutations in TP53 decrease rather than increase the association of let-7 family miRNAs, reducing their activity without preventing TP53 from interacting with AGO2. This is consistent with the oncogenic properties of these mutants. Using AGO2 RIP-seq and PAR-CLIP-seq, we show that the DNA damage-induced increase in binding of let-7 family members to the RISC complex is functional. We unambiguously determine the global miRNA-mRNA interaction networks involved in the DNA damage response, validating them through the identification of miRNA-target chimeras formed by endogenous ligation reactions. We find that the target complementary region of the let-7 seed tends to have highly fixed positions and more variable ones. Additionally, we observe that miRNAs, whose cellular abundance or differential association with AGO2 is regulated by TP53, are involved in an intricate network of regulatory feedback and feedforward circuits. TP53-mediated regulation of AGO2-miRNA interaction represents a new mechanism of miRNA regulation in carcinogenesis. © 2016 Krell et al.; Published by Cold Spring Harbor Laboratory Press.

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

PubMed

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

2011-11-01

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

A systems biology approach toward understanding seed composition in soybean.

PubMed

Li, Ling; Hur, Manhoi; Lee, Joon-Yong; Zhou, Wenxu; Song, Zhihong; Ransom, Nick; Demirkale, Cumhur Yusuf; Nettleton, Dan; Westgate, Mark; Arendsee, Zebulun; Iyer, Vidya; Shanks, Jackie; Nikolau, Basil; Wurtele, Eve Syrkin

2015-01-01

The molecular, biochemical, and genetic mechanisms that regulate the complex metabolic network of soybean seed development determine the ultimate balance of protein, lipid, and carbohydrate stored in the mature seed. Many of the genes and metabolites that participate in seed metabolism are unknown or poorly defined; even more remains to be understood about the regulation of their metabolic networks. A global omics analysis can provide insights into the regulation of seed metabolism, even without a priori assumptions about the structure of these networks. With the future goal of predictive biology in mind, we have combined metabolomics, transcriptomics, and metabolic flux technologies to reveal the global developmental and metabolic networks that determine the structure and composition of the mature soybean seed. We have coupled this global approach with interactive bioinformatics and statistical analyses to gain insights into the biochemical programs that determine soybean seed composition. For this purpose, we used Plant/Eukaryotic and Microbial Metabolomics Systems Resource (PMR, http://www.metnetdb.org/pmr, a platform that incorporates metabolomics data to develop hypotheses concerning the organization and regulation of metabolic networks, and MetNet systems biology tools http://www.metnetdb.org for plant omics data, a framework to enable interactive visualization of metabolic and regulatory networks. This combination of high-throughput experimental data and bioinformatics analyses has revealed sets of specific genes, genetic perturbations and mechanisms, and metabolic changes that are associated with the developmental variation in soybean seed composition. Researchers can explore these metabolomics and transcriptomics data interactively at PMR.

Genome-Scale Architecture of Small Molecule Regulatory Networks and the Fundamental Trade-Off between Regulation and Enzymatic Activity

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

Reznik, Ed; Christodoulou, Dimitris; Goldford, Joshua E.

Metabolic flux is in part regulated by endogenous small molecules that modulate the catalytic activity of an enzyme, e.g., allosteric inhibition. In contrast to transcriptional regulation of enzymes, technical limitations have hindered the production of a genome-scale atlas of small molecule-enzyme regulatory interactions. Here, we develop a framework leveraging the vast, but fragmented, biochemical literature to reconstruct and analyze the small molecule regulatory network (SMRN) of the model organism Escherichia coli, including the primary metabolite regulators and enzyme targets. Using metabolic control analysis, we prove a fundamental trade-off between regulation and enzymatic activity, and we combine it with metabolomic measurementsmore » and the SMRN to make inferences on the sensitivity of enzymes to their regulators. By generalizing the analysis to other organisms, we identify highly conserved regulatory interactions across evolutionarily divergent species, further emphasizing a critical role for small molecule interactions in the maintenance of metabolic homeostasis.« less

Genome-Scale Architecture of Small Molecule Regulatory Networks and the Fundamental Trade-Off between Regulation and Enzymatic Activity

DOE PAGES

Reznik, Ed; Christodoulou, Dimitris; Goldford, Joshua E.; ...

2017-09-12

Metabolic flux is in part regulated by endogenous small molecules that modulate the catalytic activity of an enzyme, e.g., allosteric inhibition. In contrast to transcriptional regulation of enzymes, technical limitations have hindered the production of a genome-scale atlas of small molecule-enzyme regulatory interactions. Here, we develop a framework leveraging the vast, but fragmented, biochemical literature to reconstruct and analyze the small molecule regulatory network (SMRN) of the model organism Escherichia coli, including the primary metabolite regulators and enzyme targets. Using metabolic control analysis, we prove a fundamental trade-off between regulation and enzymatic activity, and we combine it with metabolomic measurementsmore » and the SMRN to make inferences on the sensitivity of enzymes to their regulators. By generalizing the analysis to other organisms, we identify highly conserved regulatory interactions across evolutionarily divergent species, further emphasizing a critical role for small molecule interactions in the maintenance of metabolic homeostasis.« less

Extensive cross-talk and global regulators identified from an analysis of the integrated transcriptional and signaling network in Escherichia coli.

PubMed

Antiqueira, Lucas; Janga, Sarath Chandra; Costa, Luciano da Fontoura

2012-11-01

To understand the regulatory dynamics of transcription factors (TFs) and their interplay with other cellular components we have integrated transcriptional, protein-protein and the allosteric or equivalent interactions which mediate the physiological activity of TFs in Escherichia coli. To study this integrated network we computed a set of network measurements followed by principal component analysis (PCA), investigated the correlations between network structure and dynamics, and carried out a procedure for motif detection. In particular, we show that outliers identified in the integrated network based on their network properties correspond to previously characterized global transcriptional regulators. Furthermore, outliers are highly and widely expressed across conditions, thus supporting their global nature in controlling many genes in the cell. Motifs revealed that TFs not only interact physically with each other but also obtain feedback from signals delivered by signaling proteins supporting the extensive cross-talk between different types of networks. Our analysis can lead to the development of a general framework for detecting and understanding global regulatory factors in regulatory networks and reinforces the importance of integrating multiple types of interactions in underpinning the interrelationships between them.

Identification of the key regulating genes of diminished ovarian reserve (DOR) by network and gene ontology analysis.

PubMed

Pashaiasl, Maryam; Ebrahimi, Mansour; Ebrahimie, Esmaeil

2016-09-01

Diminished ovarian reserve (DOR) is one of the reasons for infertility that not only affects both older and young women. Ovarian reserve assessment can be used as a new prognostic tool for infertility treatment decision making. Here, up- and down-regulated gene expression profiles of granulosa cells were analysed to generate a putative interaction map of the involved genes. In addition, gene ontology (GO) analysis was used to get insight intol the biological processes and molecular functions of involved proteins in DOR. Eleven up-regulated genes and nine down-regulated genes were identified and assessed by constructing interaction networks based on their biological processes. PTGS2, CTGF, LHCGR, CITED, SOCS2, STAR and FSTL3 were the key nodes in the up-regulated networks, while the IGF2, AMH, GREM, and FOXC1 proteins were key in the down-regulated networks. MIRN101-1, MIRN153-1 and MIRN194-1 inhibited the expression of SOCS2, while CSH1 and BMP2 positively regulated IGF1 and IGF2. Ossification, ovarian follicle development, vasculogenesis, sequence-specific DNA binding transcription factor activity, and golgi apparatus are the major differential groups between up-regulated and down-regulated genes in DOR. Meta-analysis of publicly available transcriptomic data highlighted the high coexpression of CTGF, connective tissue growth factor, with the other key regulators of DOR. CTGF is involved in organ senescence and focal adhesion pathway according to GO analysis. These findings provide a comprehensive system biology based insight into the aetiology of DOR through network and gene ontology analyses.

Combining inferred regulatory and reconstructed metabolic networks enhances phenotype prediction in yeast.

PubMed

Wang, Zhuo; Danziger, Samuel A; Heavner, Benjamin D; Ma, Shuyi; Smith, Jennifer J; Li, Song; Herricks, Thurston; Simeonidis, Evangelos; Baliga, Nitin S; Aitchison, John D; Price, Nathan D

2017-05-01

Gene regulatory and metabolic network models have been used successfully in many organisms, but inherent differences between them make networks difficult to integrate. Probabilistic Regulation Of Metabolism (PROM) provides a partial solution, but it does not incorporate network inference and underperforms in eukaryotes. We present an Integrated Deduced And Metabolism (IDREAM) method that combines statistically inferred Environment and Gene Regulatory Influence Network (EGRIN) models with the PROM framework to create enhanced metabolic-regulatory network models. We used IDREAM to predict phenotypes and genetic interactions between transcription factors and genes encoding metabolic activities in the eukaryote, Saccharomyces cerevisiae. IDREAM models contain many fewer interactions than PROM and yet produce significantly more accurate growth predictions. IDREAM consistently outperformed PROM using any of three popular yeast metabolic models and across three experimental growth conditions. Importantly, IDREAM's enhanced accuracy makes it possible to identify subtle synthetic growth defects. With experimental validation, these novel genetic interactions involving the pyruvate dehydrogenase complex suggested a new role for fatty acid-responsive factor Oaf1 in regulating acetyl-CoA production in glucose grown cells.

Multi-disciplinary methods to define RNA-protein interactions and regulatory networks.

PubMed

Ascano, Manuel; Gerstberger, Stefanie; Tuschl, Thomas

2013-02-01

The advent of high-throughput technologies including deep-sequencing and protein mass spectrometry is facilitating the acquisition of large and precise data sets toward the definition of post-transcriptional regulatory networks. While early studies that investigated specific RNA-protein interactions in isolation laid the foundation for our understanding of the existence of molecular machines to assemble and process RNAs, there is a more recent appreciation of the importance of individual RNA-protein interactions that contribute to post-transcriptional gene regulation. The multitude of RNA-binding proteins (RBPs) and their many RNA targets has only been captured experimentally in recent times. In this review, we will examine current multidisciplinary approaches toward elucidating RNA-protein networks and their regulation. Copyright © 2013 Elsevier Ltd. All rights reserved.

Trainable Gene Regulation Networks with Applications to Drosophila Pattern Formation

NASA Technical Reports Server (NTRS)

Mjolsness, Eric

2000-01-01

This chapter will very briefly introduce and review some computational experiments in using trainable gene regulation network models to simulate and understand selected episodes in the development of the fruit fly, Drosophila melanogaster. For details the reader is referred to the papers introduced below. It will then introduce a new gene regulation network model which can describe promoter-level substructure in gene regulation. As described in chapter 2, gene regulation may be thought of as a combination of cis-acting regulation by the extended promoter of a gene (including all regulatory sequences) by way of the transcription complex, and of trans-acting regulation by the transcription factor products of other genes. If we simplify the cis-action by using a phenomenological model which can be tuned to data, such as a unit or other small portion of an artificial neural network, then the full transacting interaction between multiple genes during development can be modelled as a larger network which can again be tuned or trained to data. The larger network will in general need to have recurrent (feedback) connections since at least some real gene regulation networks do. This is the basic modeling approach taken, which describes how a set of recurrent neural networks can be used as a modeling language for multiple developmental processes including gene regulation within a single cell, cell-cell communication, and cell division. Such network models have been called "gene circuits", "gene regulation networks", or "genetic regulatory networks", sometimes without distinguishing the models from the actual modeled systems.

Comprehensive characterization of lncRNA-mRNA related ceRNA network across 12 major cancers

PubMed Central

Feng, Li; Li, Feng; Sun, Zeguo; Wu, Tan; Shi, Xinrui; Li, Jing; Li, Xia

2016-01-01

Recent studies indicate that long noncoding RNAs (lncRNAs) can act as competing endogenous RNAs (ceRNAs) to indirectly regulate mRNAs through shared microRNAs, which represents a novel layer of RNA crosstalk and plays critical roles in the development of tumor. However, the global regulation landscape and characterization of these lncRNA related ceRNA crosstalk in cancers is still largely unknown. Here, we systematically characterized the lncRNA related ceRNA interactions across 12 major cancers and the normal physiological states by integrating multidimensional molecule profiles of more than 5000 samples. Our study suggest the large difference of ceRNA regulation between normal and tumor states and the higher similarity across similar tissue origin of tumors. The ceRNA related molecules have more conserved features in tumor networks and they play critical roles in both the normal and tumorigenesis processes. Besides, lncRNAs in the pan-cancer ceRNA network may be potential biomarkers of tumor. By exploring hub lncRNAs, we found that these conserved key lncRNAs dominate variable tumor hallmark processes across pan-cancers. Network dynamic analysis highlights the critical roles of ceRNA regulation in tumorigenesis. By analyzing conserved ceRNA interactions, we found that miRNA mediate ceRNA regulation showed different patterns across pan-cancer; while analyzing the cancer specific ceRNA interactions reveal that lncRNAs synergistically regulated tumor driver genes of cancer hallmarks. Finally, we found that ceRNA modules have the potential to predict patient survival. Overall, our study systematically dissected the lncRNA related ceRNA networks in pan-cancer that shed new light on understanding the molecular mechanism of tumorigenesis. PMID:27580177

Differential Regulation of Cryptic Genetic Variation Shapes the Genetic Interactome Underlying Complex Traits.

PubMed

Yadav, Anupama; Dhole, Kaustubh; Sinha, Himanshu

2016-12-01

Cryptic genetic variation (CGV) refers to genetic variants whose effects are buffered in most conditions but manifest phenotypically upon specific genetic and environmental perturbations. Despite having a central role in adaptation, contribution of CGV to regulation of quantitative traits is unclear. Instead, a relatively simplistic architecture of additive genetic loci is known to regulate phenotypic variation in most traits. In this paper, we investigate the regulation of CGV and its implication on the genetic architecture of quantitative traits at a genome-wide level. We use a previously published dataset of biparental recombinant population of Saccharomyces cerevisiae phenotyped in 34 diverse environments to perform single locus, two-locus, and covariance mapping. We identify loci that have independent additive effects as well as those which regulate the phenotypic manifestation of other genetic variants (variance QTL). We find that whereas additive genetic variance is predominant, a higher order genetic interaction network regulates variation in certain environments. Despite containing pleiotropic loci, with effects across environments, these genetic networks are highly environment specific. CGV is buffered under most allelic combinations of these networks and perturbed only in rare combinations resulting in high phenotypic variance. The presence of such environment specific genetic networks is the underlying cause of abundant gene–environment interactions. We demonstrate that overlaying identified molecular networks on such genetic networks can identify potential candidate genes and underlying mechanisms regulating phenotypic variation. Such an integrated approach applied to human disease datasets has the potential to improve the ability to predict disease predisposition and identify specific therapeutic targets.

Differential Regulation of Cryptic Genetic Variation Shapes the Genetic Interactome Underlying Complex Traits

PubMed Central

Yadav, Anupama; Dhole, Kaustubh

2016-01-01

Cryptic genetic variation (CGV) refers to genetic variants whose effects are buffered in most conditions but manifest phenotypically upon specific genetic and environmental perturbations. Despite having a central role in adaptation, contribution of CGV to regulation of quantitative traits is unclear. Instead, a relatively simplistic architecture of additive genetic loci is known to regulate phenotypic variation in most traits. In this paper, we investigate the regulation of CGV and its implication on the genetic architecture of quantitative traits at a genome-wide level. We use a previously published dataset of biparental recombinant population of Saccharomyces cerevisiae phenotyped in 34 diverse environments to perform single locus, two-locus, and covariance mapping. We identify loci that have independent additive effects as well as those which regulate the phenotypic manifestation of other genetic variants (variance QTL). We find that whereas additive genetic variance is predominant, a higher order genetic interaction network regulates variation in certain environments. Despite containing pleiotropic loci, with effects across environments, these genetic networks are highly environment specific. CGV is buffered under most allelic combinations of these networks and perturbed only in rare combinations resulting in high phenotypic variance. The presence of such environment specific genetic networks is the underlying cause of abundant gene–environment interactions. We demonstrate that overlaying identified molecular networks on such genetic networks can identify potential candidate genes and underlying mechanisms regulating phenotypic variation. Such an integrated approach applied to human disease datasets has the potential to improve the ability to predict disease predisposition and identify specific therapeutic targets. PMID:28172852

Mitochondrial health, the epigenome and healthspan

PubMed Central

Aon, Miguel A.; Cortassa, Sonia; Juhaszova, Magdalena; Sollott, Steven J.

2016-01-01

Food nutrients and metabolic supply-demand dynamics constitute environmental factors that interact with our genome influencing health and disease states. These gene–environment interactions converge at the metabolic-epigenome-genome axis to regulate gene expression and phenotypic outcomes. Mounting evidence indicates that nutrients and lifestyle strongly influence genome-metabolic functional interactions determining disease via altered epigenetic regulation. The mitochondrial network is a central player of the metabolic-epigenome-genome axis, regulating the level of key metabolites (NAD+, AcCoA, ATP) acting as substrates/cofactors for acetyl transferases, kinases (e.g., protein kinase A), deacetylases (e.g., sirtuins). The chromatin, an assembly of DNA and nucleoproteins, regulates the transcriptional process, acting at the epigenomic interface between metabolism and the genome. Within this framework, we review existing evidence showing that preservation of mitochondrial network function is directly involved in decreasing the rate of damage accumulation thus slowing aging and improving healthspan. PMID:27358026

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

PubMed

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

2015-06-01

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

Understanding and Designing for Interactional Privacy Needs within Social Networking Sites

ERIC Educational Resources Information Center

Wisniewski, Pamela J.

2012-01-01

"Interpersonal boundary regulation" is a way to optimize social interactions when sharing and connecting through Social Networking Sites (SNSs). The theoretical foundation of much of my research comes from Altman's work on privacy management in the physical world. Altman believed that "we should attempt to design responsive…

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

PubMed

Mallik, Mrinmay Kumar

2018-02-07

Biological networks can be analyzed using "Centrality Analysis" to identify the more influential nodes and interactions in the network. This study was undertaken to create and visualize a biological network comprising of protein-protein interactions (PPIs) amongst proteins which are preferentially over-expressed in glioma cancer stem cell component (GCSC) of glioblastomas as compared to the glioma non-stem cancer cell (GNSC) component and then to analyze this network through centrality analyses (CA) in order to identify the essential proteins in this network and their interactions. In addition, this study proposes a new centrality analysis method pertaining exclusively to transcription factors (TFs) and interactions amongst them. Moreover the relevant molecular functions, biological processes and biochemical pathways amongst these proteins were sought through enrichment analysis. A protein interaction network was created using a list of proteins which have been shown to be preferentially expressed or over-expressed in GCSCs isolated from glioblastomas as compared to the GNSCs. This list comprising of 38 proteins, created using manual literature mining, was submitted to the Reactome FIViz tool, a web based application integrated into Cytoscape, an open source software platform for visualizing and analyzing molecular interaction networks and biological pathways to produce the network. This network was subjected to centrality analyses utilizing ranked lists of six centrality measures using the FIViz application and (for the first time) a dedicated centrality analysis plug-in ; CytoNCA. The interactions exclusively amongst the transcription factors were nalyzed through a newly proposed centrality analysis method called "Gene Expression Associated Degree Centrality Analysis (GEADCA)". Enrichment analysis was performed using the "network function analysis" tool on Reactome. The CA was able to identify a small set of proteins with consistently high centrality ranks that is indicative of their strong influence in the protein protein interaction network. Similarly the newly proposed GEADCA helped identify the transcription factors with high centrality values indicative of their key roles in transcriptional regulation. The enrichment studies provided a list of molecular functions, biological processes and biochemical pathways associated with the constructed network. The study shows how pathway based databases may be used to create and analyze a relevant protein interaction network in glioma cancer stem cells and identify the essential elements within it to gather insights into the molecular interactions that regulate the properties of glioma stem cells. How these insights may be utilized to help the development of future research towards formulation of new management strategies have been discussed from a theoretical standpoint. Copyright © 2017 Elsevier Ltd. All rights reserved.

Neuroimaging Study of Alpha and Beta EEG Biofeedback Effects on Neural Networks.

PubMed

Shtark, Mark B; Kozlova, Lyudmila I; Bezmaternykh, Dmitriy D; Mel'nikov, Mikhail Ye; Savelov, Andrey A; Sokhadze, Estate M

2018-06-01

Neural networks interaction was studied in healthy men (20-35 years old) who underwent 20 sessions of EEG biofeedback training outside the MRI scanner, with concurrent fMRI-EEG scans at the beginning, middle, and end of the course. The study recruited 35 subjects for EEG biofeedback, but only 18 of them were considered as "successful" in self-regulation of target EEG bands during the whole course of training. Results of fMRI analysis during EEG biofeedback are reported only for these "successful" trainees. The experimental group (N = 23 total, N = 13 "successful") upregulated the power of alpha rhythm, while the control group (N = 12 total, N = 5 "successful") beta rhythm, with the protocol instructions being as for alpha training in both. The acquisition of the stable skills of alpha self-regulation was followed by the weakening of the irrelevant links between the cerebellum and visuospatial network (VSN), as well as between the VSN, the right executive control network (RECN), and the cuneus. It was also found formation of a stable complex based on the interaction of the precuneus, the cuneus, the VSN, and the high level visuospatial network (HVN), along with the strengthening of the interaction of the anterior salience network (ASN) with the precuneus. In the control group, beta enhancement training was accompanied by weakening of interaction between the precuneus and the default mode network, and a decrease in connectivity between the cuneus and the primary visual network (PVN). The differences between the alpha training group and the control group increased successively during training. Alpha training was characterized by a less pronounced interaction of the network formed by the PVN and the HVN, as well as by an increased interaction of the cerebellum with the precuneus and the RECN. The study demonstrated the differences in the structure and interaction of neural networks involved into alpha and beta generating systems forming and functioning, which should be taken into account during planning neurofeedback interventions. Possibility of using fMRI-guided biofeedback organized according to the described neural networks interaction may advance more accurate targeting specific symptoms during neurotherapy.

Geometric control of capillary architecture via cell-matrix mechanical interactions.

PubMed

Sun, Jian; Jamilpour, Nima; Wang, Fei-Yue; Wong, Pak Kin

2014-03-01

Capillary morphogenesis is a multistage, multicellular activity that plays a pivotal role in various developmental and pathological situations. In-depth understanding of the regulatory mechanism along with the capability of controlling the morphogenic process will have direct implications on tissue engineering and therapeutic angiogenesis. Extensive research has been devoted to elucidate the biochemical factors that regulate capillary morphogenesis. The roles of geometric confinement and cell-matrix mechanical interactions on the capillary architecture, nevertheless, remain largely unknown. Here, we show geometric control of endothelial network topology by creating physical confinements with microfabricated fences and wells. Decreasing the thickness of the matrix also results in comparable modulation of the network architecture, supporting the boundary effect is mediated mechanically. The regulatory role of cell-matrix mechanical interaction on the network topology is further supported by alternating the matrix stiffness by a cell-inert PEG-dextran hydrogel. Furthermore, reducing the cell traction force with a Rho-associated protein kinase inhibitor diminishes the boundary effect. Computational biomechanical analysis delineates the relationship between geometric confinement and cell-matrix mechanical interaction. Collectively, these results reveal a mechanoregulation scheme of endothelial cells to regulate the capillary network architecture via cell-matrix mechanical interactions. Copyright © 2014 Elsevier Ltd. All rights reserved.

Topology and Control of the Cell-Cycle-Regulated Transcriptional Circuitry

PubMed Central

Haase, Steven B.; Wittenberg, Curt

2014-01-01

Nearly 20% of the budding yeast genome is transcribed periodically during the cell division cycle. The precise temporal execution of this large transcriptional program is controlled by a large interacting network of transcriptional regulators, kinases, and ubiquitin ligases. Historically, this network has been viewed as a collection of four coregulated gene clusters that are associated with each phase of the cell cycle. Although the broad outlines of these gene clusters were described nearly 20 years ago, new technologies have enabled major advances in our understanding of the genes comprising those clusters, their regulation, and the complex regulatory interplay between clusters. More recently, advances are being made in understanding the roles of chromatin in the control of the transcriptional program. We are also beginning to discover important regulatory interactions between the cell-cycle transcriptional program and other cell-cycle regulatory mechanisms such as checkpoints and metabolic networks. Here we review recent advances and contemporary models of the transcriptional network and consider these models in the context of eukaryotic cell-cycle controls. PMID:24395825

Screening of differentially expressed genes between multiple trauma patients with and without sepsis.

PubMed

Ji, S C; Pan, Y T; Lu, Q Y; Sun, Z Y; Liu, Y Z

2014-03-17

The purpose of this study was to identify critical genes associated with septic multiple trauma by comparing peripheral whole blood samples from multiple trauma patients with and without sepsis. A microarray data set was downloaded from the Gene Expression Omnibus (GEO) database. This data set included 70 samples, 36 from multiple trauma patients with sepsis and 34 from multiple trauma patients without sepsis (as a control set). The data were preprocessed, and differentially expressed genes (DEGs) were then screened for using packages of the R language. Functional analysis of DEGs was performed with DAVID. Interaction networks were then established for the most up- and down-regulated genes using HitPredict. Pathway-enrichment analysis was conducted for genes in the networks using WebGestalt. Fifty-eight DEGs were identified. The expression levels of PLAU (down-regulated) and MMP8 (up-regulated) presented the largest fold-changes, and interaction networks were established for these genes. Further analysis revealed that PLAT (plasminogen activator, tissue) and SERPINF2 (serpin peptidase inhibitor, clade F, member 2), which interact with PLAU, play important roles in the pathway of the component and coagulation cascade. We hypothesize that PLAU is a major regulator of the component and coagulation cascade, and down-regulation of PLAU results in dysfunction of the pathway, causing sepsis.

Systematical analysis of cutaneous squamous cell carcinoma network of microRNAs, transcription factors, and target and host genes.

PubMed

Wang, Ning; Xu, Zhi-Wen; Wang, Kun-Hao

2014-01-01

MicroRNAs (miRNAs) are small non-coding RNA molecules found in multicellular eukaryotes which are implicated in development of cancer, including cutaneous squamous cell carcinoma (cSCC). Expression is controlled by transcription factors (TFs) that bind to specific DNA sequences, thereby controlling the flow (or transcription) of genetic information from DNA to messenger RNA. Interactions result in biological signal control networks. Molecular components involved in cSCC were here assembled at abnormally expressed, related and global levels. Networks at these three levels were constructed with corresponding biological factors in term of interactions between miRNAs and target genes, TFs and miRNAs, and host genes and miRNAs. Up/down regulation or mutation of the factors were considered in the context of the regulation and significant patterns were extracted. Participants of the networks were evaluated based on their expression and regulation of other factors. Sub-networks with two core TFs, TP53 and EIF2C2, as the centers are identified. These share self-adapt feedback regulation in which a mutual restraint exists. Up or down regulation of certain genes and miRNAs are discussed. Some, for example the expression of MMP13, were in line with expectation while others, including FGFR3, need further investigation of their unexpected behavior. The present research suggests that dozens of components, miRNAs, TFs, target genes and host genes included, unite as networks through their regulation to function systematically in human cSCC. Networks built under the currently available sources provide critical signal controlling pathways and frequent patterns. Inappropriate controlling signal flow from abnormal expression of key TFs may push the system into an incontrollable situation and therefore contributes to cSCC development.

A Global Protein Kinase and Phosphatase Interaction Network in Yeast

PubMed Central

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

2011-01-01

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

APG: an Active Protein-Gene network model to quantify regulatory signals in complex biological systems.

PubMed

Wang, Jiguang; Sun, Yidan; Zheng, Si; Zhang, Xiang-Sun; Zhou, Huarong; Chen, Luonan

2013-01-01

Synergistic interactions among transcription factors (TFs) and their cofactors collectively determine gene expression in complex biological systems. In this work, we develop a novel graphical model, called Active Protein-Gene (APG) network model, to quantify regulatory signals of transcription in complex biomolecular networks through integrating both TF upstream-regulation and downstream-regulation high-throughput data. Firstly, we theoretically and computationally demonstrate the effectiveness of APG by comparing with the traditional strategy based only on TF downstream-regulation information. We then apply this model to study spontaneous type 2 diabetic Goto-Kakizaki (GK) and Wistar control rats. Our biological experiments validate the theoretical results. In particular, SP1 is found to be a hidden TF with changed regulatory activity, and the loss of SP1 activity contributes to the increased glucose production during diabetes development. APG model provides theoretical basis to quantitatively elucidate transcriptional regulation by modelling TF combinatorial interactions and exploiting multilevel high-throughput information.

APG: an Active Protein-Gene Network Model to Quantify Regulatory Signals in Complex Biological Systems

PubMed Central

Wang, Jiguang; Sun, Yidan; Zheng, Si; Zhang, Xiang-Sun; Zhou, Huarong; Chen, Luonan

2013-01-01

Synergistic interactions among transcription factors (TFs) and their cofactors collectively determine gene expression in complex biological systems. In this work, we develop a novel graphical model, called Active Protein-Gene (APG) network model, to quantify regulatory signals of transcription in complex biomolecular networks through integrating both TF upstream-regulation and downstream-regulation high-throughput data. Firstly, we theoretically and computationally demonstrate the effectiveness of APG by comparing with the traditional strategy based only on TF downstream-regulation information. We then apply this model to study spontaneous type 2 diabetic Goto-Kakizaki (GK) and Wistar control rats. Our biological experiments validate the theoretical results. In particular, SP1 is found to be a hidden TF with changed regulatory activity, and the loss of SP1 activity contributes to the increased glucose production during diabetes development. APG model provides theoretical basis to quantitatively elucidate transcriptional regulation by modelling TF combinatorial interactions and exploiting multilevel high-throughput information. PMID:23346354

Linking disease-associated genes to regulatory networks via promoter organization

PubMed Central

Döhr, S.; Klingenhoff, A.; Maier, H.; de Angelis, M. Hrabé; Werner, T.; Schneider, R.

2005-01-01

Pathway- or disease-associated genes may participate in more than one transcriptional co-regulation network. Such gene groups can be readily obtained by literature analysis or by high-throughput techniques such as microarrays or protein-interaction mapping. We developed a strategy that defines regulatory networks by in silico promoter analysis, finding potentially co-regulated subgroups without a priori knowledge. Pairs of transcription factor binding sites conserved in orthologous genes (vertically) as well as in promoter sequences of co-regulated genes (horizontally) were used as seeds for the development of promoter models representing potential co-regulation. This approach was applied to a Maturity Onset Diabetes of the Young (MODY)-associated gene list, which yielded two models connecting functionally interacting genes within MODY-related insulin/glucose signaling pathways. Additional genes functionally connected to our initial gene list were identified by database searches with these promoter models. Thus, data-driven in silico promoter analysis allowed integrating molecular mechanisms with biological functions of the cell. PMID:15701758

Role of the PDZ-scaffold protein NHERF1/EBP50 in cancer biology: from signaling regulation to clinical relevance.

PubMed

Vaquero, J; Nguyen Ho-Bouldoires, T H; Clapéron, A; Fouassier, L

2017-06-01

The transmission of cellular information requires fine and subtle regulation of proteins that need to interact in a coordinated and specific way to form efficient signaling networks. The spatial and temporal coordination relies on scaffold proteins. Thanks to protein interaction domains such as PDZ domains, scaffold proteins organize multiprotein complexes enabling the proper transmission of cellular information through intracellular networks. NHERF1/EBP50 is a PDZ-scaffold protein that was initially identified as an organizer and regulator of transporters and channels at the apical side of epithelia through actin-binding ezrin-moesin-radixin proteins. Since, NHERF1/EBP50 has emerged as a major regulator of cancer signaling network by assembling cancer-related proteins. The PDZ-scaffold EBP50 carries either anti-tumor or pro-tumor functions, two antinomic functions dictated by EBP50 expression or subcellular localization. The dual function of NHERF1/EBP50 encompasses the regulation of several major signaling pathways engaged in cancer, including the receptor tyrosine kinases PDGFR and EGFR, PI3K/PTEN/AKT and Wnt-β-catenin pathways.

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

NASA Astrophysics Data System (ADS)

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

2004-07-01

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

Mining disease genes using integrated protein-protein interaction and gene-gene co-regulation information.

PubMed

Li, Jin; Wang, Limei; Guo, Maozu; Zhang, Ruijie; Dai, Qiguo; Liu, Xiaoyan; Wang, Chunyu; Teng, Zhixia; Xuan, Ping; Zhang, Mingming

2015-01-01

In humans, despite the rapid increase in disease-associated gene discovery, a large proportion of disease-associated genes are still unknown. Many network-based approaches have been used to prioritize disease genes. Many networks, such as the protein-protein interaction (PPI), KEGG, and gene co-expression networks, have been used. Expression quantitative trait loci (eQTLs) have been successfully applied for the determination of genes associated with several diseases. In this study, we constructed an eQTL-based gene-gene co-regulation network (GGCRN) and used it to mine for disease genes. We adopted the random walk with restart (RWR) algorithm to mine for genes associated with Alzheimer disease. Compared to the Human Protein Reference Database (HPRD) PPI network alone, the integrated HPRD PPI and GGCRN networks provided faster convergence and revealed new disease-related genes. Therefore, using the RWR algorithm for integrated PPI and GGCRN is an effective method for disease-associated gene mining.

Joining the dots - protein-RNA interactions mediating local mRNA translation in neurons.

PubMed

Gallagher, Christopher; Ramos, Andres

2018-06-01

Establishing and maintaining the complex network of connections required for neuronal communication requires the transport and in situ translation of large groups of mRNAs to create local proteomes. In this Review, we discuss the regulation of local mRNA translation in neurons and the RNA-binding proteins that recognise RNA zipcode elements and connect the mRNAs to the cellular transport networks, as well as regulate their translation control. However, mRNA recognition by the regulatory proteins is mediated by the combinatorial action of multiple RNA-binding domains. This increases the specificity and affinity of the interaction, while allowing the protein to recognise a diverse set of targets and mediate a range of mechanisms for translational regulation. The structural and molecular understanding of the interactions can be used together with novel microscopy and transcriptome-wide data to build a mechanistic framework for the regulation of local mRNA translation. © 2018 Federation of European Biochemical Societies.

Modeling transcriptional networks regulating secondary growth and wood formation in forest trees

Treesearch

Lijun Liu; Vladimir Filkov; Andrew Groover

2013-01-01

The complex interactions among the genes that underlie a biological process can be modeled and presented as a transcriptional network, in which genes (nodes) and their interactions (edges) are shown in a graphical form similar to a wiring diagram. A large number of genes have been identified that are expressed during the radial woody growth of tree stems (secondary...

MIR@NT@N: a framework integrating transcription factors, microRNAs and their targets to identify sub-network motifs in a meta-regulation network model

PubMed Central

2011-01-01

Background To understand biological processes and diseases, it is crucial to unravel the concerted interplay of transcription factors (TFs), microRNAs (miRNAs) and their targets within regulatory networks and fundamental sub-networks. An integrative computational resource generating a comprehensive view of these regulatory molecular interactions at a genome-wide scale would be of great interest to biologists, but is not available to date. Results To identify and analyze molecular interaction networks, we developed MIR@NT@N, an integrative approach based on a meta-regulation network model and a large-scale database. MIR@NT@N uses a graph-based approach to predict novel molecular actors across multiple regulatory processes (i.e. TFs acting on protein-coding or miRNA genes, or miRNAs acting on messenger RNAs). Exploiting these predictions, the user can generate networks and further analyze them to identify sub-networks, including motifs such as feedback and feedforward loops (FBL and FFL). In addition, networks can be built from lists of molecular actors with an a priori role in a given biological process to predict novel and unanticipated interactions. Analyses can be contextualized and filtered by integrating additional information such as microarray expression data. All results, including generated graphs, can be visualized, saved and exported into various formats. MIR@NT@N performances have been evaluated using published data and then applied to the regulatory program underlying epithelium to mesenchyme transition (EMT), an evolutionary-conserved process which is implicated in embryonic development and disease. Conclusions MIR@NT@N is an effective computational approach to identify novel molecular regulations and to predict gene regulatory networks and sub-networks including conserved motifs within a given biological context. Taking advantage of the M@IA environment, MIR@NT@N is a user-friendly web resource freely available at http://mironton.uni.lu which will be updated on a regular basis. PMID:21375730

The network organization of protein interactions in the spliceosome is reproduced by the simple rules of food-web models

PubMed Central

Pires, Mathias M.; Cantor, Maurício; Guimarães, Paulo R.; de Aguiar, Marcus A. M.; dos Reis, Sérgio F.; Coltri, Patricia P.

2015-01-01

The network structure of biological systems provides information on the underlying processes shaping their organization and dynamics. Here we examined the structure of the network depicting protein interactions within the spliceosome, the macromolecular complex responsible for splicing in eukaryotic cells. We show the interactions of less connected spliceosome proteins are nested subsets of the connections of the highly connected proteins. At the same time, the network has a modular structure with groups of proteins sharing similar interaction patterns. We then investigated the role of affinity and specificity in shaping the spliceosome network by adapting a probabilistic model originally designed to reproduce food webs. This food-web model was as successful in reproducing the structure of protein interactions as it is in reproducing interactions among species. The good performance of the model suggests affinity and specificity, partially determined by protein size and the timing of association to the complex, may be determining network structure. Moreover, because network models allow building ensembles of realistic networks while encompassing uncertainty they can be useful to examine the dynamics and vulnerability of intracelullar processes. Unraveling the mechanisms organizing the spliceosome interactions is important to characterize the role of individual proteins on splicing catalysis and regulation. PMID:26443080

Subgenual anterior cingulate cortex controls sadness-induced modulations of cognitive and emotional network hubs.

PubMed

Ramirez-Mahaluf, Juan P; Perramon, Joan; Otal, Begonya; Villoslada, Pablo; Compte, Albert

2018-06-04

The regulation of cognitive and emotional processes is critical for proper executive functions and social behavior, but its specific mechanisms remain unknown. Here, we addressed this issue by studying with functional magnetic resonance imaging the changes in network topology that underlie competitive interactions between emotional and cognitive networks in healthy participants. Our behavioral paradigm contrasted periods with high emotional and cognitive demands by including a sadness provocation task followed by a spatial working memory task. The sharp contrast between successive tasks was designed to enhance the separability of emotional and cognitive networks and reveal areas that regulate the flow of information between them (hubs). By applying graph analysis methods on functional connectivity between 20 regions of interest in 22 participants we identified two main brain network modules, one dorsal and one ventral, and their hub areas: the left dorsolateral prefrontal cortex (dlPFC) and the left medial frontal pole (mFP). These hub areas did not modulate their mutual functional connectivity following sadness but they did so through an interposed area, the subgenual anterior cingulate cortex (sACC). Our results identify dlPFC and mFP as areas regulating interactions between emotional and cognitive networks, and suggest that their modulation by sadness experience is mediated by sACC.

Prediction of C. elegans Longevity Genes by Human and Worm Longevity Networks

PubMed Central

de Magalhães, João Pedro; Ruvkun, Gary; Fraifeld, Vadim E.; Curran, Sean P.

2012-01-01

Intricate and interconnected pathways modulate longevity, but screens to identify the components of these pathways have not been saturating. Because biological processes are often executed by protein complexes and fine-tuned by regulatory factors, the first-order protein-protein interactors of known longevity genes are likely to participate in the regulation of longevity. Data-rich maps of protein interactions have been established for many cardinal organisms such as yeast, worms, and humans. We propose that these interaction maps could be mined for the identification of new putative regulators of longevity. For this purpose, we have constructed longevity networks in both humans and worms. We reasoned that the essential first-order interactors of known longevity-associated genes in these networks are more likely to have longevity phenotypes than randomly chosen genes. We have used C. elegans to determine whether post-developmental inactivation of these essential genes modulates lifespan. Our results suggest that the worm and human longevity networks are functionally relevant and possess a high predictive power for identifying new longevity regulators. PMID:23144747

Identification of Unstable Network Modules Reveals Disease Modules Associated with the Progression of Alzheimer’s Disease

PubMed Central

Kikuchi, Masataka; Ogishima, Soichi; Miyamoto, Tadashi; Miyashita, Akinori; Kuwano, Ryozo; Nakaya, Jun; Tanaka, Hiroshi

2013-01-01

Alzheimer’s disease (AD), the most common cause of dementia, is associated with aging, and it leads to neuron death. Deposits of amyloid β and aberrantly phosphorylated tau protein are known as pathological hallmarks of AD, but the underlying mechanisms have not yet been revealed. A high-throughput gene expression analysis previously showed that differentially expressed genes accompanying the progression of AD were more down-regulated than up-regulated in the later stages of AD. This suggested that the molecular networks and their constituent modules collapsed along with AD progression. In this study, by using gene expression profiles and protein interaction networks (PINs), we identified the PINs expressed in three brain regions: the entorhinal cortex (EC), hippocampus (HIP) and superior frontal gyrus (SFG). Dividing the expressed PINs into modules, we examined the stability of the modules with AD progression and with normal aging. We found that in the AD modules, the constituent proteins, interactions and cellular functions were not maintained between consecutive stages through all brain regions. Interestingly, the modules were collapsed with AD progression, specifically in the EC region. By identifying the modules that were affected by AD pathology, we found the transcriptional regulation-associated modules that interact with the proteasome-associated module via UCHL5 hub protein, which is a deubiquitinating enzyme. Considering PINs as a system made of network modules, we found that the modules relevant to the transcriptional regulation are disrupted in the EC region, which affects the ubiquitin-proteasome system. PMID:24348898

Context-dependent interactions and the regulation of species richness in freshwater fish.

PubMed

MacDougall, Andrew S; Harvey, Eric; McCune, Jenny L; Nilsson, Karin A; Bennett, Joseph; Firn, Jennifer; Bartley, Timothy; Grace, James B; Kelly, Jocelyn; Tunney, Tyler D; McMeans, Bailey; Matsuzaki, Shin-Ichiro S; Kadoya, Taku; Esch, Ellen; Cazelles, Kevin; Lester, Nigel; McCann, Kevin S

2018-03-06

Species richness is regulated by a complex network of scale-dependent processes. This complexity can obscure the influence of limiting species interactions, making it difficult to determine if abiotic or biotic drivers are more predominant regulators of richness. Using integrative modeling of freshwater fish richness from 721 lakes along an 11 o latitudinal gradient, we find negative interactions to be a relatively minor independent predictor of species richness in lakes despite the widespread presence of predators. Instead, interaction effects, when detectable among major functional groups and 231 species pairs, were strong, often positive, but contextually dependent on environment. These results are consistent with the idea that negative interactions internally structure lake communities but do not consistently 'scale-up' to regulate richness independently of the environment. The importance of environment for interaction outcomes and its role in the regulation of species richness highlights the potential sensitivity of fish communities to the environmental changes affecting lakes globally.

Context-dependent interactions and the regulation of species richness in freshwater fish

USGS Publications Warehouse

MacDougall, Andrew S.; Harvey, Eric; McCune, Jenny L.; Nilsson, Karin A.; Bennett, Joseph; Firn, Jennifer; Bartley, Timothy; Grace, James B.; Kelly, Jocelyn; Tunney, Tyler D.; McMeans, Bailey; Matsuzaki, Shin-Ichiro S.; Kadoya, Taku; Esch, Ellen; Cazelles, Kevin; Lester, Nigel; McCann, Kevin S.

2018-01-01

Species richness is regulated by a complex network of scale-dependent processes. This complexity can obscure the influence of limiting species interactions, making it difficult to determine if abiotic or biotic drivers are more predominant regulators of richness. Using integrative modeling of freshwater fish richness from 721 lakes along an 11olatitudinal gradient, we find negative interactions to be a relatively minor independent predictor of species richness in lakes despite the widespread presence of predators. Instead, interaction effects, when detectable among major functional groups and 231 species pairs, were strong, often positive, but contextually dependent on environment. These results are consistent with the idea that negative interactions internally structure lake communities but do not consistently ‘scale-up’ to regulate richness independently of the environment. The importance of environment for interaction outcomes and its role in the regulation of species richness highlights the potential sensitivity of fish communities to the environmental changes affecting lakes globally.

Reconstructing directed gene regulatory network by only gene expression data.

PubMed

Zhang, Lu; Feng, Xi Kang; Ng, Yen Kaow; Li, Shuai Cheng

2016-08-18

Accurately identifying gene regulatory network is an important task in understanding in vivo biological activities. The inference of such networks is often accomplished through the use of gene expression data. Many methods have been developed to evaluate gene expression dependencies between transcription factor and its target genes, and some methods also eliminate transitive interactions. The regulatory (or edge) direction is undetermined if the target gene is also a transcription factor. Some methods predict the regulatory directions in the gene regulatory networks by locating the eQTL single nucleotide polymorphism, or by observing the gene expression changes when knocking out/down the candidate transcript factors; regrettably, these additional data are usually unavailable, especially for the samples deriving from human tissues. In this study, we propose the Context Based Dependency Network (CBDN), a method that is able to infer gene regulatory networks with the regulatory directions from gene expression data only. To determine the regulatory direction, CBDN computes the influence of source to target by evaluating the magnitude changes of expression dependencies between the target gene and the others with conditioning on the source gene. CBDN extends the data processing inequality by involving the dependency direction to distinguish between direct and transitive relationship between genes. We also define two types of important regulators which can influence a majority of the genes in the network directly or indirectly. CBDN can detect both of these two types of important regulators by averaging the influence functions of candidate regulator to the other genes. In our experiments with simulated and real data, even with the regulatory direction taken into account, CBDN outperforms the state-of-the-art approaches for inferring gene regulatory network. CBDN identifies the important regulators in the predicted network: 1. TYROBP influences a batch of genes that are related to Alzheimer's disease; 2. ZNF329 and RB1 significantly regulate those 'mesenchymal' gene expression signature genes for brain tumors. By merely leveraging gene expression data, CBDN can efficiently infer the existence of gene-gene interactions as well as their regulatory directions. The constructed networks are helpful in the identification of important regulators for complex diseases.

Regulation Mechanism of Salt Ions for Superlubricity of Hydrophilic Polymer Cross-Linked Networks on Ti6Al4V.

PubMed

Zhang, Caixia; Liu, Yuhong; Liu, Zhifeng; Zhang, Hongyu; Cheng, Qiang; Yang, Congbin

2017-03-07

Poly(vinylphosphonic acid) (PVPA) cross-linked networks on Ti 6 Al 4 V show superlubricity behavior when sliding against polytetrafluoroethylene in water-based lubricants. The superlubricity can occur but only with the existence of salt ions in the polymer cross-linked networks. This is different from the phenomenon in most polymer brushes. An investigation into the mechanism revealed that cations and anions in the lubricants worked together to yield the superlubricity even under harsh conditions. It is proposed that the preferential interactions of cations with PVPA molecules rather than water molecules are the main reason for the superlubricity in water-based lubricants. The interaction of anions with water molecules regulates the properties of the tribological interfaces, which influences the magnitude of the friction coefficient. Owing to the novel cross-linked networks and the interactions between cations and polymer molecules, their superlubricity can be maintained even at a high salt ion concentration of 5 M. These excellent properties make PVPA-modified Ti 6 Al 4 V a potential candidate for application in artificial implants.

Predictive regulatory models in Drosophila melanogaster by integrative inference of transcriptional networks

PubMed Central

Marbach, Daniel; Roy, Sushmita; Ay, Ferhat; Meyer, Patrick E.; Candeias, Rogerio; Kahveci, Tamer; Bristow, Christopher A.; Kellis, Manolis

2012-01-01

Gaining insights on gene regulation from large-scale functional data sets is a grand challenge in systems biology. In this article, we develop and apply methods for transcriptional regulatory network inference from diverse functional genomics data sets and demonstrate their value for gene function and gene expression prediction. We formulate the network inference problem in a machine-learning framework and use both supervised and unsupervised methods to predict regulatory edges by integrating transcription factor (TF) binding, evolutionarily conserved sequence motifs, gene expression, and chromatin modification data sets as input features. Applying these methods to Drosophila melanogaster, we predict ∼300,000 regulatory edges in a network of ∼600 TFs and 12,000 target genes. We validate our predictions using known regulatory interactions, gene functional annotations, tissue-specific expression, protein–protein interactions, and three-dimensional maps of chromosome conformation. We use the inferred network to identify putative functions for hundreds of previously uncharacterized genes, including many in nervous system development, which are independently confirmed based on their tissue-specific expression patterns. Last, we use the regulatory network to predict target gene expression levels as a function of TF expression, and find significantly higher predictive power for integrative networks than for motif or ChIP-based networks. Our work reveals the complementarity between physical evidence of regulatory interactions (TF binding, motif conservation) and functional evidence (coordinated expression or chromatin patterns) and demonstrates the power of data integration for network inference and studies of gene regulation at the systems level. PMID:22456606

Connexin-Dependent Neuroglial Networking as a New Therapeutic Target.

PubMed

Charvériat, Mathieu; Naus, Christian C; Leybaert, Luc; Sáez, Juan C; Giaume, Christian

2017-01-01

Astrocytes and neurons dynamically interact during physiological processes, and it is now widely accepted that they are both organized in plastic and tightly regulated networks. Astrocytes are connected through connexin-based gap junction channels, with brain region specificities, and those networks modulate neuronal activities, such as those involved in sleep-wake cycle, cognitive, or sensory functions. Additionally, astrocyte domains have been involved in neurogenesis and neuronal differentiation during development; they participate in the "tripartite synapse" with both pre-synaptic and post-synaptic neurons by tuning down or up neuronal activities through the control of neuronal synaptic strength. Connexin-based hemichannels are also involved in those regulations of neuronal activities, however, this feature will not be considered in the present review. Furthermore, neuronal processes, transmitting electrical signals to chemical synapses, stringently control astroglial connexin expression, and channel functions. Long-range energy trafficking toward neurons through connexin-coupled astrocytes and plasticity of those networks are hence largely dependent on neuronal activity. Such reciprocal interactions between neurons and astrocyte networks involve neurotransmitters, cytokines, endogenous lipids, and peptides released by neurons but also other brain cell types, including microglial and endothelial cells. Over the past 10 years, knowledge about neuroglial interactions has widened and now includes effects of CNS-targeting drugs such as antidepressants, antipsychotics, psychostimulants, or sedatives drugs as potential modulators of connexin function and thus astrocyte networking activity. In physiological situations, neuroglial networking is consequently resulting from a two-way interaction between astrocyte gap junction-mediated networks and those made by neurons. As both cell types are modulated by CNS drugs we postulate that neuroglial networking may emerge as new therapeutic targets in neurological and psychiatric disorders.

The Impacts of Network Centrality and Self-Regulation on an E-Learning Environment with the Support of Social Network Awareness

ERIC Educational Resources Information Center

Lin, Jian-Wei; Huang, Hsieh-Hong; Chuang, Yuh-Shy

2015-01-01

An e-learning environment that supports social network awareness (SNA) is a highly effective means of increasing peer interaction and assisting student learning by raising awareness of social and learning contexts of peers. Network centrality profoundly impacts student learning in an SNA-related e-learning environment. Additionally,…

Anger Modulates Influence Hierarchies Within and Between Emotional Reactivity and Regulation Networks

PubMed Central

Jacob, Yael; Gilam, Gadi; Lin, Tamar; Raz, Gal; Hendler, Talma

2018-01-01

Emotion regulation is hypothesized to be mediated by the interactions between emotional reactivity and regulation networks during the dynamic unfolding of the emotional episode. Yet, it remains unclear how to delineate the effective relationships between these networks. In this study, we examined the aforementioned networks’ information flow hierarchy during viewing of an anger provoking movie excerpt. Anger regulation is particularly essential for averting individuals from aggression and violence, thus improving prosocial behavior. Using subjective ratings of anger intensity we differentiated between low and high anger periods of the film. We then applied the Dependency Network Analysis (DEPNA), a newly developed graph theory method to quantify networks’ node importance during the two anger periods. The DEPNA analysis revealed that the impact of the ventromedial prefrontal cortex (vmPFC) was higher in the high anger condition, particularly within the regulation network and on the connections between the reactivity and regulation networks. We further showed that higher levels of vmPFC impact on the regulation network were associated with lower subjective anger intensity during the high-anger cinematic period, and lower trait anger levels. Supporting and replicating previous findings, these results emphasize the previously acknowledged central role of vmPFC in modulating negative affect. We further show that the impact of the vmPFC relies on its correlational influence on the connectivity between reactivity and regulation networks. More importantly, the hierarchy network analysis revealed a link between connectivity patterns of the vmPFC and individual differences in anger reactivity and trait, suggesting its potential therapeutic role. PMID:29681803

Time-Ordered Networks Reveal Limitations to Information Flow in Ant Colonies

PubMed Central

Blonder, Benjamin; Dornhaus, Anna

2011-01-01

Background An important function of many complex networks is to inhibit or promote the transmission of disease, resources, or information between individuals. However, little is known about how the temporal dynamics of individual-level interactions affect these networks and constrain their function. Ant colonies are a model comparative system for understanding general principles linking individual-level interactions to network-level functions because interactions among individuals enable integration of multiple sources of information to collectively make decisions, and allocate tasks and resources. Methodology/Findings Here we show how the temporal and spatial dynamics of such individual interactions provide upper bounds to rates of colony-level information flow in the ant Temnothorax rugatulus. We develop a general framework for analyzing dynamic networks and a mathematical model that predicts how information flow scales with individual mobility and group size. Conclusions/Significance Using thousands of time-stamped interactions between uniquely marked ants in four colonies of a range of sizes, we demonstrate that observed maximum rates of information flow are always slower than predicted, and are constrained by regulation of individual mobility and contact rate. By accounting for the ordering and timing of interactions, we can resolve important difficulties with network sampling frequency and duration, enabling a broader understanding of interaction network functioning across systems and scales. PMID:21625450

Inference and interrogation of a coregulatory network in the context of lipid accumulation in Yarrowia lipolytica.

PubMed

Trébulle, Pauline; Nicaud, Jean-Marc; Leplat, Christophe; Elati, Mohamed

2017-01-01

Complex phenotypes, such as lipid accumulation, result from cooperativity between regulators and the integration of multiscale information. However, the elucidation of such regulatory programs by experimental approaches may be challenging, particularly in context-specific conditions. In particular, we know very little about the regulators of lipid accumulation in the oleaginous yeast of industrial interest Yarrowia lipolytica . This lack of knowledge limits the development of this yeast as an industrial platform, due to the time-consuming and costly laboratory efforts required to design strains with the desired phenotypes. In this study, we aimed to identify context-specific regulators and mechanisms, to guide explorations of the regulation of lipid accumulation in Y. lipolytica . Using gene regulatory network inference, and considering the expression of 6539 genes over 26 time points from GSE35447 for biolipid production and a list of 151 transcription factors, we reconstructed a gene regulatory network comprising 111 transcription factors, 4451 target genes and 17048 regulatory interactions (YL-GRN-1) supported by evidence of protein-protein interactions. This study, based on network interrogation and wet laboratory validation (a) highlights the relevance of our proposed measure, the transcription factors influence, for identifying phases corresponding to changes in physiological state without prior knowledge (b) suggests new potential regulators and drivers of lipid accumulation and (c) experimentally validates the impact of six of the nine regulators identified on lipid accumulation, with variations in lipid content from +43.2% to -31.2% on glucose or glycerol.

Identification of fever and vaccine-associated gene interaction networks using ontology-based literature mining

PubMed Central

2012-01-01

Background Fever is one of the most common adverse events of vaccines. The detailed mechanisms of fever and vaccine-associated gene interaction networks are not fully understood. In the present study, we employed a genome-wide, Centrality and Ontology-based Network Discovery using Literature data (CONDL) approach to analyse the genes and gene interaction networks associated with fever or vaccine-related fever responses. Results Over 170,000 fever-related articles from PubMed abstracts and titles were retrieved and analysed at the sentence level using natural language processing techniques to identify genes and vaccines (including 186 Vaccine Ontology terms) as well as their interactions. This resulted in a generic fever network consisting of 403 genes and 577 gene interactions. A vaccine-specific fever sub-network consisting of 29 genes and 28 gene interactions was extracted from articles that are related to both fever and vaccines. In addition, gene-vaccine interactions were identified. Vaccines (including 4 specific vaccine names) were found to directly interact with 26 genes. Gene set enrichment analysis was performed using the genes in the generated interaction networks. Moreover, the genes in these networks were prioritized using network centrality metrics. Making scientific discoveries and generating new hypotheses were possible by using network centrality and gene set enrichment analyses. For example, our study found that the genes in the generic fever network were more enriched in cell death and responses to wounding, and the vaccine sub-network had more gene enrichment in leukocyte activation and phosphorylation regulation. The most central genes in the vaccine-specific fever network are predicted to be highly relevant to vaccine-induced fever, whereas genes that are central only in the generic fever network are likely to be highly relevant to generic fever responses. Interestingly, no Toll-like receptors (TLRs) were found in the gene-vaccine interaction network. Since multiple TLRs were found in the generic fever network, it is reasonable to hypothesize that vaccine-TLR interactions may play an important role in inducing fever response, which deserves a further investigation. Conclusions This study demonstrated that ontology-based literature mining is a powerful method for analyzing gene interaction networks and generating new scientific hypotheses. PMID:23256563

Integrated Module and Gene-Specific Regulatory Inference Implicates Upstream Signaling Networks

PubMed Central

Roy, Sushmita; Lagree, Stephen; Hou, Zhonggang; Thomson, James A.; Stewart, Ron; Gasch, Audrey P.

2013-01-01

Regulatory networks that control gene expression are important in diverse biological contexts including stress response and development. Each gene's regulatory program is determined by module-level regulation (e.g. co-regulation via the same signaling system), as well as gene-specific determinants that can fine-tune expression. We present a novel approach, Modular regulatory network learning with per gene information (MERLIN), that infers regulatory programs for individual genes while probabilistically constraining these programs to reveal module-level organization of regulatory networks. Using edge-, regulator- and module-based comparisons of simulated networks of known ground truth, we find MERLIN reconstructs regulatory programs of individual genes as well or better than existing approaches of network reconstruction, while additionally identifying modular organization of the regulatory networks. We use MERLIN to dissect global transcriptional behavior in two biological contexts: yeast stress response and human embryonic stem cell differentiation. Regulatory modules inferred by MERLIN capture co-regulatory relationships between signaling proteins and downstream transcription factors thereby revealing the upstream signaling systems controlling transcriptional responses. The inferred networks are enriched for regulators with genetic or physical interactions, supporting the inference, and identify modules of functionally related genes bound by the same transcriptional regulators. Our method combines the strengths of per-gene and per-module methods to reveal new insights into transcriptional regulation in stress and development. PMID:24146602

Columbia University: Direct Reversal of Glucocorticoid Resistance by AKT inhibition in Acute Lymphoblastic Leukemia (T-ALL) | Office of Cancer Genomics

Cancer.gov

The goal of this project is to identify key druggable regulators of glucocorticoid resistance in T-ALL. To this end, a reverse-engineered T-ALL context-specific regulatory interaction network was created from a phenotypically diverse T-ALL gene expression dataset, and then this network was interrogated using master regulator analysis to find drivers of glucocorticoid resistance.

Abscisic acid regulates root growth under osmotic stress conditions via an interacting hormonal network with cytokinin, ethylene and auxin.

PubMed

Rowe, James H; Topping, Jennifer F; Liu, Junli; Lindsey, Keith

2016-07-01

Understanding the mechanisms regulating root development under drought conditions is an important question for plant biology and world agriculture. We examine the effect of osmotic stress on abscisic acid (ABA), cytokinin and ethylene responses and how they mediate auxin transport, distribution and root growth through effects on PIN proteins. We integrate experimental data to construct hormonal crosstalk networks to formulate a systems view of root growth regulation by multiple hormones. Experimental analysis shows: that ABA-dependent and ABA-independent stress responses increase under osmotic stress, but cytokinin responses are only slightly reduced; inhibition of root growth under osmotic stress does not require ethylene signalling, but auxin can rescue root growth and meristem size; osmotic stress modulates auxin transporter levels and localization, reducing root auxin concentrations; PIN1 levels are reduced under stress in an ABA-dependent manner, overriding ethylene effects; and the interplay among ABA, ethylene, cytokinin and auxin is tissue-specific, as evidenced by differential responses of PIN1 and PIN2 to osmotic stress. Combining experimental analysis with network construction reveals that ABA regulates root growth under osmotic stress conditions via an interacting hormonal network with cytokinin, ethylene and auxin. © 2016 The Authors. New Phytologist © 2016 New Phytologist Trust.

Cellular Organization and Cytoskeletal Regulation of the Hippo Signaling Network

PubMed Central

Sun, Shuguo; Irvine, Kenneth D.

2016-01-01

The Hippo signaling network integrates diverse upstream signals to control cell fate decisions and regulate organ growth. Recent studies have provided new insights into the cellular organization of Hippo signaling, its relationship to cell-cell junctions, and how the cytoskeleton modulates Hippo signaling. Cell-cell junctions serve as platforms for Hippo signaling by localizing scaffolding proteins that interact with core components of the pathway. Interactions of Hippo pathway components with cell-cell junctions and the cytoskeleton also suggest potential mechanisms for the regulation of the pathway by cell contact and cell polarity. As our understanding of the complexity of Hippo signaling increases, a future challenge will be to understand how the diverse inputs into the pathway are integrated, and to define their respective contributions in vivo. PMID:27268910

Multi-omics approach identifies molecular mechanisms of plant-fungus mycorrhizal interaction

DOE PAGES

Larsen, Peter E.; Sreedasyam, Avinash; Trivedi, Geetika; ...

2016-01-19

In mycorrhizal symbiosis, plant roots form close, mutually beneficial interactions with soil fungi. Before this mycorrhizal interaction can be established however, plant roots must be capable of detecting potential beneficial fungal partners and initiating the gene expression patterns necessary to begin symbiosis. To predict a plant root – mycorrhizal fungi sensor systems, we analyzed in vitro experiments of Populus tremuloides (aspen tree) and Laccaria bicolor (mycorrhizal fungi) interaction and leveraged over 200 previously published transcriptomic experimental data sets, 159 experimentally validated plant transcription factor binding motifs, and more than 120-thousand experimentally validated protein-protein interactions to generate models of pre-mycorrhizal sensormore » systems in aspen root. These sensor mechanisms link extracellular signaling molecules with gene regulation through a network comprised of membrane receptors, signal cascade proteins, transcription factors, and transcription factor biding DNA motifs. Modeling predicted four pre-mycorrhizal sensor complexes in aspen that interact with fifteen transcription factors to regulate the expression of 1184 genes in response to extracellular signals synthesized by Laccaria. Predicted extracellular signaling molecules include common signaling molecules such as phenylpropanoids, salicylate, and, jasmonic acid. Lastly, this multi-omic computational modeling approach for predicting the complex sensory networks yielded specific, testable biological hypotheses for mycorrhizal interaction signaling compounds, sensor complexes, and mechanisms of gene regulation.« less

Multi-omics approach identifies molecular mechanisms of plant-fungus mycorrhizal interaction

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

Larsen, Peter E.; Sreedasyam, Avinash; Trivedi, Geetika

In mycorrhizal symbiosis, plant roots form close, mutually beneficial interactions with soil fungi. Before this mycorrhizal interaction can be established however, plant roots must be capable of detecting potential beneficial fungal partners and initiating the gene expression patterns necessary to begin symbiosis. To predict a plant root – mycorrhizal fungi sensor systems, we analyzed in vitro experiments of Populus tremuloides (aspen tree) and Laccaria bicolor (mycorrhizal fungi) interaction and leveraged over 200 previously published transcriptomic experimental data sets, 159 experimentally validated plant transcription factor binding motifs, and more than 120-thousand experimentally validated protein-protein interactions to generate models of pre-mycorrhizal sensormore » systems in aspen root. These sensor mechanisms link extracellular signaling molecules with gene regulation through a network comprised of membrane receptors, signal cascade proteins, transcription factors, and transcription factor biding DNA motifs. Modeling predicted four pre-mycorrhizal sensor complexes in aspen that interact with fifteen transcription factors to regulate the expression of 1184 genes in response to extracellular signals synthesized by Laccaria. Predicted extracellular signaling molecules include common signaling molecules such as phenylpropanoids, salicylate, and, jasmonic acid. Lastly, this multi-omic computational modeling approach for predicting the complex sensory networks yielded specific, testable biological hypotheses for mycorrhizal interaction signaling compounds, sensor complexes, and mechanisms of gene regulation.« less

Network topologies and convergent aetiologies arising from deletions and duplications observed in individuals with autism.

PubMed

Noh, Hyun Ji; Ponting, Chris P; Boulding, Hannah C; Meader, Stephen; Betancur, Catalina; Buxbaum, Joseph D; Pinto, Dalila; Marshall, Christian R; Lionel, Anath C; Scherer, Stephen W; Webber, Caleb

2013-06-01

Autism Spectrum Disorders (ASD) are highly heritable and characterised by impairments in social interaction and communication, and restricted and repetitive behaviours. Considering four sets of de novo copy number variants (CNVs) identified in 181 individuals with autism and exploiting mouse functional genomics and known protein-protein interactions, we identified a large and significantly interconnected interaction network. This network contains 187 genes affected by CNVs drawn from 45% of the patients we considered and 22 genes previously implicated in ASD, of which 192 form a single interconnected cluster. On average, those patients with copy number changed genes from this network possess changes in 3 network genes, suggesting that epistasis mediated through the network is extensive. Correspondingly, genes that are highly connected within the network, and thus whose copy number change is predicted by the network to be more phenotypically consequential, are significantly enriched among patients that possess only a single ASD-associated network copy number changed gene (p = 0.002). Strikingly, deleted or disrupted genes from the network are significantly enriched in GO-annotated positive regulators (2.3-fold enrichment, corrected p = 2×10(-5)), whereas duplicated genes are significantly enriched in GO-annotated negative regulators (2.2-fold enrichment, corrected p = 0.005). The direction of copy change is highly informative in the context of the network, providing the means through which perturbations arising from distinct deletions or duplications can yield a common outcome. These findings reveal an extensive ASD-associated molecular network, whose topology indicates ASD-relevant mutational deleteriousness and that mechanistically details how convergent aetiologies can result extensively from CNVs affecting pathways causally implicated in ASD.

Physiological β-catenin signaling controls self-renewal networks and generation of stem-like cells from nasopharyngeal carcinoma.

PubMed

Cheng, Yue; Cheung, Arthur Kwok Leung; Ko, Josephine Mun Yee; Phoon, Yee Peng; Chiu, Pui Man; Lo, Paulisally Hau Yi; Waterman, Marian L; Lung, Maria Li

2013-09-27

A few reports suggested that low levels of Wnt signaling might drive cell reprogramming, but these studies could not establish a clear relationship between Wnt signaling and self-renewal networks. There are ongoing debates as to whether and how the Wnt/β-catenin signaling is involved in the control of pluripotency gene networks. Additionally, whether physiological β-catenin signaling generates stem-like cells through interactions with other pathways is as yet unclear. The nasopharyngeal carcinoma HONE1 cells have low expression of β-catenin and wild-type expression of p53, which provided a possibility to study regulatory mechanism of stemness networks induced by physiological levels of Wnt signaling in these cells. Introduction of increased β-catenin signaling, haploid expression of β-catenin under control by its natural regulators in transferred chromosome 3, resulted in activation of Wnt/β-catenin networks and dedifferentiation in HONE1 hybrid cell lines, but not in esophageal carcinoma SLMT1 hybrid cells that had high levels of endogenous β-catenin expression. HONE1 hybrid cells displayed stem cell-like properties, including enhancement of CD24(+) and CD44(+) populations and generation of spheres that were not observed in parental HONE1 cells. Signaling cascades were detected in HONE1 hybrid cells, including activation of p53- and RB1-mediated tumor suppressor pathways, up-regulation of Nanog-, Oct4-, Sox2-, and Klf4-mediated pluripotency networks, and altered E-cadherin expression in both in vitro and in vivo assays. qPCR array analyses further revealed interactions of physiological Wnt/β-catenin signaling with other pathways such as epithelial-mesenchymal transition, TGF-β, Activin, BMPR, FGFR2, and LIFR- and IL6ST-mediated cell self-renewal networks. Using β-catenin shRNA inhibitory assays, a dominant role for β-catenin in these cellular network activities was observed. The expression of cell surface markers such as CD9, CD24, CD44, CD90, and CD133 in generated spheres was progressively up-regulated compared to HONE1 hybrid cells. Thirty-four up-regulated components of the Wnt pathway were identified in these spheres. Wnt/β-catenin signaling regulates self-renewal networks and plays a central role in the control of pluripotency genes, tumor suppressive pathways and expression of cancer stem cell markers. This current study provides a novel platform to investigate the interaction of physiological Wnt/β-catenin signaling with stemness transition networks.

Genome wide predictions of miRNA regulation by transcription factors.

PubMed

Ruffalo, Matthew; Bar-Joseph, Ziv

2016-09-01

Reconstructing regulatory networks from expression and interaction data is a major goal of systems biology. While much work has focused on trying to experimentally and computationally determine the set of transcription-factors (TFs) and microRNAs (miRNAs) that regulate genes in these networks, relatively little work has focused on inferring the regulation of miRNAs by TFs. Such regulation can play an important role in several biological processes including development and disease. The main challenge for predicting such interactions is the very small positive training set currently available. Another challenge is the fact that a large fraction of miRNAs are encoded within genes making it hard to determine the specific way in which they are regulated. To enable genome wide predictions of TF-miRNA interactions, we extended semi-supervised machine-learning approaches to integrate a large set of different types of data including sequence, expression, ChIP-seq and epigenetic data. As we show, the methods we develop achieve good performance on both a labeled test set, and when analyzing general co-expression networks. We next analyze mRNA and miRNA cancer expression data, demonstrating the advantage of using the predicted set of interactions for identifying more coherent and relevant modules, genes, and miRNAs. The complete set of predictions is available on the supporting website and can be used by any method that combines miRNAs, genes, and TFs. Code and full set of predictions are available from the supporting website: http://cs.cmu.edu/~mruffalo/tf-mirna/ zivbj@cs.cmu.edu Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Revealing gene regulation and association through biological networks

USDA-ARS?s Scientific Manuscript database

This review had first summarized traditional methods used by plant breeders for genetic improvement, such as QTL analysis and transcriptomic analysis. With accumulating data, we can draw a network that comprises all possible links between members of a community, including protein–protein interaction...

A new multi-scale method to reveal hierarchical modular structures in biological networks.

PubMed

Jiao, Qing-Ju; Huang, Yan; Shen, Hong-Bin

2016-11-15

Biological networks are effective tools for studying molecular interactions. Modular structure, in which genes or proteins may tend to be associated with functional modules or protein complexes, is a remarkable feature of biological networks. Mining modular structure from biological networks enables us to focus on a set of potentially important nodes, which provides a reliable guide to future biological experiments. The first fundamental challenge in mining modular structure from biological networks is that the quality of the observed network data is usually low owing to noise and incompleteness in the obtained networks. The second problem that poses a challenge to existing approaches to the mining of modular structure is that the organization of both functional modules and protein complexes in networks is far more complicated than was ever thought. For instance, the sizes of different modules vary considerably from each other and they often form multi-scale hierarchical structures. To solve these problems, we propose a new multi-scale protocol for mining modular structure (named ISIMB) driven by a node similarity metric, which works in an iteratively converged space to reduce the effects of the low data quality of the observed network data. The multi-scale node similarity metric couples both the local and the global topology of the network with a resolution regulator. By varying this resolution regulator to give different weightings to the local and global terms in the metric, the ISIMB method is able to fit the shape of modules and to detect them on different scales. Experiments on protein-protein interaction and genetic interaction networks show that our method can not only mine functional modules and protein complexes successfully, but can also predict functional modules from specific to general and reveal the hierarchical organization of protein complexes.

Visualization and Analysis of MiRNA-Targets Interactions Networks.

PubMed

León, Luis E; Calligaris, Sebastián D

2017-01-01

MicroRNAs are a class of small, noncoding RNA molecules of 21-25 nucleotides in length that regulate the gene expression by base-pairing with the target mRNAs, mainly leading to down-regulation or repression of the target genes. MicroRNAs are involved in diverse regulatory pathways in normal and pathological conditions. In this context, it is highly important to identify the targets of specific microRNA in order to understand the mechanism of its regulation and consequently its involvement in disease. However, the microRNA target identification is experimentally laborious and time-consuming. The in silico prediction of microRNA targets is an extremely useful approach because you can identify potential mRNA targets, reduce the number of possibilities and then, validate a few microRNA-mRNA interactions in an in vitro experimental model. In this chapter, we describe, in a simple way, bioinformatics guidelines to use miRWalk database and Cytoscape software for analyzing microRNA-mRNA interactions through their visualization as a network.

Arabidopsis Ensemble Reverse-Engineered Gene Regulatory Network Discloses Interconnected Transcription Factors in Oxidative Stress[W

PubMed Central

Vermeirssen, Vanessa; De Clercq, Inge; Van Parys, Thomas; Van Breusegem, Frank; Van de Peer, Yves

2014-01-01

The abiotic stress response in plants is complex and tightly controlled by gene regulation. We present an abiotic stress gene regulatory network of 200,014 interactions for 11,938 target genes by integrating four complementary reverse-engineering solutions through average rank aggregation on an Arabidopsis thaliana microarray expression compendium. This ensemble performed the most robustly in benchmarking and greatly expands upon the availability of interactions currently reported. Besides recovering 1182 known regulatory interactions, cis-regulatory motifs and coherent functionalities of target genes corresponded with the predicted transcription factors. We provide a valuable resource of 572 abiotic stress modules of coregulated genes with functional and regulatory information, from which we deduced functional relationships for 1966 uncharacterized genes and many regulators. Using gain- and loss-of-function mutants of seven transcription factors grown under control and salt stress conditions, we experimentally validated 141 out of 271 predictions (52% precision) for 102 selected genes and mapped 148 additional transcription factor-gene regulatory interactions (49% recall). We identified an intricate core oxidative stress regulatory network where NAC13, NAC053, ERF6, WRKY6, and NAC032 transcription factors interconnect and function in detoxification. Our work shows that ensemble reverse-engineering can generate robust biological hypotheses of gene regulation in a multicellular eukaryote that can be tested by medium-throughput experimental validation. PMID:25549671

Arabidopsis ensemble reverse-engineered gene regulatory network discloses interconnected transcription factors in oxidative stress.

PubMed

Vermeirssen, Vanessa; De Clercq, Inge; Van Parys, Thomas; Van Breusegem, Frank; Van de Peer, Yves

2014-12-01

The abiotic stress response in plants is complex and tightly controlled by gene regulation. We present an abiotic stress gene regulatory network of 200,014 interactions for 11,938 target genes by integrating four complementary reverse-engineering solutions through average rank aggregation on an Arabidopsis thaliana microarray expression compendium. This ensemble performed the most robustly in benchmarking and greatly expands upon the availability of interactions currently reported. Besides recovering 1182 known regulatory interactions, cis-regulatory motifs and coherent functionalities of target genes corresponded with the predicted transcription factors. We provide a valuable resource of 572 abiotic stress modules of coregulated genes with functional and regulatory information, from which we deduced functional relationships for 1966 uncharacterized genes and many regulators. Using gain- and loss-of-function mutants of seven transcription factors grown under control and salt stress conditions, we experimentally validated 141 out of 271 predictions (52% precision) for 102 selected genes and mapped 148 additional transcription factor-gene regulatory interactions (49% recall). We identified an intricate core oxidative stress regulatory network where NAC13, NAC053, ERF6, WRKY6, and NAC032 transcription factors interconnect and function in detoxification. Our work shows that ensemble reverse-engineering can generate robust biological hypotheses of gene regulation in a multicellular eukaryote that can be tested by medium-throughput experimental validation. © 2014 American Society of Plant Biologists. All rights reserved.

An interactive network of elastase, secretases, and PAR-2 protein regulates CXCR1 receptor surface expression on neutrophils.

PubMed

Bakele, Martina; Lotz-Havla, Amelie S; Jakowetz, Anja; Carevic, Melanie; Marcos, Veronica; Muntau, Ania C; Gersting, Soeren W; Hartl, Dominik

2014-07-25

CXCL8 (IL-8) recruits and activates neutrophils through the G protein-coupled chemokine receptor CXCR1. We showed previously that elastase cleaves CXCR1 and thereby impairs antibacterial host defense. However, the molecular intracellular machinery involved in this process remained undefined. Here we demonstrate by using flow cytometry, confocal microscopy, subcellular fractionation, co-immunoprecipitation, and bioluminescence resonance energy transfer that combined α- and γ-secretase activities are functionally involved in elastase-mediated regulation of CXCR1 surface expression on human neutrophils, whereas matrix metalloproteases are dispensable. We further demonstrate that PAR-2 is stored in mobilizable compartments in neutrophils. Bioluminescence resonance energy transfer and co-immunoprecipitation studies showed that secretases, PAR-2, and CXCR1 colocalize and physically interact in a novel protease/secretase-chemokine receptor network. PAR-2 blocking experiments provided evidence that elastase increased intracellular presenilin-1 expression through PAR-2 signaling. When viewed in combination, these studies establish a novel functional network of elastase, secretases, and PAR-2 that regulate CXCR1 expression on neutrophils. Interfering with this network could lead to novel therapeutic approaches in neutrophilic diseases, such as cystic fibrosis or rheumatoid arthritis.

An Interactive Network of Elastase, Secretases, and PAR-2 Protein Regulates CXCR1 Receptor Surface Expression on Neutrophils*

PubMed Central

Bakele, Martina; Lotz-Havla, Amelie S.; Jakowetz, Anja; Carevic, Melanie; Marcos, Veronica; Muntau, Ania C.; Gersting, Soeren W.; Hartl, Dominik

2014-01-01

CXCL8 (IL-8) recruits and activates neutrophils through the G protein-coupled chemokine receptor CXCR1. We showed previously that elastase cleaves CXCR1 and thereby impairs antibacterial host defense. However, the molecular intracellular machinery involved in this process remained undefined. Here we demonstrate by using flow cytometry, confocal microscopy, subcellular fractionation, co-immunoprecipitation, and bioluminescence resonance energy transfer that combined α- and γ-secretase activities are functionally involved in elastase-mediated regulation of CXCR1 surface expression on human neutrophils, whereas matrix metalloproteases are dispensable. We further demonstrate that PAR-2 is stored in mobilizable compartments in neutrophils. Bioluminescence resonance energy transfer and co-immunoprecipitation studies showed that secretases, PAR-2, and CXCR1 colocalize and physically interact in a novel protease/secretase-chemokine receptor network. PAR-2 blocking experiments provided evidence that elastase increased intracellular presenilin-1 expression through PAR-2 signaling. When viewed in combination, these studies establish a novel functional network of elastase, secretases, and PAR-2 that regulate CXCR1 expression on neutrophils. Interfering with this network could lead to novel therapeutic approaches in neutrophilic diseases, such as cystic fibrosis or rheumatoid arthritis. PMID:24914212

Identification of infection- and defense-related genes via a dynamic host-pathogen interaction network using a Candida albicans-zebrafish infection model.

PubMed

Kuo, Zong-Yu; Chuang, Yung-Jen; Chao, Chun-Cheih; Liu, Fu-Chen; Lan, Chung-Yu; Chen, Bor-Sen

2013-01-01

Candida albicans infections and candidiasis are difficult to treat and create very serious therapeutic challenges. In this study, based on interactive time profile microarray data of C. albicans and zebrafish during infection, the infection-related protein-protein interaction (PPI) networks of the two species and the intercellular PPI network between host and pathogen were simultaneously constructed by a dynamic interaction model, modeled as an integrated network consisting of intercellular invasion and cellular defense processes during infection. The signal transduction pathways in regulating morphogenesis and hyphal growth of C. albicans were further investigated based on significant interactions found in the intercellular PPI network. Two cellular networks were also developed corresponding to the different infection stages (adhesion and invasion), and then compared with each other to identify proteins from which we can gain more insight into the pathogenic role of hyphal development in the C. albicans infection process. Important defense-related proteins in zebrafish were predicted using the same approach. The hyphal growth PPI network, zebrafish PPI network and host-pathogen intercellular PPI network were combined to form an integrated infectious PPI network that helps us understand the systematic mechanisms underlying the pathogenicity of C. albicans and the immune response of the host, and may help improve medical therapies and facilitate the development of new antifungal drugs. Copyright © 2013 S. Karger AG, Basel.

Network Compression as a Quality Measure for Protein Interaction Networks

PubMed Central

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

2012-01-01

With the advent of large-scale protein interaction studies, there is much debate about data quality. Can different noise levels in the measurements be assessed by analyzing network structure? Because proteomic regulation is inherently co-operative, modular and redundant, it is inherently compressible when represented as a network. Here we propose that network compression can be used to compare false positive and false negative noise levels in protein interaction networks. We validate this hypothesis by first confirming the detrimental effect of false positives and false negatives. Second, we show that gold standard networks are more compressible. Third, we show that compressibility correlates with co-expression, co-localization, and shared function. Fourth, we also observe correlation with better protein tagging methods, physiological expression in contrast to over-expression of tagged proteins, and smart pooling approaches for yeast two-hybrid screens. Overall, this new measure is a proxy for both sensitivity and specificity and gives complementary information to standard measures such as average degree and clustering coefficients. PMID:22719828

Topology and static response of interaction networks in molecular biology

PubMed Central

Radulescu, Ovidiu; Lagarrigue, Sandrine; Siegel, Anne; Veber, Philippe; Le Borgne, Michel

2005-01-01

We introduce a mathematical framework describing static response of networks occurring in molecular biology. This formalism has many similarities with the Laplace–Kirchhoff equations for electrical networks. We introduce the concept of graph boundary and we show how the response of the biological networks to external perturbations can be related to the Dirichlet or Neumann problems for the corresponding equations on the interaction graph. Solutions to these two problems are given in terms of path moduli (measuring path rigidity with respect to the propagation of interaction along the graph). Path moduli are related to loop products in the interaction graph via generalized Mason–Coates formulae. We apply our results to two specific biological examples: the lactose operon and the genetic regulation of lipogenesis. Our applications show consistency with experimental results and in the case of lipogenesis check some hypothesis on the behaviour of hepatic fatty acids on fasting. PMID:16849230

Increased Global Interaction Across Functional Brain Modules During Cognitive Emotion Regulation.

PubMed

Brandl, Felix; Mulej Bratec, Satja; Xie, Xiyao; Wohlschläger, Afra M; Riedl, Valentin; Meng, Chun; Sorg, Christian

2017-07-13

Cognitive emotion regulation (CER) enables humans to flexibly modulate their emotions. While local theories of CER neurobiology suggest interactions between specialized local brain circuits underlying CER, e.g., in subparts of amygdala and medial prefrontal cortices (mPFC), global theories hypothesize global interaction increases among larger functional brain modules comprising local circuits. We tested the global CER hypothesis using graph-based whole-brain network analysis of functional MRI data during aversive emotional processing with and without CER. During CER, global between-module interaction across stable functional network modules increased. Global interaction increase was particularly driven by subregions of amygdala and cuneus-nodes of highest nodal participation-that overlapped with CER-specific local activations, and by mPFC and posterior cingulate as relevant connector hubs. Results provide evidence for the global nature of human CER, complementing functional specialization of embedded local brain circuits during successful CER. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Hacking the Cell: Network Intrusion and Exploitation by Adenovirus E1A.

PubMed

King, Cason R; Zhang, Ali; Tessier, Tanner M; Gameiro, Steven F; Mymryk, Joe S

2018-05-01

As obligate intracellular parasites, viruses are dependent on their infected hosts for survival. Consequently, viruses are under enormous selective pressure to utilize available cellular components and processes to their own advantage. As most, if not all, cellular activities are regulated at some level via protein interactions, host protein interaction networks are particularly vulnerable to viral exploitation. Indeed, viral proteins frequently target highly connected "hub" proteins to "hack" the cellular network, defining the molecular basis for viral control over the host. This widespread and successful strategy of network intrusion and exploitation has evolved convergently among numerous genetically distinct viruses as a result of the endless evolutionary arms race between pathogens and hosts. Here we examine the means by which a particularly well-connected viral hub protein, human adenovirus E1A, compromises and exploits the vulnerabilities of eukaryotic protein interaction networks. Importantly, these interactions identify critical regulatory hubs in the human proteome and help define the molecular basis of their function. Copyright © 2018 King et al.

Hacking the Cell: Network Intrusion and Exploitation by Adenovirus E1A

PubMed Central

King, Cason R.; Zhang, Ali; Tessier, Tanner M.; Gameiro, Steven F.

2018-01-01

ABSTRACT As obligate intracellular parasites, viruses are dependent on their infected hosts for survival. Consequently, viruses are under enormous selective pressure to utilize available cellular components and processes to their own advantage. As most, if not all, cellular activities are regulated at some level via protein interactions, host protein interaction networks are particularly vulnerable to viral exploitation. Indeed, viral proteins frequently target highly connected “hub” proteins to “hack” the cellular network, defining the molecular basis for viral control over the host. This widespread and successful strategy of network intrusion and exploitation has evolved convergently among numerous genetically distinct viruses as a result of the endless evolutionary arms race between pathogens and hosts. Here we examine the means by which a particularly well-connected viral hub protein, human adenovirus E1A, compromises and exploits the vulnerabilities of eukaryotic protein interaction networks. Importantly, these interactions identify critical regulatory hubs in the human proteome and help define the molecular basis of their function. PMID:29717008

MYC interaction with the tumor suppressive SWI/SNF complex member INI1 regulates transcription and cellular transformation

PubMed Central

Stojanova, Angelina; Tu, William B.; Ponzielli, Romina; Kotlyar, Max; Chan, Pak-Kei; Boutros, Paul C.; Khosravi, Fereshteh; Jurisica, Igor; Raught, Brian; Penn, Linda Z.

2016-01-01

ABSTRACT MYC is a key driver of cellular transformation and is deregulated in most human cancers. Studies of MYC and its interactors have provided mechanistic insight into its role as a regulator of gene transcription. MYC has been previously linked to chromatin regulation through its interaction with INI1 (SMARCB1/hSNF5/BAF47), a core member of the SWI/SNF chromatin remodeling complex. INI1 is a potent tumor suppressor that is inactivated in several types of cancers, most prominently as the hallmark alteration in pediatric malignant rhabdoid tumors. However, the molecular and functional interaction of MYC and INI1 remains unclear. Here, we characterize the MYC-INI1 interaction in mammalian cells, mapping their minimal binding domains to functionally significant regions of MYC (leucine zipper) and INI1 (repeat motifs), and demonstrating that the interaction does not interfere with MYC-MAX interaction. Protein-protein interaction network analysis expands the MYC-INI1 interaction to the SWI/SNF complex and a larger network of chromatin regulatory complexes. Genome-wide analysis reveals that the DNA-binding regions and target genes of INI1 significantly overlap with those of MYC. In an INI1-deficient rhabdoid tumor system, we observe that with re-expression of INI1, MYC and INI1 bind to common target genes and have opposing effects on gene expression. Functionally, INI1 re-expression suppresses cell proliferation and MYC-potentiated transformation. Our findings thus establish the antagonistic roles of the INI1 and MYC transcriptional regulators in mediating cellular and oncogenic functions. PMID:27267444

Cellular Organization and Cytoskeletal Regulation of the Hippo Signaling Network.

PubMed

Sun, Shuguo; Irvine, Kenneth D

2016-09-01

The Hippo signaling network integrates diverse upstream signals to control cell fate decisions and regulate organ growth. Recent studies have provided new insights into the cellular organization of Hippo signaling, its relationship to cell-cell junctions, and how the cytoskeleton modulates Hippo signaling. Cell-cell junctions serve as platforms for Hippo signaling by localizing scaffolding proteins that interact with core components of the pathway. Interactions of Hippo pathway components with cell-cell junctions and the cytoskeleton also suggest potential mechanisms for the regulation of the pathway by cell contact and cell polarity. As our understanding of the complexity of Hippo signaling increases, a future challenge will be to understand how the diverse inputs into the pathway are integrated and to define their respective contributions in vivo. Copyright © 2016 Elsevier Ltd. All rights reserved.

Evolution of the Max and Mlx networks in animals.

PubMed

McFerrin, Lisa G; Atchley, William R

2011-01-01

Transcription factors (TFs) are essential for the regulation of gene expression and often form emergent complexes to perform vital roles in cellular processes. In this paper, we focus on the parallel Max and Mlx networks of TFs because of their critical involvement in cell cycle regulation, proliferation, growth, metabolism, and apoptosis. A basic-helix-loop-helix-zipper (bHLHZ) domain mediates the competitive protein dimerization and DNA binding among Max and Mlx network members to form a complex system of cell regulation. To understand the importance of these network interactions, we identified the bHLHZ domain of Max and Mlx network proteins across the animal kingdom and carried out several multivariate statistical analyses. The presence and conservation of Max and Mlx network proteins in animal lineages stemming from the divergence of Metazoa indicate that these networks have ancient and essential functions. Phylogenetic analysis of the bHLHZ domain identified clear relationships among protein families with distinct points of radiation and divergence. Multivariate discriminant analysis further isolated specific amino acid changes within the bHLHZ domain that classify proteins, families, and network configurations. These analyses on Max and Mlx network members provide a model for characterizing the evolution of TFs involved in essential networks.

Predicting Human Protein Subcellular Locations by the Ensemble of Multiple Predictors via Protein-Protein Interaction Network with Edge Clustering Coefficients

PubMed Central

Du, Pufeng; Wang, Lusheng

2014-01-01

One of the fundamental tasks in biology is to identify the functions of all proteins to reveal the primary machinery of a cell. Knowledge of the subcellular locations of proteins will provide key hints to reveal their functions and to understand the intricate pathways that regulate biological processes at the cellular level. Protein subcellular location prediction has been extensively studied in the past two decades. A lot of methods have been developed based on protein primary sequences as well as protein-protein interaction network. In this paper, we propose to use the protein-protein interaction network as an infrastructure to integrate existing sequence based predictors. When predicting the subcellular locations of a given protein, not only the protein itself, but also all its interacting partners were considered. Unlike existing methods, our method requires neither the comprehensive knowledge of the protein-protein interaction network nor the experimentally annotated subcellular locations of most proteins in the protein-protein interaction network. Besides, our method can be used as a framework to integrate multiple predictors. Our method achieved 56% on human proteome in absolute-true rate, which is higher than the state-of-the-art methods. PMID:24466278

Responses to olfactory signals reflect network structure of flower-visitor interactions.

PubMed

Junker, Robert R; Höcherl, Nicole; Blüthgen, Nico

2010-07-01

1. Network analyses provide insights into the diversity and complexity of ecological interactions and have motivated conclusions about community stability and co-evolution. However, biological traits and mechanisms such as chemical signals regulating the interactions between individual species--the microstructure of a network--are poorly understood. 2. We linked the responses of receivers (flower visitors) towards signals (flower scent) to the structure of a highly diverse natural flower-insect network. For each interaction, we define link temperature--a newly developed metric--as the deviation of the observed interaction strength from neutrality, assuming that animals randomly interact with flowers. 3. Link temperature was positively correlated to the specific visitors' responses to floral scents, experimentally examined in a mobile olfactometer. Thus, communication between plants and consumers via phytochemical signals reflects a significant part of the microstructure in a complex network. Negative as well as positive responses towards floral scents contributed to these results, where individual experience was important apart from innate behaviour. 4. Our results indicate that: (1) biological mechanisms have a profound impact on the microstructure of complex networks that underlies the outcome of aggregate statistics, and (2) floral scents act as a filter, promoting the visitation of some flower visitors, but also inhibiting the visitation of others.

Role of bundle helices in a regulatory crosstalk in the trimeric betaine transporter BetP.

PubMed

Gärtner, Rebecca M; Perez, Camilo; Koshy, Caroline; Ziegler, Christine

2011-12-02

The Na(+)-coupled betaine symporter BetP regulates transport activity in response to hyperosmotic stress only in its trimeric state, suggesting a regulatory crosstalk between individual protomers. BetP shares the overall fold of two inverted structurally related five-transmembrane (TM) helix repeats with the sequence-unrelated Na(+)-coupled symporters LeuT, vSGLT, and Mhp1, which are neither trimeric nor regulated in transport activity. Conformational changes characteristic for this transporter fold involve the two first helices of each repeat, which form a four-TM-helix bundle. Here, we identify two ionic networks in BetP located on both sides of the membrane that might be responsible for BetP's unique regulatory behavior by restricting the conformational flexibility of the four-TM-helix bundle. The cytoplasmic ionic interaction network links both first helices of each repeat in one protomer to the osmosensing C-terminal domain of the adjacent protomer. Moreover, the periplasmic ionic interaction network conformationally locks the four-TM-helix bundle between the same neighbor protomers. By a combination of site-directed mutagenesis, cross-linking, and betaine uptake measurements, we demonstrate how conformational changes in individual bundle helices are transduced to the entire bundle by specific inter-helical interactions. We suggest that one purpose of bundle networking is to assist crosstalk between protomers during transport regulation by specifically modulating the transition from outward-facing to inward-facing state. Copyright © 2011 Elsevier Ltd. All rights reserved.

Defining the Protein–Protein Interaction Network of the Human Hippo Pathway*

PubMed Central

Wang, Wenqi; Li, Xu; Huang, Jun; Feng, Lin; Dolinta, Keithlee G.; Chen, Junjie

2014-01-01

The Hippo pathway, which is conserved from Drosophila to mammals, has been recognized as a tumor suppressor signaling pathway governing cell proliferation and apoptosis, two key events involved in organ size control and tumorigenesis. Although several upstream regulators, the conserved kinase cascade and key downstream effectors including nuclear transcriptional factors have been defined, the global organization of this signaling pathway is not been fully understood. Thus, we conducted a proteomic analysis of human Hippo pathway, which revealed the involvement of an extensive protein–protein interaction network in this pathway. The mass spectrometry data were deposited to ProteomeXchange with identifier PXD000415. Our data suggest that 550 interactions within 343 unique protein components constitute the central protein–protein interaction landscape of human Hippo pathway. Our study provides a glimpse into the global organization of Hippo pathway, reveals previously unknown interactions within this pathway, and uncovers new potential components involved in the regulation of this pathway. Understanding these interactions will help us further dissect the Hippo signaling-pathway and extend our knowledge of organ size control. PMID:24126142

Predicting gene regulatory networks by combining spatial and temporal gene expression data in Arabidopsis root stem cells

PubMed Central

de Luis Balaguer, Maria Angels; Fisher, Adam P.; Clark, Natalie M.; Fernandez-Espinosa, Maria Guadalupe; Möller, Barbara K.; Weijers, Dolf; Williams, Cranos; Lorenzo, Oscar; Sozzani, Rosangela

2017-01-01

Identifying the transcription factors (TFs) and associated networks involved in stem cell regulation is essential for understanding the initiation and growth of plant tissues and organs. Although many TFs have been shown to have a role in the Arabidopsis root stem cells, a comprehensive view of the transcriptional signature of the stem cells is lacking. In this work, we used spatial and temporal transcriptomic data to predict interactions among the genes involved in stem cell regulation. To accomplish this, we transcriptionally profiled several stem cell populations and developed a gene regulatory network inference algorithm that combines clustering with dynamic Bayesian network inference. We leveraged the topology of our networks to infer potential major regulators. Specifically, through mathematical modeling and experimental validation, we identified PERIANTHIA (PAN) as an important molecular regulator of quiescent center function. The results presented in this work show that our combination of molecular biology, computational biology, and mathematical modeling is an efficient approach to identify candidate factors that function in the stem cells. PMID:28827319

Time-evolving genetic networks reveal a NAC troika that negatively regulates leaf senescence in Arabidopsis.

PubMed

Kim, Hyo Jung; Park, Ji-Hwan; Kim, Jingil; Kim, Jung Ju; Hong, Sunghyun; Kim, Jeongsik; Kim, Jin Hee; Woo, Hye Ryun; Hyeon, Changbong; Lim, Pyung Ok; Nam, Hong Gil; Hwang, Daehee

2018-05-22

Senescence is controlled by time-evolving networks that describe the temporal transition of interactions among senescence regulators. Here, we present time-evolving networks for NAM/ATAF/CUC (NAC) transcription factors in Arabidopsis during leaf aging. The most evident characteristic of these time-dependent networks was a shift from positive to negative regulation among NACs at a presenescent stage. ANAC017, ANAC082, and ANAC090, referred to as a "NAC troika," govern the positive-to-negative regulatory shift. Knockout of the NAC troika accelerated senescence and the induction of other NAC s, whereas overexpression of the NAC troika had the opposite effects. Transcriptome and molecular analyses revealed shared suppression of senescence-promoting processes by the NAC troika, including salicylic acid (SA) and reactive oxygen species (ROS) responses, but with predominant regulation of SA and ROS responses by ANAC090 and ANAC017, respectively. Our time-evolving networks provide a unique regulatory module of presenescent repressors that direct the timely induction of senescence-promoting processes at the presenescent stage of leaf aging. Copyright © 2018 the Author(s). Published by PNAS.

Time-evolving genetic networks reveal a NAC troika that negatively regulates leaf senescence in Arabidopsis

PubMed Central

Kim, Hyo Jung; Park, Ji-Hwan; Kim, Jingil; Kim, Jung Ju; Hong, Sunghyun; Kim, Jin Hee; Woo, Hye Ryun; Lim, Pyung Ok; Nam, Hong Gil; Hwang, Daehee

2018-01-01

Senescence is controlled by time-evolving networks that describe the temporal transition of interactions among senescence regulators. Here, we present time-evolving networks for NAM/ATAF/CUC (NAC) transcription factors in Arabidopsis during leaf aging. The most evident characteristic of these time-dependent networks was a shift from positive to negative regulation among NACs at a presenescent stage. ANAC017, ANAC082, and ANAC090, referred to as a “NAC troika,” govern the positive-to-negative regulatory shift. Knockout of the NAC troika accelerated senescence and the induction of other NACs, whereas overexpression of the NAC troika had the opposite effects. Transcriptome and molecular analyses revealed shared suppression of senescence-promoting processes by the NAC troika, including salicylic acid (SA) and reactive oxygen species (ROS) responses, but with predominant regulation of SA and ROS responses by ANAC090 and ANAC017, respectively. Our time-evolving networks provide a unique regulatory module of presenescent repressors that direct the timely induction of senescence-promoting processes at the presenescent stage of leaf aging. PMID:29735710

Brain network dysregulation, emotion, and complaints after mild traumatic brain injury.

PubMed

van der Horn, Harm J; Liemburg, Edith J; Scheenen, Myrthe E; de Koning, Myrthe E; Marsman, Jan-Bernard C; Spikman, Jacoba M; van der Naalt, Joukje

2016-04-01

To assess the role of brain networks in emotion regulation and post-traumatic complaints in the sub-acute phase after non-complicated mild traumatic brain injury (mTBI). Fifty-four patients with mTBI (34 with and 20 without complaints) and 20 healthy controls (group-matched for age, sex, education, and handedness) were included. Resting-state fMRI was performed at four weeks post-injury. Static and dynamic functional connectivity were studied within and between the default mode, executive (frontoparietal and bilateral frontal network), and salience network. The hospital anxiety and depression scale (HADS) was used to measure anxiety (HADS-A) and depression (HADS-D). Regarding within-network functional connectivity, none of the selected brain networks were different between groups. Regarding between-network interactions, patients with complaints exhibited lower functional connectivity between the bilateral frontal and salience network compared to patients without complaints. In the total patient group, higher HADS-D scores were related to lower functional connectivity between the bilateral frontal network and both the right frontoparietal and salience network, and to higher connectivity between the right frontoparietal and salience network. Furthermore, whereas higher HADS-D scores were associated with lower connectivity within the parietal midline areas of the bilateral frontal network, higher HADS-A scores were related to lower connectivity within medial prefrontal areas of the bilateral frontal network. Functional interactions of the executive and salience networks were related to emotion regulation and complaints after mTBI, with a key role for the bilateral frontal network. These findings may have implications for future studies on the effect of psychological interventions. © 2016 Wiley Periodicals, Inc.

Detection of gene communities in multi-networks reveals cancer drivers

NASA Astrophysics Data System (ADS)

Cantini, Laura; Medico, Enzo; Fortunato, Santo; Caselle, Michele

2015-12-01

We propose a new multi-network-based strategy to integrate different layers of genomic information and use them in a coordinate way to identify driving cancer genes. The multi-networks that we consider combine transcription factor co-targeting, microRNA co-targeting, protein-protein interaction and gene co-expression networks. The rationale behind this choice is that gene co-expression and protein-protein interactions require a tight coregulation of the partners and that such a fine tuned regulation can be obtained only combining both the transcriptional and post-transcriptional layers of regulation. To extract the relevant biological information from the multi-network we studied its partition into communities. To this end we applied a consensus clustering algorithm based on state of art community detection methods. Even if our procedure is valid in principle for any pathology in this work we concentrate on gastric, lung, pancreas and colorectal cancer and identified from the enrichment analysis of the multi-network communities a set of candidate driver cancer genes. Some of them were already known oncogenes while a few are new. The combination of the different layers of information allowed us to extract from the multi-network indications on the regulatory pattern and functional role of both the already known and the new candidate driver genes.

Rhizoma Dioscoreae extract protects against alveolar bone loss by regulating the cell cycle: A predictive study based on the protein‑protein interaction network.

PubMed

Zhang, Zhi-Guo; Song, Chang-Heng; Zhang, Fang-Zhen; Chen, Yan-Jing; Xiang, Li-Hua; Xiao, Gary Guishan; Ju, Da-Hong

2016-06-01

Rhizoma Dioscoreae extract (RDE) exhibits a protective effect on alveolar bone loss in ovariectomized (OVX) rats. The aim of this study was to predict the pathways or targets that are regulated by RDE, by re‑assessing our previously reported data and conducting a protein‑protein interaction (PPI) network analysis. In total, 383 differentially expressed genes (≥3‑fold) between alveolar bone samples from the RDE and OVX group rats were identified, and a PPI network was constructed based on these genes. Furthermore, four molecular clusters (A‑D) in the PPI network with the smallest P‑values were detected by molecular complex detection (MCODE) algorithm. Using Database for Annotation, Visualization and Integrated Discovery (DAVID) and Ingenuity Pathway Analysis (IPA) tools, two molecular clusters (A and B) were enriched for biological process in Gene Ontology (GO). Only cluster A was associated with biological pathways in the IPA database. GO and pathway analysis results showed that cluster A, associated with cell cycle regulation, was the most important molecular cluster in the PPI network. In addition, cyclin‑dependent kinase 1 (CDK1) may be a key molecule achieving the cell‑cycle‑regulatory function of cluster A. From the PPI network analysis, it was predicted that delayed cell cycle progression in excessive alveolar bone remodeling via downregulation of CDK1 may be another mechanism underling the anti‑osteopenic effect of RDE on alveolar bone.

Network representations of immune system complexity

PubMed Central

Subramanian, Naeha; Torabi-Parizi, Parizad; Gottschalk, Rachel A.; Germain, Ronald N.; Dutta, Bhaskar

2015-01-01

The mammalian immune system is a dynamic multi-scale system composed of a hierarchically organized set of molecular, cellular and organismal networks that act in concert to promote effective host defense. These networks range from those involving gene regulatory and protein-protein interactions underlying intracellular signaling pathways and single cell responses to increasingly complex networks of in vivo cellular interaction, positioning and migration that determine the overall immune response of an organism. Immunity is thus not the product of simple signaling events but rather non-linear behaviors arising from dynamic, feedback-regulated interactions among many components. One of the major goals of systems immunology is to quantitatively measure these complex multi-scale spatial and temporal interactions, permitting development of computational models that can be used to predict responses to perturbation. Recent technological advances permit collection of comprehensive datasets at multiple molecular and cellular levels while advances in network biology support representation of the relationships of components at each level as physical or functional interaction networks. The latter facilitate effective visualization of patterns and recognition of emergent properties arising from the many interactions of genes, molecules, and cells of the immune system. We illustrate the power of integrating ‘omics’ and network modeling approaches for unbiased reconstruction of signaling and transcriptional networks with a focus on applications involving the innate immune system. We further discuss future possibilities for reconstruction of increasingly complex cellular and organism-level networks and development of sophisticated computational tools for prediction of emergent immune behavior arising from the concerted action of these networks. PMID:25625853

BioCichlid: central dogma-based 3D visualization system of time-course microarray data on a hierarchical biological network.

PubMed

Ishiwata, Ryosuke R; Morioka, Masaki S; Ogishima, Soichi; Tanaka, Hiroshi

2009-02-15

BioCichlid is a 3D visualization system of time-course microarray data on molecular networks, aiming at interpretation of gene expression data by transcriptional relationships based on the central dogma with physical and genetic interactions. BioCichlid visualizes both physical (protein) and genetic (regulatory) network layers, and provides animation of time-course gene expression data on the genetic network layer. Transcriptional regulations are represented to bridge the physical network (transcription factors) and genetic network (regulated genes) layers, thus integrating promoter analysis into the pathway mapping. BioCichlid enhances the interpretation of microarray data and allows for revealing the underlying mechanisms causing differential gene expressions. BioCichlid is freely available and can be accessed at http://newton.tmd.ac.jp/. Source codes for both biocichlid server and client are also available.

Learning Control Over Emotion Networks Through Connectivity-Based Neurofeedback.

PubMed

Koush, Yury; Meskaldji, Djalel-E; Pichon, Swann; Rey, Gwladys; Rieger, Sebastian W; Linden, David E J; Van De Ville, Dimitri; Vuilleumier, Patrik; Scharnowski, Frank

2017-02-01

Most mental functions are associated with dynamic interactions within functional brain networks. Thus, training individuals to alter functional brain networks might provide novel and powerful means to improve cognitive performance and emotions. Using a novel connectivity-neurofeedback approach based on functional magnetic resonance imaging (fMRI), we show for the first time that participants can learn to change functional brain networks. Specifically, we taught participants control over a key component of the emotion regulation network, in that they learned to increase top-down connectivity from the dorsomedial prefrontal cortex, which is involved in cognitive control, onto the amygdala, which is involved in emotion processing. After training, participants successfully self-regulated the top-down connectivity between these brain areas even without neurofeedback, and this was associated with concomitant increases in subjective valence ratings of emotional stimuli of the participants. Connectivity-based neurofeedback goes beyond previous neurofeedback approaches, which were limited to training localized activity within a brain region. It allows to noninvasively and nonpharmacologically change interconnected functional brain networks directly, thereby resulting in specific behavioral changes. Our results demonstrate that connectivity-based neurofeedback training of emotion regulation networks enhances emotion regulation capabilities. This approach can potentially lead to powerful therapeutic emotion regulation protocols for neuropsychiatric disorders. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

A pseudogene long noncoding RNA network regulates PTEN transcription and translation in human cells

PubMed Central

Johnsson, Per; Ackley, Amanda; Vidarsdottir, Linda; Lui, Weng-Onn; Corcoran, Martin; Grandér, Dan; Morris, Kevin V.

2013-01-01

PTEN is a tumor suppressor gene that has been shown to be under the regulatory control of a PTEN pseudogene expressed noncoding RNA, PTENpg1. Here, we characterize a previously unidentified PTENpg1 encoded antisense RNA (asRNA), which regulates PTEN transcription and PTEN mRNA stability. We find two PTENpg1 asRNA isoforms, alpha and beta. The alpha isoform functions in trans, localizes to the PTEN promoter, and epigenetically modulates PTEN transcription by the recruitment of DNMT3a and EZH2. In contrast, the beta isoform interacts with PTENpg1 through an RNA:RNA pairing interaction, which affects PTEN protein output via changes of PTENpg1 stability and microRNA sponge activity. Disruption of this asRNA-regulated network induces cell cycle arrest and sensitizes cells to doxorubicin, suggesting a biological function for the respective PTENpg1 expressed asRNAs. PMID:23435381

A pseudogene long-noncoding-RNA network regulates PTEN transcription and translation in human cells.

PubMed

Johnsson, Per; Ackley, Amanda; Vidarsdottir, Linda; Lui, Weng-Onn; Corcoran, Martin; Grandér, Dan; Morris, Kevin V

2013-04-01

PTEN is a tumor-suppressor gene that has been shown to be under the regulatory control of a PTEN pseudogene expressed noncoding RNA, PTENpg1. Here, we characterize a previously unidentified PTENpg1-encoded antisense RNA (asRNA), which regulates PTEN transcription and PTEN mRNA stability. We find two PTENpg1 asRNA isoforms, α and β. The α isoform functions in trans, localizes to the PTEN promoter and epigenetically modulates PTEN transcription by the recruitment of DNA methyltransferase 3a and Enhancer of Zeste. In contrast, the β isoform interacts with PTENpg1 through an RNA-RNA pairing interaction, which affects PTEN protein output through changes of PTENpg1 stability and microRNA sponge activity. Disruption of this asRNA-regulated network induces cell-cycle arrest and sensitizes cells to doxorubicin, which suggests a biological function for the respective PTENpg1 expressed asRNAs.

Network reconfiguration and neuronal plasticity in rhythm-generating networks.

PubMed

Koch, Henner; Garcia, Alfredo J; Ramirez, Jan-Marino

2011-12-01

Neuronal networks are highly plastic and reconfigure in a state-dependent manner. The plasticity at the network level emerges through multiple intrinsic and synaptic membrane properties that imbue neurons and their interactions with numerous nonlinear properties. These properties are continuously regulated by neuromodulators and homeostatic mechanisms that are critical to maintain not only network stability and also adapt networks in a short- and long-term manner to changes in behavioral, developmental, metabolic, and environmental conditions. This review provides concrete examples from neuronal networks in invertebrates and vertebrates, and illustrates that the concepts and rules that govern neuronal networks and behaviors are universal.

Hi-C Chromatin Interaction Networks Predict Co-expression in the Mouse Cortex

PubMed Central

Hulsman, Marc; Lelieveldt, Boudewijn P. F.; de Ridder, Jeroen; Reinders, Marcel

2015-01-01

The three dimensional conformation of the genome in the cell nucleus influences important biological processes such as gene expression regulation. Recent studies have shown a strong correlation between chromatin interactions and gene co-expression. However, predicting gene co-expression from frequent long-range chromatin interactions remains challenging. We address this by characterizing the topology of the cortical chromatin interaction network using scale-aware topological measures. We demonstrate that based on these characterizations it is possible to accurately predict spatial co-expression between genes in the mouse cortex. Consistent with previous findings, we find that the chromatin interaction profile of a gene-pair is a good predictor of their spatial co-expression. However, the accuracy of the prediction can be substantially improved when chromatin interactions are described using scale-aware topological measures of the multi-resolution chromatin interaction network. We conclude that, for co-expression prediction, it is necessary to take into account different levels of chromatin interactions ranging from direct interaction between genes (i.e. small-scale) to chromatin compartment interactions (i.e. large-scale). PMID:25965262

Dynamic reconfiguration of human brain functional networks through neurofeedback.

PubMed

Haller, Sven; Kopel, Rotem; Jhooti, Permi; Haas, Tanja; Scharnowski, Frank; Lovblad, Karl-Olof; Scheffler, Klaus; Van De Ville, Dimitri

2013-11-01

Recent fMRI studies demonstrated that functional connectivity is altered following cognitive tasks (e.g., learning) or due to various neurological disorders. We tested whether real-time fMRI-based neurofeedback can be a tool to voluntarily reconfigure brain network interactions. To disentangle learning-related from regulation-related effects, we first trained participants to voluntarily regulate activity in the auditory cortex (training phase) and subsequently asked participants to exert learned voluntary self-regulation in the absence of feedback (transfer phase without learning). Using independent component analysis (ICA), we found network reconfigurations (increases in functional network connectivity) during the neurofeedback training phase between the auditory target region and (1) the auditory pathway; (2) visual regions related to visual feedback processing; (3) insula related to introspection and self-regulation and (4) working memory and high-level visual attention areas related to cognitive effort. Interestingly, the auditory target region was identified as the hub of the reconfigured functional networks without a-priori assumptions. During the transfer phase, we again found specific functional connectivity reconfiguration between auditory and attention network confirming the specific effect of self-regulation on functional connectivity. Functional connectivity to working memory related networks was no longer altered consistent with the absent demand on working memory. We demonstrate that neurofeedback learning is mediated by widespread changes in functional connectivity. In contrast, applying learned self-regulation involves more limited and specific network changes in an auditory setup intended as a model for tinnitus. Hence, neurofeedback training might be used to promote recovery from neurological disorders that are linked to abnormal patterns of brain connectivity. Copyright © 2013 Elsevier Inc. All rights reserved.

Identification of potential crucial genes associated with steroid-induced necrosis of femoral head based on gene expression profile.

PubMed

Lin, Zhe; Lin, Yongsheng

2017-09-05

The aim of this study was to explore potential crucial genes associated with the steroid-induced necrosis of femoral head (SINFH) and to provide valid biological information for further investigation of SINFH. Gene expression profile of GSE26316, generated from 3 SINFH rat samples and 3 normal rat samples were downloaded from Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) were identified using LIMMA package. After functional enrichment analyses of DEGs, protein-protein interaction (PPI) network and sub-PPI network analyses were conducted based on the STRING database and cytoscape. In total, 59 up-regulated DEGs and 156 downregulated DEGs were identified. The up-regulated DEGs were mainly involved in functions about immunity (e.g. Fcer1A and Il7R), and the downregulated DEGs were mainly enriched in muscle system process (e.g. Tnni2, Mylpf and Myl1). The PPI network of DEGs consisted of 123 nodes and 300 interactions. Tnni2, Mylpf, and Myl1 were the top 3 outstanding genes based on both subgraph centrality and degree centrality evaluation. These three genes interacted with each other in the network. Furthermore, the significant network module was composed of 22 downregulated genes (e.g. Tnni2, Mylpf and Myl1). These genes were mainly enriched in functions like muscle system process. The DEGs related to the regulation of immune system process (e.g. Fcer1A and Il7R), and DEGs correlated with muscle system process (e.g. Tnni2, Mylpf and Myl1) may be closely associated with the progress of SINFH, which is still needed to be confirmed by experiments. Copyright © 2017 Elsevier B.V. All rights reserved.

Transcription factor FOXA2-centered transcriptional regulation network in non-small cell lung cancer

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

Jang, Sang-Min; An, Joo-Hee; Kim, Chul-Hong

2015-08-07

Lung cancer is the leading cause of cancer-mediated death. Although various therapeutic approaches are used for lung cancer treatment, these mainly target the tumor suppressor p53 transcription factor, which is involved in apoptosis and cell cycle arrest. However, p53-targeted therapies have limited application in lung cancer, since p53 is found to be mutated in more than half of lung cancers. In this study, we propose tumor suppressor FOXA2 as an alternative target protein for therapies against lung cancer and reveal a possible FOXA2-centered transcriptional regulation network by identifying new target genes and binding partners of FOXA2 by using various screeningmore » techniques. The genes encoding Glu/Asp-rich carboxy-terminal domain 2 (CITED2), nuclear receptor subfamily 0, group B, member 2 (NR0B2), cell adhesion molecule 1 (CADM1) and BCL2-associated X protein (BAX) were identified as putative target genes of FOXA2. Additionally, the proteins including highly similar to heat shock protein HSP 90-beta (HSP90A), heat shock 70 kDa protein 1A variant (HSPA1A), histone deacetylase 1 (HDAC1) and HDAC3 were identified as novel interacting partners of FOXA2. Moreover, we showed that FOXA2-dependent promoter activation of BAX and p21 genes is significantly reduced via physical interactions between the identified binding partners and FOXA2. These results provide opportunities to understand the FOXA2-centered transcriptional regulation network and novel therapeutic targets to modulate this network in p53-deficient lung cancer. - Highlights: • Identification of new target genes of FOXA2. • Identifications of novel interaction proteins of FOXA2. • Construction of FOXA2-centered transcriptional regulatory network in non-small cell lung cancer.« less

The transcriptional regulatory network of Corynebacterium jeikeium K411 and its interaction with metabolic routes contributing to human body odor formation.

PubMed

Barzantny, Helena; Schröder, Jasmin; Strotmeier, Jasmin; Fredrich, Eugenie; Brune, Iris; Tauch, Andreas

2012-06-15

Lipophilic corynebacteria are involved in the generation of volatile odorous products in the process of human body odor formation by degrading skin lipids and specific odor precursors. Therefore, these bacteria represent appropriate model systems for the cosmetic industry to examine axillary malodor formation on the molecular level. To understand the transcriptional control of metabolic pathways involved in this process, the transcriptional regulatory network of the lipophilic axilla isolate Corynebacterium jeikeium K411 was reconstructed from the complete genome sequence. This bioinformatic approach detected a gene-regulatory repertoire of 83 candidate proteins, including 56 DNA-binding transcriptional regulators, nine two-component systems, nine sigma factors, and nine regulators with diverse physiological functions. Furthermore, a cross-genome comparison among selected corynebacterial species of the taxonomic cluster 3 revealed a common gene-regulatory repertoire of 44 transcriptional regulators, including the MarR-like regulator Jk0257, which is exclusively encoded in the genomes of this taxonomical subline. The current network reconstruction comprises 48 transcriptional regulators and 674 gene-regulatory interactions that were assigned to five interconnected functional modules. Most genes involved in lipid degradation are under the combined control of the global cAMP-sensing transcriptional regulator GlxR and the LuxR-family regulator RamA, probably reflecting the essential role of lipid degradation in C. jeikeium. This study provides the first genome-scale in silico analysis of the transcriptional regulation of metabolism in a lipophilic bacterium involved in the formation of human body odor. Copyright © 2012 Elsevier B.V. All rights reserved.

Accurate prediction of protein–protein interactions from sequence alignments using a Bayesian method

PubMed Central

Burger, Lukas; van Nimwegen, Erik

2008-01-01

Accurate and large-scale prediction of protein–protein interactions directly from amino-acid sequences is one of the great challenges in computational biology. Here we present a new Bayesian network method that predicts interaction partners using only multiple alignments of amino-acid sequences of interacting protein domains, without tunable parameters, and without the need for any training examples. We first apply the method to bacterial two-component systems and comprehensively reconstruct two-component signaling networks across all sequenced bacteria. Comparisons of our predictions with known interactions show that our method infers interaction partners genome-wide with high accuracy. To demonstrate the general applicability of our method we show that it also accurately predicts interaction partners in a recent dataset of polyketide synthases. Analysis of the predicted genome-wide two-component signaling networks shows that cognates (interacting kinase/regulator pairs, which lie adjacent on the genome) and orphans (which lie isolated) form two relatively independent components of the signaling network in each genome. In addition, while most genes are predicted to have only a small number of interaction partners, we find that 10% of orphans form a separate class of ‘hub' nodes that distribute and integrate signals to and from up to tens of different interaction partners. PMID:18277381

Robust co-regulation of tyrosine phosphorylation sites on proteins reveals novel protein interactions†

PubMed Central

Naegle, Kristen M.; White, Forest M.; Lauffenburger, Douglas A.; Yaffe, Michael B.

2012-01-01

Cell signaling networks propagate information from extracellular cues via dynamic modulation of protein–protein interactions in a context-dependent manner. Networks based on receptor tyrosine kinases (RTKs), for example, phosphorylate intracellular proteins in response to extracellular ligands, resulting in dynamic protein–protein interactions that drive phenotypic changes. Most commonly used methods for discovering these protein–protein interactions, however, are optimized for detecting stable, longer-lived complexes, rather than the type of transient interactions that are essential components of dynamic signaling networks such as those mediated by RTKs. Substrate phosphorylation downstream of RTK activation modifies substrate activity and induces phospho-specific binding interactions, resulting in the formation of large transient macromolecular signaling complexes. Since protein complex formation should follow the trajectory of events that drive it, we reasoned that mining phosphoproteomic datasets for highly similar dynamic behavior of measured phosphorylation sites on different proteins could be used to predict novel, transient protein–protein interactions that had not been previously identified. We applied this method to explore signaling events downstream of EGFR stimulation. Our computational analysis of robustly co-regulated phosphorylation sites, based on multiple clustering analysis of quantitative time-resolved mass-spectrometry phosphoproteomic data, not only identified known sitewise-specific recruitment of proteins to EGFR, but also predicted novel, a priori interactions. A particularly intriguing prediction of EGFR interaction with the cytoskeleton-associated protein PDLIM1 was verified within cells using co-immunoprecipitation and in situ proximity ligation assays. Our approach thus offers a new way to discover protein–protein interactions in a dynamic context- and phosphorylation site-specific manner. PMID:22851037

Probing Allosteric Inhibition Mechanisms of the Hsp70 Chaperone Proteins Using Molecular Dynamics Simulations and Analysis of the Residue Interaction Networks.

PubMed

Stetz, Gabrielle; Verkhivker, Gennady M

2016-08-22

Although molecular mechanisms of allosteric regulation in the Hsp70 chaperones have been extensively studied at both structural and functional levels, the current understanding of allosteric inhibition of chaperone activities by small molecules is still lacking. In the current study, using a battery of computational approaches, we probed allosteric inhibition mechanisms of E. coli Hsp70 (DnaK) and human Hsp70 proteins by small molecule inhibitors PET-16 and novolactone. Molecular dynamics simulations and binding free energy analysis were combined with network-based modeling of residue interactions and allosteric communications to systematically characterize and compare molecular signatures of the apo form, substrate-bound, and inhibitor-bound chaperone complexes. The results suggested a mechanism by which the allosteric inhibitors may leverage binding energy hotspots in the interaction networks to stabilize a specific conformational state and impair the interdomain allosteric control. Using the network-based centrality analysis and community detection, we demonstrated that substrate binding may strengthen the connectivity of local interaction communities, leading to a dense interaction network that can promote an efficient allosteric communication. In contrast, binding of PET-16 to DnaK may induce significant dynamic changes and lead to a fractured interaction network and impaired allosteric communications in the DnaK complex. By using a mechanistic-based analysis of distance fluctuation maps and allosteric propensities of protein residues, we determined that the allosteric network in the PET-16 complex may be small and localized due to the reduced communication and low cooperativity of the substrate binding loops, which may promote the higher rates of substrate dissociation and the decreased substrate affinity. In comparison with the significant effect of PET-16, binding of novolactone to HSPA1A may cause only moderate network changes and preserve allosteric coupling between the allosteric pocket and the substrate binding region. The impact of novolactone on the conformational dynamics and allosteric communications in the HSPA1A complex was comparable to the substrate effect, which is consistent with the experimental evidence that PET-16, but not novolactone binding, can significantly decrease substrate affinity. We argue that the unique dynamic and network signatures of PET-16 and novolactone may be linked with the experimentally observed functional effects of these inhibitors on allosteric regulation and substrate binding.

Multiple-Localization and Hub Proteins

PubMed Central

Ota, Motonori; Gonja, Hideki; Koike, Ryotaro; Fukuchi, Satoshi

2016-01-01

Protein-protein interactions are fundamental for all biological phenomena, and protein-protein interaction networks provide a global view of the interactions. The hub proteins, with many interaction partners, play vital roles in the networks. We investigated the subcellular localizations of proteins in the human network, and found that the ones localized in multiple subcellular compartments, especially the nucleus/cytoplasm proteins (NCP), the cytoplasm/cell membrane proteins (CMP), and the nucleus/cytoplasm/cell membrane proteins (NCMP), tend to be hubs. Examinations of keywords suggested that among NCP, those related to post-translational modifications and transcription functions are the major contributors to the large number of interactions. These types of proteins are characterized by a multi-domain architecture and intrinsic disorder. A survey of the typical hub proteins with prominent numbers of interaction partners in the type revealed that most are either transcription factors or co-regulators involved in signaling pathways. They translocate from the cytoplasm to the nucleus, triggered by the phosphorylation and/or ubiquitination of intrinsically disordered regions. Among CMP and NCMP, the contributors to the numerous interactions are related to either kinase or ubiquitin ligase activity. Many of them reside on the cytoplasmic side of the cell membrane, and act as the upstream regulators of signaling pathways. Overall, these hub proteins function to transfer external signals to the nucleus, through the cell membrane and the cytoplasm. Our analysis suggests that multiple-localization is a crucial concept to characterize groups of hub proteins and their biological functions in cellular information processing. PMID:27285823

Analysis of diverse regulatory networks in a hierarchical context shows consistent tendencies for collaboration in the middle levels

PubMed Central

Bhardwaj, Nitin; Yan, Koon-Kiu; Gerstein, Mark B.

2010-01-01

Gene regulatory networks have been shown to share some common aspects with commonplace social governance structures. Thus, we can get some intuition into their organization by arranging them into well-known hierarchical layouts. These hierarchies, in turn, can be placed between the extremes of autocracies, with well-defined levels and clear chains of command, and democracies, without such defined levels and with more co-regulatory partnerships between regulators. In general, the presence of partnerships decreases the variation in information flow amongst nodes within a level, more evenly distributing stress. Here we study various regulatory networks (transcriptional, modification, and phosphorylation) for five diverse species, Escherichia coli to human. We specify three levels of regulators—top, middle, and bottom—which collectively govern the non-regulator targets lying in the lowest fourth level. We define quantities for nodes, levels, and entire networks that measure their degree of collaboration and autocratic vs. democratic character. We show individual regulators have a range of partnership tendencies: Some regulate their targets in combination with other regulators in local instantiations of democratic structure, whereas others regulate mostly in isolation, in more autocratic fashion. Overall, we show that in all networks studied the middle level has the highest collaborative propensity and coregulatory partnerships occur most frequently amongst midlevel regulators, an observation that has parallels in corporate settings where middle managers must interact most to ensure organizational effectiveness. There is, however, one notable difference between networks in different species: The amount of collaborative regulation and democratic character increases markedly with overall genomic complexity. PMID:20351254

An expanding universe of circadian networks in higher plants.

PubMed

Pruneda-Paz, Jose L; Kay, Steve A

2010-05-01

Extensive circadian clock networks regulate almost every biological process in plants. Clock-controlled physiological responses are coupled with daily oscillations in environmental conditions resulting in enhanced fitness and growth vigor. Identification of core clock components and their associated molecular interactions has established the basic network architecture of plant clocks, which consists of multiple interlocked feedback loops. A hierarchical structure of transcriptional feedback overlaid with regulated protein turnover sets the pace of the clock and ultimately drives all clock-controlled processes. Although originally described as linear entities, increasing evidence suggests that many signaling pathways can act as both inputs and outputs within the overall network. Future studies will determine the molecular mechanisms involved in these complex regulatory loops. 2010 Elsevier Ltd. All rights reserved.

The comprehensive liver transcriptome of two cattle breeds with different intramuscular fat content.

PubMed

Wang, Xi; Zhang, Yuanqing; Zhang, Xizhong; Wang, Dongcai; Jin, Guang; Li, Bo; Xu, Fang; Cheng, Jing; Zhang, Feng; Wu, Sujun; Rui, Su; He, Jiang; Zhang, Ronghua; Liu, Wenzhong

2017-08-26

Intramuscular fat (IMF) content is an important determinant factor of meat quality in cattle. There is significant difference in IMF content between Jinnan and Simmental cattle. Here, to identify candidate genes and networks associated with IMF deposition, we deeply explored the transcriptome architecture of liver in these two cattle breeds. We sequenced the liver transcriptome of five Jinnan and three Simmental cattle, yielding about 413.9 million sequencing reads. 124 differentially expressed genes (DEGs) were detected, of which 53 were up-regulated and 71 were down-regulated in Jinnan cattle. 1282 potentially novel genes were also identified. Gene ontology analysis revealed these DEGs (including CYP21A2, PC, ACACB, APOA1, and FADS2) were significantly enriched in lipid biosynthetic process, regulation of cholesterol esterification, reverse cholesterol transport, and regulation of lipoprotein lipase activity. Genes involved in pyruvate metabolism pathway were also significantly overrepresented. Moreover, we identified an interaction network which related to lipid metabolism, which might be contributed to the IMF deposition in cattle. We concluded that the DEGs involved in the regulation of lipid metabolism could play an important role in IMF deposition. Overall, we proposed a new panel of candidate genes and interaction networks that can be associated with IMF deposition and used as biomarkers in cattle breeding. Copyright © 2017 Elsevier Inc. All rights reserved.

The impact of the metabotropic glutamate receptor and other gene family interaction networks on autism

PubMed Central

Hadley, Dexter; Wu, Zhi-liang; Kao, Charlly; Kini, Akshata; Mohamed-Hadley, Alisha; Thomas, Kelly; Vazquez, Lyam; Qiu, Haijun; Mentch, Frank; Pellegrino, Renata; Kim, Cecilia; Connolly, John; Pinto, Dalila; Merikangas, Alison; Klei, Lambertus; Vorstman, Jacob A.S.; Thompson, Ann; Regan, Regina; Pagnamenta, Alistair T.; Oliveira, Bárbara; Magalhaes, Tiago R.; Gilbert, John; Duketis, Eftichia; De Jonge, Maretha V.; Cuccaro, Michael; Correia, Catarina T.; Conroy, Judith; Conceição, Inês C.; Chiocchetti, Andreas G.; Casey, Jillian P.; Bolshakova, Nadia; Bacchelli, Elena; Anney, Richard; Zwaigenbaum, Lonnie; Wittemeyer, Kerstin; Wallace, Simon; Engeland, Herman van; Soorya, Latha; Rogé, Bernadette; Roberts, Wendy; Poustka, Fritz; Mouga, Susana; Minshew, Nancy; McGrew, Susan G.; Lord, Catherine; Leboyer, Marion; Le Couteur, Ann S.; Kolevzon, Alexander; Jacob, Suma; Guter, Stephen; Green, Jonathan; Green, Andrew; Gillberg, Christopher; Fernandez, Bridget A.; Duque, Frederico; Delorme, Richard; Dawson, Geraldine; Café, Cátia; Brennan, Sean; Bourgeron, Thomas; Bolton, Patrick F.; Bölte, Sven; Bernier, Raphael; Baird, Gillian; Bailey, Anthony J.; Anagnostou, Evdokia; Almeida, Joana; Wijsman, Ellen M.; Vieland, Veronica J.; Vicente, Astrid M.; Schellenberg, Gerard D.; Pericak-Vance, Margaret; Paterson, Andrew D.; Parr, Jeremy R.; Oliveira, Guiomar; Almeida, Joana; Café, Cátia; Mouga, Susana; Correia, Catarina; Nurnberger, John I.; Monaco, Anthony P.; Maestrini, Elena; Klauck, Sabine M.; Hakonarson, Hakon; Haines, Jonathan L.; Geschwind, Daniel H.; Freitag, Christine M.; Folstein, Susan E.; Ennis, Sean; Coon, Hilary; Battaglia, Agatino; Szatmari, Peter; Sutcliffe, James S.; Hallmayer, Joachim; Gill, Michael; Cook, Edwin H.; Buxbaum, Joseph D.; Devlin, Bernie; Gallagher, Louise; Betancur, Catalina; Scherer, Stephen W.; Glessner, Joseph; Hakonarson, Hakon

2014-01-01

Although multiple reports show that defective genetic networks underlie the aetiology of autism, few have translated into pharmacotherapeutic opportunities. Since drugs compete with endogenous small molecules for protein binding, many successful drugs target large gene families with multiple drug binding sites. Here we search for defective gene family interaction networks (GFINs) in 6,742 patients with the ASDs relative to 12,544 neurologically normal controls, to find potentially druggable genetic targets. We find significant enrichment of structural defects (P≤2.40E−09, 1.8-fold enrichment) in the metabotropic glutamate receptor (GRM) GFIN, previously observed to impact attention deficit hyperactivity disorder (ADHD) and schizophrenia. Also, the MXD-MYC-MAX network of genes, previously implicated in cancer, is significantly enriched (P≤3.83E−23, 2.5-fold enrichment), as is the calmodulin 1 (CALM1) gene interaction network (P≤4.16E−04, 14.4-fold enrichment), which regulates voltage-independent calcium-activated action potentials at the neuronal synapse. We find that multiple defective gene family interactions underlie autism, presenting new translational opportunities to explore for therapeutic interventions. PMID:24927284

Network Modeling of microRNA-mRNA Interactions in Neuroblastoma Tumorigenesis Identifies miR-204 as a Direct Inhibitor of MYCN.

PubMed

Ooi, Chi Yan; Carter, Daniel R; Liu, Bing; Mayoh, Chelsea; Beckers, Anneleen; Lalwani, Amit; Nagy, Zsuzsanna; De Brouwer, Sara; Decaesteker, Bieke; Hung, Tzong-Tyng; Norris, Murray D; Haber, Michelle; Liu, Tao; De Preter, Katleen; Speleman, Frank; Cheung, Belamy B; Marshall, Glenn M

2018-06-15

Neuroblastoma is a pediatric cancer of the sympathetic nervous system where MYCN amplification is a key indicator of poor prognosis. However, mechanisms by which MYCN promotes neuroblastoma tumorigenesis are not fully understood. In this study, we analyzed global miRNA and mRNA expression profiles of tissues at different stages of tumorigenesis from TH-MYCN transgenic mice, a model of MYCN-driven neuroblastoma. On the basis of a Bayesian learning network model in which we compared pretumor ganglia from TH-MYCN +/+ mice to age-matched wild-type controls, we devised a predicted miRNA-mRNA interaction network. Among the miRNA-mRNA interactions operating during human neuroblastoma tumorigenesis, we identified miR-204 as a tumor suppressor miRNA that inhibited a subnetwork of oncogenes strongly associated with MYCN -amplified neuroblastoma and poor patient outcome. MYCN bound to the miR-204 promoter and repressed miR-204 transcription. Conversely, miR-204 directly bound MYCN mRNA and repressed MYCN expression. miR-204 overexpression significantly inhibited neuroblastoma cell proliferation in vitro and tumorigenesis in vivo Together, these findings identify novel tumorigenic miRNA gene networks and miR-204 as a tumor suppressor that regulates MYCN expression in neuroblastoma tumorigenesis. Significance: Network modeling of miRNA-mRNA regulatory interactions in a mouse model of neuroblastoma identifies miR-204 as a tumor suppressor and negative regulator of MYCN. Cancer Res; 78(12); 3122-34. ©2018 AACR . ©2018 American Association for Cancer Research.

Network analyses based on comprehensive molecular interaction maps reveal robust control structures in yeast stress response pathways

PubMed Central

Kawakami, Eiryo; Singh, Vivek K; Matsubara, Kazuko; Ishii, Takashi; Matsuoka, Yukiko; Hase, Takeshi; Kulkarni, Priya; Siddiqui, Kenaz; Kodilkar, Janhavi; Danve, Nitisha; Subramanian, Indhupriya; Katoh, Manami; Shimizu-Yoshida, Yuki; Ghosh, Samik; Jere, Abhay; Kitano, Hiroaki

2016-01-01

Cellular stress responses require exquisite coordination between intracellular signaling molecules to integrate multiple stimuli and actuate specific cellular behaviors. Deciphering the web of complex interactions underlying stress responses is a key challenge in understanding robust biological systems and has the potential to lead to the discovery of targeted therapeutics for diseases triggered by dysregulation of stress response pathways. We constructed large-scale molecular interaction maps of six major stress response pathways in Saccharomyces cerevisiae (baker’s or budding yeast). Biological findings from over 900 publications were converted into standardized graphical formats and integrated into a common framework. The maps are posted at http://www.yeast-maps.org/yeast-stress-response/ for browse and curation by the research community. On the basis of these maps, we undertook systematic analyses to unravel the underlying architecture of the networks. A series of network analyses revealed that yeast stress response pathways are organized in bow–tie structures, which have been proposed as universal sub-systems for robust biological regulation. Furthermore, we demonstrated a potential role for complexes in stabilizing the conserved core molecules of bow–tie structures. Specifically, complex-mediated reversible reactions, identified by network motif analyses, appeared to have an important role in buffering the concentration and activity of these core molecules. We propose complex-mediated reactions as a key mechanism mediating robust regulation of the yeast stress response. Thus, our comprehensive molecular interaction maps provide not only an integrated knowledge base, but also a platform for systematic network analyses to elucidate the underlying architecture in complex biological systems. PMID:28725465

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

PubMed

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

2013-07-01

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

Continuous time Bayesian networks identify Prdm1 as a negative regulator of TH17 cell differentiation in humans

PubMed Central

Acerbi, Enzo; Viganò, Elena; Poidinger, Michael; Mortellaro, Alessandra; Zelante, Teresa; Stella, Fabio

2016-01-01

T helper 17 (TH17) cells represent a pivotal adaptive cell subset involved in multiple immune disorders in mammalian species. Deciphering the molecular interactions regulating TH17 cell differentiation is particularly critical for novel drug target discovery designed to control maladaptive inflammatory conditions. Using continuous time Bayesian networks over a time-course gene expression dataset, we inferred the global regulatory network controlling TH17 differentiation. From the network, we identified the Prdm1 gene encoding the B lymphocyte-induced maturation protein 1 as a crucial negative regulator of human TH17 cell differentiation. The results have been validated by perturbing Prdm1 expression on freshly isolated CD4+ naïve T cells: reduction of Prdm1 expression leads to augmentation of IL-17 release. These data unravel a possible novel target to control TH17 polarization in inflammatory disorders. Furthermore, this study represents the first in vitro validation of continuous time Bayesian networks as gene network reconstruction method and as hypothesis generation tool for wet-lab biological experiments. PMID:26976045

Mechanisms and Evolution of Control Logic in Prokaryotic Transcriptional Regulation

PubMed Central

van Hijum, Sacha A. F. T.; Medema, Marnix H.; Kuipers, Oscar P.

2009-01-01

Summary: A major part of organismal complexity and versatility of prokaryotes resides in their ability to fine-tune gene expression to adequately respond to internal and external stimuli. Evolution has been very innovative in creating intricate mechanisms by which different regulatory signals operate and interact at promoters to drive gene expression. The regulation of target gene expression by transcription factors (TFs) is governed by control logic brought about by the interaction of regulators with TF binding sites (TFBSs) in cis-regulatory regions. A factor that in large part determines the strength of the response of a target to a given TF is motif stringency, the extent to which the TFBS fits the optimal TFBS sequence for a given TF. Advances in high-throughput technologies and computational genomics allow reconstruction of transcriptional regulatory networks in silico. To optimize the prediction of transcriptional regulatory networks, i.e., to separate direct regulation from indirect regulation, a thorough understanding of the control logic underlying the regulation of gene expression is required. This review summarizes the state of the art of the elements that determine the functionality of TFBSs by focusing on the molecular biological mechanisms and evolutionary origins of cis-regulatory regions. PMID:19721087

Cortactin Branches Out: Roles in Regulating Protrusive Actin Dynamics

PubMed Central

Ammer, Amanda Gatesman; Weed, Scott A.

2008-01-01

Since its discovery in the early 1990’s, cortactin has emerged as a key signaling protein in many cellular processes, including cell adhesion, migration, endocytosis, and tumor invasion. While the list of cellular functions influenced by cortactin grows, the ability of cortactin to interact with and alter the cortical actin network is central to its role in regulating these processes. Recently, several advances have been made in our understanding of the interaction between actin and cortactin, providing insight into how these two proteins work together to provide a framework for normal and altered cellular function. This review examines how regulation of cortactin through post-translational modifications and interactions with multiple binding partners elicits changes in cortical actin cytoskeletal organization, impacting the regulation and formation of actin-rich motility structures. PMID:18615630

Pathway redundancy and protein essentiality revealed in the Saccharomyces cerevisiae interaction networks

PubMed Central

Ulitsky, Igor; Shamir, Ron

2007-01-01

The biological interpretation of genetic interactions is a major challenge. Recently, Kelley and Ideker proposed a method to analyze together genetic and physical networks, which explains many of the known genetic interactions as linking different pathways in the physical network. Here, we extend this method and devise novel analytic tools for interpreting genetic interactions in a physical context. Applying these tools on a large-scale Saccharomyces cerevisiae data set, our analysis reveals 140 between-pathway models that explain 3765 genetic interactions, roughly doubling those that were previously explained. Model genes tend to have short mRNA half-lives and many phosphorylation sites, suggesting that their stringent regulation is linked to pathway redundancy. We also identify ‘pivot' proteins that have many physical interactions with both pathways in our models, and show that pivots tend to be essential and highly conserved. Our analysis of models and pivots sheds light on the organization of the cellular machinery as well as on the roles of individual proteins. PMID:17437029

Discovery of Intramolecular Signal Transduction Network Based on a New Protein Dynamics Model of Energy Dissipation

PubMed Central

Ma, Cheng-Wei; Xiu, Zhi-Long; Zeng, An-Ping

2012-01-01

A novel approach to reveal intramolecular signal transduction network is proposed in this work. To this end, a new algorithm of network construction is developed, which is based on a new protein dynamics model of energy dissipation. A key feature of this approach is that direction information is specified after inferring protein residue-residue interaction network involved in the process of signal transduction. This enables fundamental analysis of the regulation hierarchy and identification of regulation hubs of the signaling network. A well-studied allosteric enzyme, E. coli aspartokinase III, is used as a model system to demonstrate the new method. Comparison with experimental results shows that the new approach is able to predict all the sites that have been experimentally proved to desensitize allosteric regulation of the enzyme. In addition, the signal transduction network shows a clear preference for specific structural regions, secondary structural types and residue conservation. Occurrence of super-hubs in the network indicates that allosteric regulation tends to gather residues with high connection ability to collectively facilitate the signaling process. Furthermore, a new parameter of propagation coefficient is defined to determine the propagation capability of residues within a signal transduction network. In conclusion, the new approach is useful for fundamental understanding of the process of intramolecular signal transduction and thus has significant impact on rational design of novel allosteric proteins. PMID:22363664

Nestedness across biological scales

PubMed Central

Marquitti, Flavia M. D.; Raimundo, Rafael L. G.; Sebastián-González, Esther; Coltri, Patricia P.; Perez, S. Ivan; Brandt, Débora Y. C.; Nunes, Kelly; Daura-Jorge, Fábio G.; Floeter, Sergio R.; Guimarães, Paulo R.

2017-01-01

Biological networks pervade nature. They describe systems throughout all levels of biological organization, from molecules regulating metabolism to species interactions that shape ecosystem dynamics. The network thinking revealed recurrent organizational patterns in complex biological systems, such as the formation of semi-independent groups of connected elements (modularity) and non-random distributions of interactions among elements. Other structural patterns, such as nestedness, have been primarily assessed in ecological networks formed by two non-overlapping sets of elements; information on its occurrence on other levels of organization is lacking. Nestedness occurs when interactions of less connected elements form proper subsets of the interactions of more connected elements. Only recently these properties began to be appreciated in one-mode networks (where all elements can interact) which describe a much wider variety of biological phenomena. Here, we compute nestedness in a diverse collection of one-mode networked systems from six different levels of biological organization depicting gene and protein interactions, complex phenotypes, animal societies, metapopulations, food webs and vertebrate metacommunities. Our findings suggest that nestedness emerge independently of interaction type or biological scale and reveal that disparate systems can share nested organization features characterized by inclusive subsets of interacting elements with decreasing connectedness. We primarily explore the implications of a nested structure for each of these studied systems, then theorize on how nested networks are assembled. We hypothesize that nestedness emerges across scales due to processes that, although system-dependent, may share a general compromise between two features: specificity (the number of interactions the elements of the system can have) and affinity (how these elements can be connected to each other). Our findings suggesting occurrence of nestedness throughout biological scales can stimulate the debate on how pervasive nestedness may be in nature, while the theoretical emergent principles can aid further research on commonalities of biological networks. PMID:28166284

Tightly Regulated Expression of Autographa californica Multicapsid Nucleopolyhedrovirus Immediate Early Genes Emerges from Their Interactions and Possible Collective Behaviors

PubMed Central

Taka, Hitomi; Asano, Shin-ichiro; Matsuura, Yoshiharu; Bando, Hisanori

2015-01-01

To infect their hosts, DNA viruses must successfully initiate the expression of viral genes that control subsequent viral gene expression and manipulate the host environment. Viral genes that are immediately expressed upon infection play critical roles in the early infection process. In this study, we investigated the expression and regulation of five canonical regulatory immediate-early (IE) genes of Autographa californica multicapsid nucleopolyhedrovirus: ie0, ie1, ie2, me53, and pe38. A systematic transient gene-expression analysis revealed that these IE genes are generally transactivators, suggesting the existence of a highly interactive regulatory network. A genetic analysis using gene knockout viruses demonstrated that the expression of these IE genes was tolerant to the single deletions of activator IE genes in the early stage of infection. A network graph analysis on the regulatory relationships observed in the transient expression analysis suggested that the robustness of IE gene expression is due to the organization of the IE gene regulatory network and how each IE gene is activated. However, some regulatory relationships detected by the genetic analysis were contradictory to those observed in the transient expression analysis, especially for IE0-mediated regulation. Statistical modeling, combined with genetic analysis using knockout alleles for ie0 and ie1, showed that the repressor function of ie0 was due to the interaction between ie0 and ie1, not ie0 itself. Taken together, these systematic approaches provided insight into the topology and nature of the IE gene regulatory network. PMID:25816136

Split luciferase complementation assay to detect regulated protein-protein interactions in rice protoplasts in a large-scale format

PubMed Central

2014-01-01

Background The rice interactome, in which a network of protein-protein interactions has been elucidated in rice, is a useful resource to identify functional modules of rice signal transduction pathways. Protein-protein interactions occur in cells in two ways, constitutive and regulative. While a yeast-based high-throughput method has been widely used to identify the constitutive interactions, a method to detect the regulated interactions is rarely developed for a large-scale analysis. Results A split luciferase complementation assay was applied to detect the regulated interactions in rice. A transformation method of rice protoplasts in a 96-well plate was first established for a large-scale analysis. In addition, an antibody that specifically recognizes a carboxyl-terminal fragment of Renilla luciferase was newly developed. A pair of antibodies that recognize amino- and carboxyl- terminal fragments of Renilla luciferase, respectively, was then used to monitor quality and quantity of interacting recombinant-proteins accumulated in the cells. For a proof-of-concept, the method was applied to detect the gibberellin-dependent interaction between GIBBERELLIN INSENSITIVE DWARF1 and SLENDER RICE 1. Conclusions A method to detect regulated protein-protein interactions was developed towards establishment of the rice interactome. PMID:24987490

Becoming popular: interpersonal emotion regulation predicts relationship formation in real life social networks.

PubMed

Niven, Karen; Garcia, David; van der Löwe, Ilmo; Holman, David; Mansell, Warren

2015-01-01

Building relationships is crucial for satisfaction and success, especially when entering new social contexts. In the present paper, we investigate whether attempting to improve others' feelings helps people to make connections in new networks. In Study 1, a social network study following new networks of people for a 12-week period indicated that use of interpersonal emotion regulation (IER) strategies predicted growth in popularity, as indicated by other network members' reports of spending time with the person, in work and non-work interactions. In Study 2, linguistic analysis of the tweets from over 8000 Twitter users from formation of their accounts revealed that use of IER predicted greater popularity in terms of the number of followers gained. However, not all types of IER had positive effects. Behavioral IER strategies (which use behavior to reassure or comfort in order to regulate affect) were associated with greater popularity, while cognitive strategies (which change a person's thoughts about his or her situation or feelings in order to regulate affect) were negatively associated with popularity. Our findings have implications for our understanding of how new relationships are formed, highlighting the important the role played by intentional emotion regulatory processes.

Becoming popular: interpersonal emotion regulation predicts relationship formation in real life social networks

PubMed Central

Niven, Karen; Garcia, David; van der Löwe, Ilmo; Holman, David; Mansell, Warren

2015-01-01

Building relationships is crucial for satisfaction and success, especially when entering new social contexts. In the present paper, we investigate whether attempting to improve others’ feelings helps people to make connections in new networks. In Study 1, a social network study following new networks of people for a 12-week period indicated that use of interpersonal emotion regulation (IER) strategies predicted growth in popularity, as indicated by other network members’ reports of spending time with the person, in work and non-work interactions. In Study 2, linguistic analysis of the tweets from over 8000 Twitter users from formation of their accounts revealed that use of IER predicted greater popularity in terms of the number of followers gained. However, not all types of IER had positive effects. Behavioral IER strategies (which use behavior to reassure or comfort in order to regulate affect) were associated with greater popularity, while cognitive strategies (which change a person’s thoughts about his or her situation or feelings in order to regulate affect) were negatively associated with popularity. Our findings have implications for our understanding of how new relationships are formed, highlighting the important the role played by intentional emotion regulatory processes. PMID:26483718

Association Between Young Australian's Drinking Behaviours and Their Interactions With Alcohol Brands on Facebook: Results of an Online Survey.

PubMed

Jones, Sandra C; Robinson, Laura; Barrie, Lance; Francis, Kate; Lee, Jeong Kyu

2016-07-01

To examine the association of alcohol-brand social networking pages and Facebook users' drinking attitudes and behaviours. Cross-sectional, self-report data were obtained from a convenience sample of 283 Australian Facebook users aged 16-24 years via an online survey. More than half of the respondents reported using Facebook for more than an hour daily. While only 20% had actively interacted with an alcohol brand on Facebook, we found a significant association between this active interaction and alcohol consumption, and a strong association between engagement with alcohol brands on Facebook and problematic drinking. The findings of this study demonstrate the need for further research into the complex interaction between social networking and alcohol consumption, and add support to calls for effective regulation of alcohol marketing on social network platforms. © The Author 2015. Medical Council on Alcohol and Oxford University Press. All rights reserved.

Causal structure of oscillations in gene regulatory networks: Boolean analysis of ordinary differential equation attractors.

PubMed

Sun, Mengyang; Cheng, Xianrui; Socolar, Joshua E S

2013-06-01

A common approach to the modeling of gene regulatory networks is to represent activating or repressing interactions using ordinary differential equations for target gene concentrations that include Hill function dependences on regulator gene concentrations. An alternative formulation represents the same interactions using Boolean logic with time delays associated with each network link. We consider the attractors that emerge from the two types of models in the case of a simple but nontrivial network: a figure-8 network with one positive and one negative feedback loop. We show that the different modeling approaches give rise to the same qualitative set of attractors with the exception of a possible fixed point in the ordinary differential equation model in which concentrations sit at intermediate values. The properties of the attractors are most easily understood from the Boolean perspective, suggesting that time-delay Boolean modeling is a useful tool for understanding the logic of regulatory networks.

In silico prediction of protein-protein interactions in human macrophages

PubMed Central

2014-01-01

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

Inferring Boolean network states from partial information

PubMed Central

2013-01-01

Networks of molecular interactions regulate key processes in living cells. Therefore, understanding their functionality is a high priority in advancing biological knowledge. Boolean networks are often used to describe cellular networks mathematically and are fitted to experimental datasets. The fitting often results in ambiguities since the interpretation of the measurements is not straightforward and since the data contain noise. In order to facilitate a more reliable mapping between datasets and Boolean networks, we develop an algorithm that infers network trajectories from a dataset distorted by noise. We analyze our algorithm theoretically and demonstrate its accuracy using simulation and microarray expression data. PMID:24006954

Morphine Regulated Synaptic Networks Revealed by Integrated Proteomics and Network Analysis*

PubMed Central

Stockton, Steven D.; Gomes, Ivone; Liu, Tong; Moraje, Chandrakala; Hipólito, Lucia; Jones, Matthew R.; Ma'ayan, Avi; Morón, Jose A.; Li, Hong; Devi, Lakshmi A.

2015-01-01

Despite its efficacy, the use of morphine for the treatment of chronic pain remains limited because of the rapid development of tolerance, dependence and ultimately addiction. These undesired effects are thought to be because of alterations in synaptic transmission and neuroplasticity within the reward circuitry including the striatum. In this study we used subcellular fractionation and quantitative proteomics combined with computational approaches to investigate the morphine-induced protein profile changes at the striatal postsynaptic density. Over 2,600 proteins were identified by mass spectrometry analysis of subcellular fractions enriched in postsynaptic density associated proteins from saline or morphine-treated striata. Among these, the levels of 34 proteins were differentially altered in response to morphine. These include proteins involved in G-protein coupled receptor signaling, regulation of transcription and translation, chaperones, and protein degradation pathways. The altered expression levels of several of these proteins was validated by Western blotting analysis. Using Genes2Fans software suite we connected the differentially expressed proteins with proteins identified within the known background protein-protein interaction network. This led to the generation of a network consisting of 116 proteins with 40 significant intermediates. To validate this, we confirmed the presence of three proteins predicted to be significant intermediates: caspase-3, receptor-interacting serine/threonine protein kinase 3 and NEDD4 (an E3-ubiquitin ligase identified as a neural precursor cell expressed developmentally down-regulated protein 4). Because this morphine-regulated network predicted alterations in proteasomal degradation, we examined the global ubiquitination state of postsynaptic density proteins and found it to be substantially altered. Together, these findings suggest a role for protein degradation and for the ubiquitin/proteasomal system in the etiology of opiate dependence and addiction. PMID:26149443

Network-Based Identification and Prioritization of Key Regulators of Coronary Artery Disease Loci

PubMed Central

Zhao, Yuqi; Chen, Jing; Freudenberg, Johannes M.; Meng, Qingying; Rajpal, Deepak K.; Yang, Xia

2017-01-01

Objective Recent genome-wide association studies of coronary artery disease (CAD) have revealed 58 genome-wide significant and 148 suggestive genetic loci. However, the molecular mechanisms through which they contribute to CAD and the clinical implications of these findings remain largely unknown. We aim to retrieve gene subnetworks of the 206 CAD loci and identify and prioritize candidate regulators to better understand the biological mechanisms underlying the genetic associations. Approach and Results We devised a new integrative genomics approach that incorporated (1) candidate genes from the top CAD loci, (2) the complete genetic association results from the 1000 genomes-based CAD genome-wide association studies from the Coronary Artery Disease Genome Wide Replication and Meta-Analysis Plus the Coronary Artery Disease consortium, (3) tissue-specific gene regulatory networks that depict the potential relationship and interactions between genes, and (4) tissue-specific gene expression patterns between CAD patients and controls. The networks and top-ranked regulators according to these data-driven criteria were further queried against literature, experimental evidence, and drug information to evaluate their disease relevance and potential as drug targets. Our analysis uncovered several potential novel regulators of CAD such as LUM and STAT3, which possess properties suitable as drug targets. We also revealed molecular relations and potential mechanisms through which the top CAD loci operate. Furthermore, we found that multiple CAD-relevant biological processes such as extracellular matrix, inflammatory and immune pathways, complement and coagulation cascades, and lipid metabolism interact in the CAD networks. Conclusions Our data-driven integrative genomics framework unraveled tissue-specific relations among the candidate genes of the CAD genome-wide association studies loci and prioritized novel network regulatory genes orchestrating biological processes relevant to CAD. PMID:26966275

Timescale analysis of rule-based biochemical reaction networks

PubMed Central

Klinke, David J.; Finley, Stacey D.

2012-01-01

The flow of information within a cell is governed by a series of protein-protein interactions that can be described as a reaction network. Mathematical models of biochemical reaction networks can be constructed by repetitively applying specific rules that define how reactants interact and what new species are formed upon reaction. To aid in understanding the underlying biochemistry, timescale analysis is one method developed to prune the size of the reaction network. In this work, we extend the methods associated with timescale analysis to reaction rules instead of the species contained within the network. To illustrate this approach, we applied timescale analysis to a simple receptor-ligand binding model and a rule-based model of Interleukin-12 (IL-12) signaling in näive CD4+ T cells. The IL-12 signaling pathway includes multiple protein-protein interactions that collectively transmit information; however, the level of mechanistic detail sufficient to capture the observed dynamics has not been justified based upon the available data. The analysis correctly predicted that reactions associated with JAK2 and TYK2 binding to their corresponding receptor exist at a pseudo-equilibrium. In contrast, reactions associated with ligand binding and receptor turnover regulate cellular response to IL-12. An empirical Bayesian approach was used to estimate the uncertainty in the timescales. This approach complements existing rank- and flux-based methods that can be used to interrogate complex reaction networks. Ultimately, timescale analysis of rule-based models is a computational tool that can be used to reveal the biochemical steps that regulate signaling dynamics. PMID:21954150

The default network and self-generated thought: component processes, dynamic control, and clinical relevance

PubMed Central

Andrews-Hanna, Jessica R.; Smallwood, Jonathan; Spreng, R. Nathan

2014-01-01

Though only a decade has elapsed since the default network was first emphasized as being a large-scale brain system, recent years have brought great insight into the network’s adaptive functions. A growing theme highlights the default network as playing a key role in internally-directed—or self-generated—thought. Here, we synthesize recent findings from cognitive science, neuroscience, and clinical psychology to focus attention on two emerging topics as current and future directions surrounding the default network. First, we present evidence that self-generated thought is a multi-faceted construct whose component processes are supported by different subsystems within the network. Second, we highlight the dynamic nature of the default network, emphasizing its interaction with executive control systems when regulating aspects of internal thought. We conclude by discussing clinical implications of disruptions to the integrity of the network, and consider disorders when thought content becomes polarized or network interactions become disrupted or imbalanced. PMID:24502540

Structural Basis of Cooperative Ligand Binding by the Glycine Riboswitch

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

E Butler; J Wang; Y Xiong

2011-12-31

The glycine riboswitch regulates gene expression through the cooperative recognition of its amino acid ligand by a tandem pair of aptamers. A 3.6 {angstrom} crystal structure of the tandem riboswitch from the glycine permease operon of Fusobacterium nucleatum reveals the glycine binding sites and an extensive network of interactions, largely mediated by asymmetric A-minor contacts, that serve to communicate ligand binding status between the aptamers. These interactions provide a structural basis for how the glycine riboswitch cooperatively regulates gene expression.

Systematic review of computational methods for identifying miRNA-mediated RNA-RNA crosstalk.

PubMed

Li, Yongsheng; Jin, Xiyun; Wang, Zishan; Li, Lili; Chen, Hong; Lin, Xiaoyu; Yi, Song; Zhang, Yunpeng; Xu, Juan

2017-10-25

Posttranscriptional crosstalk and communication between RNAs yield large regulatory competing endogenous RNA (ceRNA) networks via shared microRNAs (miRNAs), as well as miRNA synergistic networks. The ceRNA crosstalk represents a novel layer of gene regulation that controls both physiological and pathological processes such as development and complex diseases. The rapidly expanding catalogue of ceRNA regulation has provided evidence for exploitation as a general model to predict the ceRNAs in silico. In this article, we first reviewed the current progress of RNA-RNA crosstalk in human complex diseases. Then, the widely used computational methods for modeling ceRNA-ceRNA interaction networks are further summarized into five types: two types of global ceRNA regulation prediction methods and three types of context-specific prediction methods, which are based on miRNA-messenger RNA regulation alone, or by integrating heterogeneous data, respectively. To provide guidance in the computational prediction of ceRNA-ceRNA interactions, we finally performed a comparative study of different combinations of miRNA-target methods as well as five types of ceRNA identification methods by using literature-curated ceRNA regulation and gene perturbation. The results revealed that integration of different miRNA-target prediction methods and context-specific miRNA/gene expression profiles increased the performance for identifying ceRNA regulation. Moreover, different computational methods were complementary in identifying ceRNA regulation and captured different functional parts of similar pathways. We believe that the application of these computational techniques provides valuable functional insights into ceRNA regulation and is a crucial step for informing subsequent functional validation studies. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Fractal Patterns of Neural Activity Exist within the Suprachiasmatic Nucleus and Require Extrinsic Network Interactions

PubMed Central

Hu, Kun; Meijer, Johanna H.; Shea, Steven A.; vanderLeest, Henk Tjebbe; Pittman-Polletta, Benjamin; Houben, Thijs; van Oosterhout, Floor; Deboer, Tom; Scheer, Frank A. J. L.

2012-01-01

The mammalian central circadian pacemaker (the suprachiasmatic nucleus, SCN) contains thousands of neurons that are coupled through a complex network of interactions. In addition to the established role of the SCN in generating rhythms of ∼24 hours in many physiological functions, the SCN was recently shown to be necessary for normal self-similar/fractal organization of motor activity and heart rate over a wide range of time scales—from minutes to 24 hours. To test whether the neural network within the SCN is sufficient to generate such fractal patterns, we studied multi-unit neural activity of in vivo and in vitro SCNs in rodents. In vivo SCN-neural activity exhibited fractal patterns that are virtually identical in mice and rats and are similar to those in motor activity at time scales from minutes up to 10 hours. In addition, these patterns remained unchanged when the main afferent signal to the SCN, namely light, was removed. However, the fractal patterns of SCN-neural activity are not autonomous within the SCN as these patterns completely broke down in the isolated in vitro SCN despite persistence of circadian rhythmicity. Thus, SCN-neural activity is fractal in the intact organism and these fractal patterns require network interactions between the SCN and extra-SCN nodes. Such a fractal control network could underlie the fractal regulation observed in many physiological functions that involve the SCN, including motor control and heart rate regulation. PMID:23185285

AMYGDALA MICROCIRCUITS CONTROLLING LEARNED FEAR

PubMed Central

Duvarci, Sevil; Pare, Denis

2014-01-01

We review recent work on the role of intrinsic amygdala networks in the regulation of classically conditioned defensive behaviors, commonly known as conditioned fear. These new developments highlight how conditioned fear depends on far more complex networks than initially envisioned. Indeed, multiple parallel inhibitory and excitatory circuits are differentially recruited during the expression versus extinction of conditioned fear. Moreover, shifts between expression and extinction circuits involve coordinated interactions with different regions of the medial prefrontal cortex. However, key areas of uncertainty remain, particularly with respect to the connectivity of the different cell types. Filling these gaps in our knowledge is important because much evidence indicates that human anxiety disorders results from an abnormal regulation of the networks supporting fear learning. PMID:24908482

Modeling of Kidney Hemodynamics: Probability-Based Topology of an Arterial Network.

PubMed

Postnov, Dmitry D; Marsh, Donald J; Postnov, Dmitry E; Braunstein, Thomas H; Holstein-Rathlou, Niels-Henrik; Martens, Erik A; Sosnovtseva, Olga

2016-07-01

Through regulation of the extracellular fluid volume, the kidneys provide important long-term regulation of blood pressure. At the level of the individual functional unit (the nephron), pressure and flow control involves two different mechanisms that both produce oscillations. The nephrons are arranged in a complex branching structure that delivers blood to each nephron and, at the same time, provides a basis for an interaction between adjacent nephrons. The functional consequences of this interaction are not understood, and at present it is not possible to address this question experimentally. We provide experimental data and a new modeling approach to clarify this problem. To resolve details of microvascular structure, we collected 3D data from more than 150 afferent arterioles in an optically cleared rat kidney. Using these results together with published micro-computed tomography (μCT) data we develop an algorithm for generating the renal arterial network. We then introduce a mathematical model describing blood flow dynamics and nephron to nephron interaction in the network. The model includes an implementation of electrical signal propagation along a vascular wall. Simulation results show that the renal arterial architecture plays an important role in maintaining adequate pressure levels and the self-sustained dynamics of nephrons.

Towards a comprehensive understanding of emerging dynamics and function of pancreatic islets: A complex network approach. Comment on "Network science of biological systems at different scales: A review" by Gosak et al.

NASA Astrophysics Data System (ADS)

Loppini, Alessandro

2018-03-01

Complex network theory represents a comprehensive mathematical framework to investigate biological systems, ranging from sub-cellular and cellular scales up to large-scale networks describing species interactions and ecological systems. In their exhaustive and comprehensive work [1], Gosak et al. discuss several scenarios in which the network approach was able to uncover general properties and underlying mechanisms of cells organization and regulation, tissue functions and cell/tissue failure in pathology, by the study of chemical reaction networks, structural networks and functional connectivities.

Identification of crucial genes related to postmenopausal osteoporosis using gene expression profiling.

PubMed

Ma, Min; Chen, Xiaofei; Lu, Liangyu; Yuan, Feng; Zeng, Wen; Luo, Shulin; Yin, Feng; Cai, Junfeng

2016-12-01

Postmenopausal osteoporosis is a common bone disease and characterized by low bone mineral density. This study aimed to reveal key genes associated with postmenopausal osteoporosis (PMO), and provide a theoretical basis for subsequent experiments. The dataset GSE7429 was obtained from Gene Expression Omnibus. A total of 20 B cell samples (ten ones, respectively from postmenopausal women with low or high bone mineral density (BMD) were included in this dataset. Following screening of differentially expressed genes (DEGs), coexpression analysis of all genes was performed, and key genes in the coexpression network were screened using the random walk algorithm. Afterwards, functional and pathway analyses were conducted. Additionally, protein-protein interactions (PPIs) between DEGs and key genes were analyzed. A set of 308 DEGs (170 up-regulated ones and 138 down-regulated ones) between low BMD and high BMD samples were identified, and 101 key genes in the coexpression network were screened out. In the coexpression network, some genes had a higher score and degree, such as CSTA. The key genes in the coexpression network were mainly enriched in GO terms of the defense response (e.g., SERPINA1 and CST3), immune response (e.g., IL32 and CLEC7A); while, the DEGs were mainly enriched in structural constituent of cytoskeleton (e.g., CYLC2 and TUBA1B) and membrane-enclosed lumen (e.g., CCNE1 and INTS5). In the PPI network, CCNE1 interacted with REL; and TUBA1B interacted with ESR1. A series of interactions, such as CSTA/TYROBP, CCNE1/REL and TUBA1B/ESR1 might play pivotal roles in the occurrence and development of PMO.

Ontology-based literature mining of E. coli vaccine-associated gene interaction networks.

PubMed

Hur, Junguk; Özgür, Arzucan; He, Yongqun

2017-03-14

Pathogenic Escherichia coli infections cause various diseases in humans and many animal species. However, with extensive E. coli vaccine research, we are still unable to fully protect ourselves against E. coli infections. To more rational development of effective and safe E. coli vaccine, it is important to better understand E. coli vaccine-associated gene interaction networks. In this study, we first extended the Vaccine Ontology (VO) to semantically represent various E. coli vaccines and genes used in the vaccine development. We also normalized E. coli gene names compiled from the annotations of various E. coli strains using a pan-genome-based annotation strategy. The Interaction Network Ontology (INO) includes a hierarchy of various interaction-related keywords useful for literature mining. Using VO, INO, and normalized E. coli gene names, we applied an ontology-based SciMiner literature mining strategy to mine all PubMed abstracts and retrieve E. coli vaccine-associated E. coli gene interactions. Four centrality metrics (i.e., degree, eigenvector, closeness, and betweenness) were calculated for identifying highly ranked genes and interaction types. Using vaccine-related PubMed abstracts, our study identified 11,350 sentences that contain 88 unique INO interactions types and 1,781 unique E. coli genes. Each sentence contained at least one interaction type and two unique E. coli genes. An E. coli gene interaction network of genes and INO interaction types was created. From this big network, a sub-network consisting of 5 E. coli vaccine genes, including carA, carB, fimH, fepA, and vat, and 62 other E. coli genes, and 25 INO interaction types was identified. While many interaction types represent direct interactions between two indicated genes, our study has also shown that many of these retrieved interaction types are indirect in that the two genes participated in the specified interaction process in a required but indirect process. Our centrality analysis of these gene interaction networks identified top ranked E. coli genes and 6 INO interaction types (e.g., regulation and gene expression). Vaccine-related E. coli gene-gene interaction network was constructed using ontology-based literature mining strategy, which identified important E. coli vaccine genes and their interactions with other genes through specific interaction types.

Model-based design of RNA hybridization networks implemented in living cells

PubMed Central

Rodrigo, Guillermo; Prakash, Satya; Shen, Shensi; Majer, Eszter

2017-01-01

Abstract Synthetic gene circuits allow the behavior of living cells to be reprogrammed, and non-coding small RNAs (sRNAs) are increasingly being used as programmable regulators of gene expression. However, sRNAs (natural or synthetic) are generally used to regulate single target genes, while complex dynamic behaviors would require networks of sRNAs regulating each other. Here, we report a strategy for implementing such networks that exploits hybridization reactions carried out exclusively by multifaceted sRNAs that are both targets of and triggers for other sRNAs. These networks are ultimately coupled to the control of gene expression. We relied on a thermodynamic model of the different stable conformational states underlying this system at the nucleotide level. To test our model, we designed five different RNA hybridization networks with a linear architecture, and we implemented them in Escherichia coli. We validated the network architecture at the molecular level by native polyacrylamide gel electrophoresis, as well as the network function at the bacterial population and single-cell levels with a fluorescent reporter. Our results suggest that it is possible to engineer complex cellular programs based on RNA from first principles. Because these networks are mainly based on physical interactions, our designs could be expanded to other organisms as portable regulatory resources or to implement biological computations. PMID:28934501

Salience network integrity predicts default mode network function after traumatic brain injury

PubMed Central

Bonnelle, Valerie; Ham, Timothy E.; Leech, Robert; Kinnunen, Kirsi M.; Mehta, Mitul A.; Greenwood, Richard J.; Sharp, David J.

2012-01-01

Efficient behavior involves the coordinated activity of large-scale brain networks, but the way in which these networks interact is uncertain. One theory is that the salience network (SN)—which includes the anterior cingulate cortex, presupplementary motor area, and anterior insulae—regulates dynamic changes in other networks. If this is the case, then damage to the structural connectivity of the SN should disrupt the regulation of associated networks. To investigate this hypothesis, we studied a group of 57 patients with cognitive impairments following traumatic brain injury (TBI) and 25 control subjects using the stop-signal task. The pattern of brain activity associated with stop-signal task performance was studied by using functional MRI, and the structural integrity of network connections was quantified by using diffusion tensor imaging. Efficient inhibitory control was associated with rapid deactivation within parts of the default mode network (DMN), including the precuneus and posterior cingulate cortex. TBI patients showed a failure of DMN deactivation, which was associated with an impairment of inhibitory control. TBI frequently results in traumatic axonal injury, which can disconnect brain networks by damaging white matter tracts. The abnormality of DMN function was specifically predicted by the amount of white matter damage in the SN tract connecting the right anterior insulae to the presupplementary motor area and dorsal anterior cingulate cortex. The results provide evidence that structural integrity of the SN is necessary for the efficient regulation of activity in the DMN, and that a failure of this regulation leads to inefficient cognitive control. PMID:22393019

Reconstructing gene regulatory networks from knock-out data using Gaussian Noise Model and Pearson Correlation Coefficient.

PubMed

Mohamed Salleh, Faridah Hani; Arif, Shereena Mohd; Zainudin, Suhaila; Firdaus-Raih, Mohd

2015-12-01

A gene regulatory network (GRN) is a large and complex network consisting of interacting elements that, over time, affect each other's state. The dynamics of complex gene regulatory processes are difficult to understand using intuitive approaches alone. To overcome this problem, we propose an algorithm for inferring the regulatory interactions from knock-out data using a Gaussian model combines with Pearson Correlation Coefficient (PCC). There are several problems relating to GRN construction that have been outlined in this paper. We demonstrated the ability of our proposed method to (1) predict the presence of regulatory interactions between genes, (2) their directionality and (3) their states (activation or suppression). The algorithm was applied to network sizes of 10 and 50 genes from DREAM3 datasets and network sizes of 10 from DREAM4 datasets. The predicted networks were evaluated based on AUROC and AUPR. We discovered that high false positive values were generated by our GRN prediction methods because the indirect regulations have been wrongly predicted as true relationships. We achieved satisfactory results as the majority of sub-networks achieved AUROC values above 0.5. Copyright © 2015 Elsevier Ltd. All rights reserved.

Reprogramming cell fate with a genome-scale library of artificial transcription factors.

PubMed

Eguchi, Asuka; Wleklinski, Matthew J; Spurgat, Mackenzie C; Heiderscheit, Evan A; Kropornicka, Anna S; Vu, Catherine K; Bhimsaria, Devesh; Swanson, Scott A; Stewart, Ron; Ramanathan, Parameswaran; Kamp, Timothy J; Slukvin, Igor; Thomson, James A; Dutton, James R; Ansari, Aseem Z

2016-12-20

Artificial transcription factors (ATFs) are precision-tailored molecules designed to bind DNA and regulate transcription in a preprogrammed manner. Libraries of ATFs enable the high-throughput screening of gene networks that trigger cell fate decisions or phenotypic changes. We developed a genome-scale library of ATFs that display an engineered interaction domain (ID) to enable cooperative assembly and synergistic gene expression at targeted sites. We used this ATF library to screen for key regulators of the pluripotency network and discovered three combinations of ATFs capable of inducing pluripotency without exogenous expression of Oct4 (POU domain, class 5, TF 1). Cognate site identification, global transcriptional profiling, and identification of ATF binding sites reveal that the ATFs do not directly target Oct4; instead, they target distinct nodes that converge to stimulate the endogenous pluripotency network. This forward genetic approach enables cell type conversions without a priori knowledge of potential key regulators and reveals unanticipated gene network dynamics that drive cell fate choices.

A protein phosphatase network controls the temporal and spatial dynamics of differentiation commitment in human epidermis

PubMed Central

Walko, Gernot; Viswanathan, Priyalakshmi; Tihy, Matthieu; Nijjher, Jagdeesh; Dunn, Sara-Jane; Lamond, Angus I

2017-01-01

Epidermal homeostasis depends on a balance between stem cell renewal and terminal differentiation. The transition between the two cell states, termed commitment, is poorly understood. Here, we characterise commitment by integrating transcriptomic and proteomic data from disaggregated primary human keratinocytes held in suspension to induce differentiation. Cell detachment induces several protein phosphatases, five of which - DUSP6, PPTC7, PTPN1, PTPN13 and PPP3CA – promote differentiation by negatively regulating ERK MAPK and positively regulating AP1 transcription factors. Conversely, DUSP10 expression antagonises commitment. The phosphatases form a dynamic network of transient positive and negative interactions that change over time, with DUSP6 predominating at commitment. Boolean network modelling identifies a mandatory switch between two stable states (stem and differentiated) via an unstable (committed) state. Phosphatase expression is also spatially regulated in vivo and in vitro. We conclude that an auto-regulatory phosphatase network maintains epidermal homeostasis by controlling the onset and duration of commitment. PMID:29043977

Reprogramming cell fate with a genome-scale library of artificial transcription factors

PubMed Central

Eguchi, Asuka; Wleklinski, Matthew J.; Spurgat, Mackenzie C.; Heiderscheit, Evan A.; Kropornicka, Anna S.; Vu, Catherine K.; Bhimsaria, Devesh; Swanson, Scott A.; Stewart, Ron; Ramanathan, Parameswaran; Kamp, Timothy J.; Slukvin, Igor; Thomson, James A.; Dutton, James R.; Ansari, Aseem Z.

2016-01-01

Artificial transcription factors (ATFs) are precision-tailored molecules designed to bind DNA and regulate transcription in a preprogrammed manner. Libraries of ATFs enable the high-throughput screening of gene networks that trigger cell fate decisions or phenotypic changes. We developed a genome-scale library of ATFs that display an engineered interaction domain (ID) to enable cooperative assembly and synergistic gene expression at targeted sites. We used this ATF library to screen for key regulators of the pluripotency network and discovered three combinations of ATFs capable of inducing pluripotency without exogenous expression of Oct4 (POU domain, class 5, TF 1). Cognate site identification, global transcriptional profiling, and identification of ATF binding sites reveal that the ATFs do not directly target Oct4; instead, they target distinct nodes that converge to stimulate the endogenous pluripotency network. This forward genetic approach enables cell type conversions without a priori knowledge of potential key regulators and reveals unanticipated gene network dynamics that drive cell fate choices. PMID:27930301

Integrated cellular network of transcription regulations and protein-protein interactions

PubMed Central

2010-01-01

Background With the accumulation of increasing omics data, a key goal of systems biology is to construct networks at different cellular levels to investigate cellular machinery of the cell. However, there is currently no satisfactory method to construct an integrated cellular network that combines the gene regulatory network and the signaling regulatory pathway. Results In this study, we integrated different kinds of omics data and developed a systematic method to construct the integrated cellular network based on coupling dynamic models and statistical assessments. The proposed method was applied to S. cerevisiae stress responses, elucidating the stress response mechanism of the yeast. From the resulting integrated cellular network under hyperosmotic stress, the highly connected hubs which are functionally relevant to the stress response were identified. Beyond hyperosmotic stress, the integrated network under heat shock and oxidative stress were also constructed and the crosstalks of these networks were analyzed, specifying the significance of some transcription factors to serve as the decision-making devices at the center of the bow-tie structure and the crucial role for rapid adaptation scheme to respond to stress. In addition, the predictive power of the proposed method was also demonstrated. Conclusions We successfully construct the integrated cellular network which is validated by literature evidences. The integration of transcription regulations and protein-protein interactions gives more insight into the actual biological network and is more predictive than those without integration. The method is shown to be powerful and flexible and can be used under different conditions and for different species. The coupling dynamic models of the whole integrated cellular network are very useful for theoretical analyses and for further experiments in the fields of network biology and synthetic biology. PMID:20211003

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

PubMed

Wang, Yu-Chao; Chen, Bor-Sen

2010-03-08

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

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

PubMed

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

2017-01-01

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

Signaling Networks among Stem Cell Precursors, Transit-Amplifying Progenitors, and their Niche in Developing Hair Follicles.

PubMed

Rezza, Amélie; Wang, Zichen; Sennett, Rachel; Qiao, Wenlian; Wang, Dongmei; Heitman, Nicholas; Mok, Ka Wai; Clavel, Carlos; Yi, Rui; Zandstra, Peter; Ma'ayan, Avi; Rendl, Michael

2016-03-29

The hair follicle (HF) is a complex miniorgan that serves as an ideal model system to study stem cell (SC) interactions with the niche during growth and regeneration. Dermal papilla (DP) cells are required for SC activation during the adult hair cycle, but signal exchange between niche and SC precursors/transit-amplifying cell (TAC) progenitors that regulates HF morphogenetic growth is largely unknown. Here we use six transgenic reporters to isolate 14 major skin and HF cell populations. With next-generation RNA sequencing, we characterize their transcriptomes and define unique molecular signatures. SC precursors, TACs, and the DP niche express a plethora of ligands and receptors. Signaling interaction network analysis reveals a bird's-eye view of pathways implicated in epithelial-mesenchymal interactions. Using a systematic tissue-wide approach, this work provides a comprehensive platform, linked to an interactive online database, to identify and further explore the SC/TAC/niche crosstalk regulating HF growth. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Dancing through Life: Molecular Dynamics Simulations and Network-Centric Modeling of Allosteric Mechanisms in Hsp70 and Hsp110 Chaperone Proteins.

PubMed

Stetz, Gabrielle; Verkhivker, Gennady M

2015-01-01

Hsp70 and Hsp110 chaperones play an important role in regulating cellular processes that involve protein folding and stabilization, which are essential for the integrity of signaling networks. Although many aspects of allosteric regulatory mechanisms in Hsp70 and Hsp110 chaperones have been extensively studied and significantly advanced in recent experimental studies, the atomistic picture of signal propagation and energetics of dynamics-based communication still remain unresolved. In this work, we have combined molecular dynamics simulations and protein stability analysis of the chaperone structures with the network modeling of residue interaction networks to characterize molecular determinants of allosteric mechanisms. We have shown that allosteric mechanisms of Hsp70 and Hsp110 chaperones may be primarily determined by nucleotide-induced redistribution of local conformational ensembles in the inter-domain regions and the substrate binding domain. Conformational dynamics and energetics of the peptide substrate binding with the Hsp70 structures has been analyzed using free energy calculations, revealing allosteric hotspots that control negative cooperativity between regulatory sites. The results have indicated that cooperative interactions may promote a population-shift mechanism in Hsp70, in which functional residues are organized in a broad and robust allosteric network that can link the nucleotide-binding site and the substrate-binding regions. A smaller allosteric network in Hsp110 structures may elicit an entropy-driven allostery that occurs in the absence of global structural changes. We have found that global mediating residues with high network centrality may be organized in stable local communities that are indispensable for structural stability and efficient allosteric communications. The network-centric analysis of allosteric interactions has also established that centrality of functional residues could correlate with their sensitivity to mutations across diverse chaperone functions. This study reconciles a wide spectrum of structural and functional experiments by demonstrating how integration of molecular simulations and network-centric modeling may explain thermodynamic and mechanistic aspects of allosteric regulation in chaperones.

Dancing through Life: Molecular Dynamics Simulations and Network-Centric Modeling of Allosteric Mechanisms in Hsp70 and Hsp110 Chaperone Proteins

PubMed Central

Stetz, Gabrielle; Verkhivker, Gennady M.

2015-01-01

Hsp70 and Hsp110 chaperones play an important role in regulating cellular processes that involve protein folding and stabilization, which are essential for the integrity of signaling networks. Although many aspects of allosteric regulatory mechanisms in Hsp70 and Hsp110 chaperones have been extensively studied and significantly advanced in recent experimental studies, the atomistic picture of signal propagation and energetics of dynamics-based communication still remain unresolved. In this work, we have combined molecular dynamics simulations and protein stability analysis of the chaperone structures with the network modeling of residue interaction networks to characterize molecular determinants of allosteric mechanisms. We have shown that allosteric mechanisms of Hsp70 and Hsp110 chaperones may be primarily determined by nucleotide-induced redistribution of local conformational ensembles in the inter-domain regions and the substrate binding domain. Conformational dynamics and energetics of the peptide substrate binding with the Hsp70 structures has been analyzed using free energy calculations, revealing allosteric hotspots that control negative cooperativity between regulatory sites. The results have indicated that cooperative interactions may promote a population-shift mechanism in Hsp70, in which functional residues are organized in a broad and robust allosteric network that can link the nucleotide-binding site and the substrate-binding regions. A smaller allosteric network in Hsp110 structures may elicit an entropy-driven allostery that occurs in the absence of global structural changes. We have found that global mediating residues with high network centrality may be organized in stable local communities that are indispensable for structural stability and efficient allosteric communications. The network-centric analysis of allosteric interactions has also established that centrality of functional residues could correlate with their sensitivity to mutations across diverse chaperone functions. This study reconciles a wide spectrum of structural and functional experiments by demonstrating how integration of molecular simulations and network-centric modeling may explain thermodynamic and mechanistic aspects of allosteric regulation in chaperones. PMID:26619280

Bridging the gap between modules in isolation and as part of networks: A systems framework for elucidating interaction and regulation of signalling modules

NASA Astrophysics Data System (ADS)

Menon, Govind; Krishnan, J.

2016-07-01

While signalling and biochemical modules have been the focus of numerous studies, they are typically studied in isolation, with no examination of the effects of the ambient network. In this paper we formulate and develop a systems framework, rooted in dynamical systems, to understand such effects, by studying the interaction of signalling modules. The modules we consider are (i) basic covalent modification, (ii) monostable switches, (iii) bistable switches, (iv) adaptive modules, and (v) oscillatory modules. We systematically examine the interaction of these modules by analyzing (a) sequential interaction without shared components, (b) sequential interaction with shared components, and (c) oblique interactions. Our studies reveal that the behaviour of a module in isolation may be substantially different from that in a network, and explicitly demonstrate how the behaviour of a given module, the characteristics of the ambient network, and the possibility of shared components can result in new effects. Our global approach illuminates different aspects of the structure and functioning of modules, revealing the importance of dynamical characteristics as well as biochemical features; this provides a methodological platform for investigating the complexity of natural modules shaped by evolution, elucidating the effects of ambient networks on a module in multiple cellular contexts, and highlighting the capabilities and constraints for engineering robust synthetic modules. Overall, such a systems framework provides a platform for bridging the gap between non-linear information processing modules, in isolation and as parts of networks, and a basis for understanding new aspects of natural and engineered cellular networks.

Bridging the gap between modules in isolation and as part of networks: A systems framework for elucidating interaction and regulation of signalling modules.

PubMed

Menon, Govind; Krishnan, J

2016-07-21

While signalling and biochemical modules have been the focus of numerous studies, they are typically studied in isolation, with no examination of the effects of the ambient network. In this paper we formulate and develop a systems framework, rooted in dynamical systems, to understand such effects, by studying the interaction of signalling modules. The modules we consider are (i) basic covalent modification, (ii) monostable switches, (iii) bistable switches, (iv) adaptive modules, and (v) oscillatory modules. We systematically examine the interaction of these modules by analyzing (a) sequential interaction without shared components, (b) sequential interaction with shared components, and (c) oblique interactions. Our studies reveal that the behaviour of a module in isolation may be substantially different from that in a network, and explicitly demonstrate how the behaviour of a given module, the characteristics of the ambient network, and the possibility of shared components can result in new effects. Our global approach illuminates different aspects of the structure and functioning of modules, revealing the importance of dynamical characteristics as well as biochemical features; this provides a methodological platform for investigating the complexity of natural modules shaped by evolution, elucidating the effects of ambient networks on a module in multiple cellular contexts, and highlighting the capabilities and constraints for engineering robust synthetic modules. Overall, such a systems framework provides a platform for bridging the gap between non-linear information processing modules, in isolation and as parts of networks, and a basis for understanding new aspects of natural and engineered cellular networks.

System analysis identifies distinct and common functional networks governed by transcription factor ASCL1, in glioma and small cell lung cancer.

PubMed

Donakonda, Sainitin; Sinha, Swati; Dighe, Shrinivas Nivrutti; Rao, Manchanahalli R Satyanarayana

2017-07-25

ASCL1 is a basic Helix-Loop-Helix transcription factor (TF), which is involved in various cellular processes like neuronal development and signaling pathways. Transcriptome profiling has shown that ASCL1 overexpression plays an important role in the development of glioma and Small Cell Lung Carcinoma (SCLC), but distinct and common molecular mechanisms regulated by ASCL1 in these cancers are unknown. In order to understand how it drives the cellular functional network in these two tumors, we generated a gene expression profile in a glioma cell line (U87MG) to identify ASCL1 gene targets by an si RNA silencing approach and then compared this with a publicly available dataset of similarly silenced SCLC (NCI-H1618 cells). We constructed TF-TF and gene-gene interactions, as well as protein interaction networks of ASCL1 regulated genes in glioma and SCLC cells. Detailed network analysis uncovered various biological processes governed by ASCL1 target genes in these two tumor cell lines. We find that novel ASCL1 functions related to mitosis and signaling pathways influencing development and tumor growth are affected in both glioma and SCLC cells. In addition, we also observed ASCL1 governed functional networks that are distinct to glioma and SCLC.

Insights into significant pathways and gene interaction networks underlying breast cancer cell line MCF-7 treated with 17β-estradiol (E2).

PubMed

Huan, Jinliang; Wang, Lishan; Xing, Li; Qin, Xianju; Feng, Lingbin; Pan, Xiaofeng; Zhu, Ling

2014-01-01

Estrogens are known to regulate the proliferation of breast cancer cells and to alter their cytoarchitectural and phenotypic properties, but the gene networks and pathways by which estrogenic hormones regulate these events are only partially understood. We used global gene expression profiling by Affymetrix GeneChip microarray analysis, with KEGG pathway enrichment, PPI network construction, module analysis and text mining methods to identify patterns and time courses of genes that are either stimulated or inhibited by estradiol (E2) in estrogen receptor (ER)-positive MCF-7 human breast cancer cells. Of the genes queried on the Affymetrix Human Genome U133 plus 2.0 microarray, we identified 628 (12h), 852 (24h) and 880 (48 h) differentially expressed genes (DEGs) that showed a robust pattern of regulation by E2. From pathway enrichment analysis, we found out the changes of metabolic pathways of E2 treated samples at each time point. At 12h time point, the changes of metabolic pathways were mainly focused on pathways in cancer, focal adhesion, and chemokine signaling pathway. At 24h time point, the changes were mainly enriched in neuroactive ligand-receptor interaction, cytokine-cytokine receptor interaction and calcium signaling pathway. At 48 h time point, the significant pathways were pathways in cancer, regulation of actin cytoskeleton, cell adhesion molecules (CAMs), axon guidance and ErbB signaling pathway. Of interest, our PPI network analysis and module analysis found that E2 treatment induced enhancement of PRSS23 at the three time points and PRSS23 was in the central position of each module. Text mining results showed that the important genes of DEGs have relationship with signal pathways, such as ERbB pathway (AREG), Wnt pathway (NDP), MAPK pathway (NTRK3, TH), IP3 pathway (TRA@) and some transcript factors (TCF4, MAF). Our studies highlight the diverse gene networks and metabolic and cell regulatory pathways through which E2 operates to achieve its widespread effects on breast cancer cells. © 2013 Elsevier B.V. All rights reserved.

Semantic integration of data on transcriptional regulation

PubMed Central

Baitaluk, Michael; Ponomarenko, Julia

2010-01-01

Motivation: Experimental and predicted data concerning gene transcriptional regulation are distributed among many heterogeneous sources. However, there are no resources to integrate these data automatically or to provide a ‘one-stop shop’ experience for users seeking information essential for deciphering and modeling gene regulatory networks. Results: IntegromeDB, a semantic graph-based ‘deep-web’ data integration system that automatically captures, integrates and manages publicly available data concerning transcriptional regulation, as well as other relevant biological information, is proposed in this article. The problems associated with data integration are addressed by ontology-driven data mapping, multiple data annotation and heterogeneous data querying, also enabling integration of the user's data. IntegromeDB integrates over 100 experimental and computational data sources relating to genomics, transcriptomics, genetics, and functional and interaction data concerning gene transcriptional regulation in eukaryotes and prokaryotes. Availability: IntegromeDB is accessible through the integrated research environment BiologicalNetworks at http://www.BiologicalNetworks.org Contact: baitaluk@sdsc.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:20427517

Semantic integration of data on transcriptional regulation.

PubMed

Baitaluk, Michael; Ponomarenko, Julia

2010-07-01

Experimental and predicted data concerning gene transcriptional regulation are distributed among many heterogeneous sources. However, there are no resources to integrate these data automatically or to provide a 'one-stop shop' experience for users seeking information essential for deciphering and modeling gene regulatory networks. IntegromeDB, a semantic graph-based 'deep-web' data integration system that automatically captures, integrates and manages publicly available data concerning transcriptional regulation, as well as other relevant biological information, is proposed in this article. The problems associated with data integration are addressed by ontology-driven data mapping, multiple data annotation and heterogeneous data querying, also enabling integration of the user's data. IntegromeDB integrates over 100 experimental and computational data sources relating to genomics, transcriptomics, genetics, and functional and interaction data concerning gene transcriptional regulation in eukaryotes and prokaryotes. IntegromeDB is accessible through the integrated research environment BiologicalNetworks at http://www.BiologicalNetworks.org baitaluk@sdsc.edu Supplementary data are available at Bioinformatics online.

Graphs for information security control in software defined networks

NASA Astrophysics Data System (ADS)

Grusho, Alexander A.; Abaev, Pavel O.; Shorgin, Sergey Ya.; Timonina, Elena E.

2017-07-01

Information security control in software defined networks (SDN) is connected with execution of the security policy rules regulating information accesses and protection against distribution of the malicious code and harmful influences. The paper offers a representation of a security policy in the form of hierarchical structure which in case of distribution of resources for the solution of tasks defines graphs of admissible interactions in a networks. These graphs define commutation tables of switches via the SDN controller.

Mapping transcription factor interactome networks using HaloTag protein arrays.

PubMed

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

2016-07-19

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

CoryneRegNet 3.0--an interactive systems biology platform for the analysis of gene regulatory networks in corynebacteria and Escherichia coli.

PubMed

Baumbach, Jan; Wittkop, Tobias; Rademacher, Katrin; Rahmann, Sven; Brinkrolf, Karina; Tauch, Andreas

2007-04-30

CoryneRegNet is an ontology-based data warehouse for the reconstruction and visualization of transcriptional regulatory interactions in prokaryotes. To extend the biological content of CoryneRegNet, we added comprehensive data on transcriptional regulations in the model organism Escherichia coli K-12, originally deposited in the international reference database RegulonDB. The enhanced web interface of CoryneRegNet offers several types of search options. The results of a search are displayed in a table-based style and include a visualization of the genetic organization of the respective gene region. Information on DNA binding sites of transcriptional regulators is depicted by sequence logos. The results can also be displayed by several layouters implemented in the graphical user interface GraphVis, allowing, for instance, the visualization of genome-wide network reconstructions and the homology-based inter-species comparison of reconstructed gene regulatory networks. In an application example, we compare the composition of the gene regulatory networks involved in the SOS response of E. coli and Corynebacterium glutamicum. CoryneRegNet is available at the following URL: http://www.cebitec.uni-bielefeld.de/groups/gi/software/coryneregnet/.

MiR-155-regulated molecular network orchestrates cell fate in the innate and adaptive immune response to Mycobacterium tuberculosis.

PubMed

Rothchild, Alissa C; Sissons, James R; Shafiani, Shahin; Plaisier, Christopher; Min, Deborah; Mai, Dat; Gilchrist, Mark; Peschon, Jacques; Larson, Ryan P; Bergthaler, Andreas; Baliga, Nitin S; Urdahl, Kevin B; Aderem, Alan

2016-10-11

The regulation of host-pathogen interactions during Mycobacterium tuberculosis (Mtb) infection remains unresolved. MicroRNAs (miRNAs) are important regulators of the immune system, and so we used a systems biology approach to construct an miRNA regulatory network activated in macrophages during Mtb infection. Our network comprises 77 putative miRNAs that are associated with temporal gene expression signatures in macrophages early after Mtb infection. In this study, we demonstrate a dual role for one of these regulators, miR-155. On the one hand, miR-155 maintains the survival of Mtb-infected macrophages, thereby providing a niche favoring bacterial replication; on the other hand, miR-155 promotes the survival and function of Mtb-specific T cells, enabling an effective adaptive immune response. MiR-155-induced cell survival is mediated through the SH2 domain-containing inositol 5-phosphatase 1 (SHIP1)/protein kinase B (Akt) pathway. Thus, dual regulation of the same cell survival pathway in innate and adaptive immune cells leads to vastly different outcomes with respect to bacterial containment.

Emotion regulation, attention to emotion, and the ventral attentional network

PubMed Central

Viviani, Roberto

2013-01-01

Accounts of the effect of emotional information on behavioral response and current models of emotion regulation are based on two opposed but interacting processes: automatic bottom-up processes (triggered by emotionally arousing stimuli) and top-down control processes (mapped to prefrontal cortical areas). Data on the existence of a third attentional network operating without recourse to limited-capacity processes but influencing response raise the issue of how it is integrated in emotion regulation. We summarize here data from attention to emotion, voluntary emotion regulation, and on the origin of biases against negative content suggesting that the ventral network is modulated by exposure to emotional stimuli when the task does not constrain the handling of emotional content. In the parietal lobes, preferential activation of ventral areas associated with “bottom-up” attention by ventral network theorists is strongest in studies of cognitive reappraisal. In conditions when no explicit instruction is given to change one's response to emotional stimuli, control of emotionally arousing stimuli is observed without concomitant activation of the dorsal attentional network, replaced by a shift of activation toward ventral areas. In contrast, in studies where emotional stimuli are placed in the role of distracter, the observed deactivation of these ventral semantic association areas is consistent with the existence of proactive control on the role emotional representations are allowed to take in generating response. It is here argued that attentional orienting mechanisms located in the ventral network constitute an intermediate kind of process, with features only partially in common with effortful and automatic processes, which plays an important role in handling emotion by conveying the influence of semantic networks, with which the ventral network is co-localized. Current neuroimaging work in emotion regulation has neglected this system by focusing on a bottom-up/top-down dichotomy of attentional control. PMID:24223546

Intranasal oxytocin modulates neural functional connectivity during human social interaction.

PubMed

Rilling, James K; Chen, Xiangchuan; Chen, Xu; Haroon, Ebrahim

2018-02-10

Oxytocin (OT) modulates social behavior in primates and many other vertebrate species. Studies in non-primate animals have demonstrated that, in addition to influencing activity within individual brain areas, OT influences functional connectivity across networks of areas involved in social behavior. Previously, we used fMRI to image brain function in human subjects during a dyadic social interaction task following administration of either intranasal oxytocin (INOT) or placebo, and analyzed the data with a standard general linear model. Here, we conduct an extensive re-analysis of these data to explore how OT modulates functional connectivity across a neural network that animal studies implicate in social behavior. OT induced widespread increases in functional connectivity in response to positive social interactions among men and widespread decreases in functional connectivity in response to negative social interactions among women. Nucleus basalis of Meynert, an important regulator of selective attention and motivation with a particularly high density of OT receptors, had the largest number of OT-modulated connections. Regions known to receive mesolimbic dopamine projections such as the nucleus accumbens and lateral septum were also hubs for OT effects on functional connectivity. Our results suggest that the neural mechanism by which OT influences primate social cognition may include changes in patterns of activity across neural networks that regulate social behavior in other animals. © 2018 Wiley Periodicals, Inc.

Using Networks To Understand Medical Data: The Case of Class III Malocclusions

PubMed Central

Scala, Antonio; Auconi, Pietro; Scazzocchio, Marco; Caldarelli, Guido; McNamara, James A.; Franchi, Lorenzo

2012-01-01

A system of elements that interact or regulate each other can be represented by a mathematical object called a network. While network analysis has been successfully applied to high-throughput biological systems, less has been done regarding their application in more applied fields of medicine; here we show an application based on standard medical diagnostic data. We apply network analysis to Class III malocclusion, one of the most difficult to understand and treat orofacial anomaly. We hypothesize that different interactions of the skeletal components can contribute to pathological disequilibrium; in order to test this hypothesis, we apply network analysis to 532 Class III young female patients. The topology of the Class III malocclusion obtained by network analysis shows a strong co-occurrence of abnormal skeletal features. The pattern of these occurrences influences the vertical and horizontal balance of disharmony in skeletal form and position. Patients with more unbalanced orthodontic phenotypes show preponderance of the pathological skeletal nodes and minor relevance of adaptive dentoalveolar equilibrating nodes. Furthermore, by applying Power Graphs analysis we identify some functional modules among orthodontic nodes. These modules correspond to groups of tightly inter-related features and presumably constitute the key regulators of plasticity and the sites of unbalance of the growing dentofacial Class III system. The data of the present study show that, in their most basic abstraction level, the orofacial characteristics can be represented as graphs using nodes to represent orthodontic characteristics, and edges to represent their various types of interactions. The applications of this mathematical model could improve the interpretation of the quantitative, patient-specific information, and help to better targeting therapy. Last but not least, the methodology we have applied in analyzing orthodontic features can be applied easily to other fields of the medical science. PMID:23028552

Intrinsic limits to gene regulation by global crosstalk

PubMed Central

Friedlander, Tamar; Prizak, Roshan; Guet, Călin C.; Barton, Nicholas H.; Tkačik, Gašper

2016-01-01

Gene regulation relies on the specificity of transcription factor (TF)–DNA interactions. Limited specificity may lead to crosstalk: a regulatory state in which a gene is either incorrectly activated due to noncognate TF–DNA interactions or remains erroneously inactive. As each TF can have numerous interactions with noncognate cis-regulatory elements, crosstalk is inherently a global problem, yet has previously not been studied as such. We construct a theoretical framework to analyse the effects of global crosstalk on gene regulation. We find that crosstalk presents a significant challenge for organisms with low-specificity TFs, such as metazoans. Crosstalk is not easily mitigated by known regulatory schemes acting at equilibrium, including variants of cooperativity and combinatorial regulation. Our results suggest that crosstalk imposes a previously unexplored global constraint on the functioning and evolution of regulatory networks, which is qualitatively distinct from the known constraints that act at the level of individual gene regulatory elements. PMID:27489144

Inference of time-delayed gene regulatory networks based on dynamic Bayesian network hybrid learning method

PubMed Central

Yu, Bin; Xu, Jia-Meng; Li, Shan; Chen, Cheng; Chen, Rui-Xin; Wang, Lei; Zhang, Yan; Wang, Ming-Hui

2017-01-01

Gene regulatory networks (GRNs) research reveals complex life phenomena from the perspective of gene interaction, which is an important research field in systems biology. Traditional Bayesian networks have a high computational complexity, and the network structure scoring model has a single feature. Information-based approaches cannot identify the direction of regulation. In order to make up for the shortcomings of the above methods, this paper presents a novel hybrid learning method (DBNCS) based on dynamic Bayesian network (DBN) to construct the multiple time-delayed GRNs for the first time, combining the comprehensive score (CS) with the DBN model. DBNCS algorithm first uses CMI2NI (conditional mutual inclusive information-based network inference) algorithm for network structure profiles learning, namely the construction of search space. Then the redundant regulations are removed by using the recursive optimization algorithm (RO), thereby reduce the false positive rate. Secondly, the network structure profiles are decomposed into a set of cliques without loss, which can significantly reduce the computational complexity. Finally, DBN model is used to identify the direction of gene regulation within the cliques and search for the optimal network structure. The performance of DBNCS algorithm is evaluated by the benchmark GRN datasets from DREAM challenge as well as the SOS DNA repair network in Escherichia coli, and compared with other state-of-the-art methods. The experimental results show the rationality of the algorithm design and the outstanding performance of the GRNs. PMID:29113310

Inference of time-delayed gene regulatory networks based on dynamic Bayesian network hybrid learning method.

PubMed

Yu, Bin; Xu, Jia-Meng; Li, Shan; Chen, Cheng; Chen, Rui-Xin; Wang, Lei; Zhang, Yan; Wang, Ming-Hui

2017-10-06

Gene regulatory networks (GRNs) research reveals complex life phenomena from the perspective of gene interaction, which is an important research field in systems biology. Traditional Bayesian networks have a high computational complexity, and the network structure scoring model has a single feature. Information-based approaches cannot identify the direction of regulation. In order to make up for the shortcomings of the above methods, this paper presents a novel hybrid learning method (DBNCS) based on dynamic Bayesian network (DBN) to construct the multiple time-delayed GRNs for the first time, combining the comprehensive score (CS) with the DBN model. DBNCS algorithm first uses CMI2NI (conditional mutual inclusive information-based network inference) algorithm for network structure profiles learning, namely the construction of search space. Then the redundant regulations are removed by using the recursive optimization algorithm (RO), thereby reduce the false positive rate. Secondly, the network structure profiles are decomposed into a set of cliques without loss, which can significantly reduce the computational complexity. Finally, DBN model is used to identify the direction of gene regulation within the cliques and search for the optimal network structure. The performance of DBNCS algorithm is evaluated by the benchmark GRN datasets from DREAM challenge as well as the SOS DNA repair network in Escherichia coli , and compared with other state-of-the-art methods. The experimental results show the rationality of the algorithm design and the outstanding performance of the GRNs.

Coherent organization in gene regulation: a study on six networks

NASA Astrophysics Data System (ADS)

Aral, Neşe; Kabakçıoğlu, Alkan

2016-04-01

Structural and dynamical fingerprints of evolutionary optimization in biological networks are still unclear. Here we analyze the dynamics of genetic regulatory networks responsible for the regulation of cell cycle and cell differentiation in three organisms or cell types each, and show that they follow a version of Hebb's rule which we have termed coherence. More precisely, we find that simultaneously expressed genes with a common target are less likely to act antagonistically at the attractors of the regulatory dynamics. We then investigate the dependence of coherence on structural parameters, such as the mean number of inputs per node and the activatory/repressory interaction ratio, as well as on dynamically determined quantities, such as the basin size and the number of expressed genes.

The autophagy interaction network of the aging model Podospora anserina.

PubMed

Philipp, Oliver; Hamann, Andrea; Osiewacz, Heinz D; Koch, Ina

2017-03-27

Autophagy is a conserved molecular pathway involved in the degradation and recycling of cellular components. It is active either as response to starvation or molecular damage. Evidence is emerging that autophagy plays a key role in the degradation of damaged cellular components and thereby affects aging and lifespan control. In earlier studies, it was found that autophagy in the aging model Podospora anserina acts as a longevity assurance mechanism. However, only little is known about the individual components controlling autophagy in this aging model. Here, we report a biochemical and bioinformatics study to detect the protein-protein interaction (PPI) network of P. anserina combining experimental and theoretical methods. We constructed the PPI network of autophagy in P. anserina based on the corresponding networks of yeast and human. We integrated PaATG8 interaction partners identified in an own yeast two-hybrid analysis using ATG8 of P. anserina as bait. Additionally, we included age-dependent transcriptome data. The resulting network consists of 89 proteins involved in 186 interactions. We applied bioinformatics approaches to analyze the network topology and to prove that the network is not random, but exhibits biologically meaningful properties. We identified hub proteins which play an essential role in the network as well as seven putative sub-pathways, and interactions which are likely to be evolutionary conserved amongst species. We confirmed that autophagy-associated genes are significantly often up-regulated and co-expressed during aging of P. anserina. With the present study, we provide a comprehensive biological network of the autophagy pathway in P. anserina comprising PPI and gene expression data. It is based on computational prediction as well as experimental data. We identified sub-pathways, important hub proteins, and evolutionary conserved interactions. The network clearly illustrates the relation of autophagy to aging processes and enables further specific studies to understand autophagy and aging in P. anserina as well as in other systems.

Abasy Atlas: a comprehensive inventory of systems, global network properties and systems-level elements across bacteria

PubMed Central

Ibarra-Arellano, Miguel A.; Campos-González, Adrián I.; Treviño-Quintanilla, Luis G.; Tauch, Andreas; Freyre-González, Julio A.

2016-01-01

The availability of databases electronically encoding curated regulatory networks and of high-throughput technologies and methods to discover regulatory interactions provides an invaluable source of data to understand the principles underpinning the organization and evolution of these networks responsible for cellular regulation. Nevertheless, data on these sources never goes beyond the regulon level despite the fact that regulatory networks are complex hierarchical-modular structures still challenging our understanding. This brings the necessity for an inventory of systems across a large range of organisms, a key step to rendering feasible comparative systems biology approaches. In this work, we take the first step towards a global understanding of the regulatory networks organization by making a cartography of the functional architectures of diverse bacteria. Abasy (Across-bacteria systems) Atlas provides a comprehensive inventory of annotated functional systems, global network properties and systems-level elements (global regulators, modular genes shaping functional systems, basal machinery genes and intermodular genes) predicted by the natural decomposition approach for reconstructed and meta-curated regulatory networks across a large range of bacteria, including pathogenically and biotechnologically relevant organisms. The meta-curation of regulatory datasets provides the most complete and reliable set of regulatory interactions currently available, which can even be projected into subsets by considering the force or weight of evidence supporting them or the systems that they belong to. Besides, Abasy Atlas provides data enabling large-scale comparative systems biology studies aimed at understanding the common principles and particular lifestyle adaptions of systems across bacteria. Abasy Atlas contains systems and system-level elements for 50 regulatory networks comprising 78 649 regulatory interactions covering 42 bacteria in nine taxa, containing 3708 regulons and 1776 systems. All this brings together a large corpus of data that will surely inspire studies to generate hypothesis regarding the principles governing the evolution and organization of systems and the functional architectures controlling them. Database URL: http://abasy.ccg.unam.mx PMID:27242034

From Genes to Networks: Characterizing Gene-Regulatory Interactions in Plants.

PubMed

Kaufmann, Kerstin; Chen, Dijun

2017-01-01

Plants, like other eukaryotes, have evolved complex mechanisms to coordinate gene expression during development, environmental response, and cellular homeostasis. Transcription factors (TFs), accompanied by basic cofactors and posttranscriptional regulators, are key players in gene-regulatory networks (GRNs). The coordinated control of gene activity is achieved by the interplay of these factors and by physical interactions between TFs and DNA. Here, we will briefly outline recent technological progress made to elucidate GRNs in plants. We will focus on techniques that allow us to characterize physical interactions in GRNs in plants and to analyze their regulatory consequences. Targeted manipulation allows us to test the relevance of specific gene-regulatory interactions. The combination of genome-wide experimental approaches with mathematical modeling allows us to get deeper insights into key-regulatory interactions and combinatorial control of important processes in plants.

Noncovalent Ubiquitin Interactions Regulate the Catalytic Activity of Ubiquitin Writers.

PubMed

Wright, Joshua D; Mace, Peter D; Day, Catherine L

2016-11-01

Covalent modification of substrate proteins with ubiquitin is the end result of an intricate network of protein-protein interactions. The inherent ability of the E1, E2, and E3 proteins of the ubiquitylation cascade (the ubiquitin writers) to interact with ubiquitin facilitates this process. Importantly, contact between ubiquitin and the E2/E3 writers is required for catalysis and the assembly of chains of a given linkage. However, ubiquitin is also an activator of ubiquitin-writing enzymes, with many recent studies highlighting the ability of ubiquitin to regulate activity and substrate modification. Here, we review the interactions between ubiquitin-writing enzymes and regulatory ubiquitin molecules that promote activity, and highlight the potential of these interactions to promote processive ubiquitin transfer. Copyright © 2016 Elsevier Ltd. All rights reserved.

The effect of individual variation on the structure and function of interaction networks in harvester ants

PubMed Central

Pinter-Wollman, Noa; Wollman, Roy; Guetz, Adam; Holmes, Susan; Gordon, Deborah M.

2011-01-01

Social insects exhibit coordinated behaviour without central control. Local interactions among individuals determine their behaviour and regulate the activity of the colony. Harvester ants are recruited for outside work, using networks of brief antennal contacts, in the nest chamber closest to the nest exit: the entrance chamber. Here, we combine empirical observations, image analysis and computer simulations to investigate the structure and function of the interaction network in the entrance chamber. Ant interactions were distributed heterogeneously in the chamber, with an interaction hot-spot at the entrance leading further into the nest. The distribution of the total interactions per ant followed a right-skewed distribution, indicating the presence of highly connected individuals. Numbers of ant encounters observed positively correlated with the duration of observation. Individuals varied in interaction frequency, even after accounting for the duration of observation. An ant's interaction frequency was explained by its path shape and location within the entrance chamber. Computer simulations demonstrate that variation among individuals in connectivity accelerates information flow to an extent equivalent to an increase in the total number of interactions. Individual variation in connectivity, arising from variation among ants in location and spatial behaviour, creates interaction centres, which may expedite information flow. PMID:21490001

An Arabidopsis Gene Regulatory Network for Secondary Cell Wall Synthesis

PubMed Central

Taylor-Teeples, M; Lin, L; de Lucas, M; Turco, G; Toal, TW; Gaudinier, A; Young, NF; Trabucco, GM; Veling, MT; Lamothe, R; Handakumbura, PP; Xiong, G; Wang, C; Corwin, J; Tsoukalas, A; Zhang, L; Ware, D; Pauly, M; Kliebenstein, DJ; Dehesh, K; Tagkopoulos, I; Breton, G; Pruneda-Paz, JL; Ahnert, SE; Kay, SA; Hazen, SP; Brady, SM

2014-01-01

Summary The plant cell wall is an important factor for determining cell shape, function and response to the environment. Secondary cell walls, such as those found in xylem, are composed of cellulose, hemicelluloses and lignin and account for the bulk of plant biomass. The coordination between transcriptional regulation of synthesis for each polymer is complex and vital to cell function. A regulatory hierarchy of developmental switches has been proposed, although the full complement of regulators remains unknown. Here, we present a protein-DNA network between Arabidopsis transcription factors and secondary cell wall metabolic genes with gene expression regulated by a series of feed-forward loops. This model allowed us to develop and validate new hypotheses about secondary wall gene regulation under abiotic stress. Distinct stresses are able to perturb targeted genes to potentially promote functional adaptation. These interactions will serve as a foundation for understanding the regulation of a complex, integral plant component. PMID:25533953

Social networks help to infer causality in the tumor microenvironment.

PubMed

Crespo, Isaac; Doucey, Marie-Agnès; Xenarios, Ioannis

2016-03-15

Networks have become a popular way to conceptualize a system of interacting elements, such as electronic circuits, social communication, metabolism or gene regulation. Network inference, analysis, and modeling techniques have been developed in different areas of science and technology, such as computer science, mathematics, physics, and biology, with an active interdisciplinary exchange of concepts and approaches. However, some concepts seem to belong to a specific field without a clear transferability to other domains. At the same time, it is increasingly recognized that within some biological systems--such as the tumor microenvironment--where different types of resident and infiltrating cells interact to carry out their functions, the complexity of the system demands a theoretical framework, such as statistical inference, graph analysis and dynamical models, in order to asses and study the information derived from high-throughput experimental technologies. In this article we propose to adopt and adapt the concepts of influence and investment from the world of social network analysis to biological problems, and in particular to apply this approach to infer causality in the tumor microenvironment. We showed that constructing a bidirectional network of influence between cell and cell communication molecules allowed us to determine the direction of inferred regulations at the expression level and correctly recapitulate cause-effect relationships described in literature. This work constitutes an example of a transfer of knowledge and concepts from the world of social network analysis to biomedical research, in particular to infer network causality in biological networks. This causality elucidation is essential to model the homeostatic response of biological systems to internal and external factors, such as environmental conditions, pathogens or treatments.

Modeling gene regulatory network motifs using statecharts

PubMed Central

2012-01-01

Background Gene regulatory networks are widely used by biologists to describe the interactions among genes, proteins and other components at the intra-cellular level. Recently, a great effort has been devoted to give gene regulatory networks a formal semantics based on existing computational frameworks. For this purpose, we consider Statecharts, which are a modular, hierarchical and executable formal model widely used to represent software systems. We use Statecharts for modeling small and recurring patterns of interactions in gene regulatory networks, called motifs. Results We present an improved method for modeling gene regulatory network motifs using Statecharts and we describe the successful modeling of several motifs, including those which could not be modeled or whose models could not be distinguished using the method of a previous proposal. We model motifs in an easy and intuitive way by taking advantage of the visual features of Statecharts. Our modeling approach is able to simulate some interesting temporal properties of gene regulatory network motifs: the delay in the activation and the deactivation of the "output" gene in the coherent type-1 feedforward loop, the pulse in the incoherent type-1 feedforward loop, the bistability nature of double positive and double negative feedback loops, the oscillatory behavior of the negative feedback loop, and the "lock-in" effect of positive autoregulation. Conclusions We present a Statecharts-based approach for the modeling of gene regulatory network motifs in biological systems. The basic motifs used to build more complex networks (that is, simple regulation, reciprocal regulation, feedback loop, feedforward loop, and autoregulation) can be faithfully described and their temporal dynamics can be analyzed. PMID:22536967

Reconstruction and topological characterization of the sigma factor regulatory network of Mycobacterium tuberculosis

PubMed Central

Chauhan, Rinki; Ravi, Janani; Datta, Pratik; Chen, Tianlong; Schnappinger, Dirk; Bassler, Kevin E.; Balázsi, Gábor; Gennaro, Maria Laura

2016-01-01

Accessory sigma factors, which reprogram RNA polymerase to transcribe specific gene sets, activate bacterial adaptive responses to noxious environments. Here we reconstruct the complete sigma factor regulatory network of the human pathogen Mycobacterium tuberculosis by an integrated approach. The approach combines identification of direct regulatory interactions between M. tuberculosis sigma factors in an E. coli model system, validation of selected links in M. tuberculosis, and extensive literature review. The resulting network comprises 41 direct interactions among all 13 sigma factors. Analysis of network topology reveals (i) a three-tiered hierarchy initiating at master regulators, (ii) high connectivity and (iii) distinct communities containing multiple sigma factors. These topological features are likely associated with multi-layer signal processing and specialized stress responses involving multiple sigma factors. Moreover, the identification of overrepresented network motifs, such as autoregulation and coregulation of sigma and anti-sigma factor pairs, provides structural information that is relevant for studies of network dynamics. PMID:27029515

Living in the branches: population dynamics and ecological processes in dendritic networks

USGS Publications Warehouse

Grant, E.H.C.; Lowe, W.H.; Fagan, W.F.

2007-01-01

Spatial structure regulates and modifies processes at several levels of ecological organization (e.g. individual/genetic, population and community) and is thus a key component of complex systems, where knowledge at a small scale can be insufficient for understanding system behaviour at a larger scale. Recent syntheses outline potential applications of network theory to ecological systems, but do not address the implications of physical structure for network dynamics. There is a specific need to examine how dendritic habitat structure, such as that found in stream, hedgerow and cave networks, influences ecological processes. Although dendritic networks are one type of ecological network, they are distinguished by two fundamental characteristics: (1) both the branches and the nodes serve as habitat, and (2) the specific spatial arrangement and hierarchical organization of these elements interacts with a species' movement behaviour to alter patterns of population distribution and abundance, and community interactions. Here, we summarize existing theory relating to ecological dynamics in dendritic networks, review empirical studies examining the population- and community-level consequences of these networks, and suggest future research integrating spatial pattern and processes in dendritic systems.

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

Protein-protein interaction networks: unraveling the wiring of molecular machines within the cell.

PubMed

De Las Rivas, Javier; Fontanillo, Celia

2012-11-01

Mapping and understanding of the protein interaction networks with their key modules and hubs can provide deeper insights into the molecular machinery underlying complex phenotypes. In this article, we present the basic characteristics and definitions of protein networks, starting with a distinction of the different types of associations between proteins. We focus the review on protein-protein interactions (PPIs), a subset of associations defined as physical contacts between proteins that occur by selective molecular docking in a particular biological context. We present such definition as opposed to other types of protein associations derived from regulatory, genetic, structural or functional relations. To determine PPIs, a variety of binary and co-complex methods exist; however, not all the technologies provide the same information and data quality. A way of increasing confidence in a given protein interaction is to integrate orthogonal experimental evidences. The use of several complementary methods testing each single interaction assesses the accuracy of PPI data and tries to minimize the occurrence of false interactions. Following this approach there have been important efforts to unify primary databases of experimentally proven PPIs into integrated databases. These meta-databases provide a measure of the confidence of interactions based on the number of experimental proofs that report them. As a conclusion, we can state that integrated information allows the building of more reliable interaction networks. Identification of communities, cliques, modules and hubs by analysing the topological parameters and graph properties of the protein networks allows the discovery of central/critical nodes, which are candidates to regulate cellular flux and dynamics.

Co-expression network with protein-protein interaction and transcription regulation in malaria parasite Plasmodium falciparum.

PubMed

Yu, Fu-Dong; Yang, Shao-You; Li, Yuan-Yuan; Hu, Wei

2013-04-10

Malaria continues to be one of the most severe global infectious diseases, as a major threat to human health and economic development. Network-based biological analysis is a promising approach to uncover key genes and biological processes from a network viewpoint, which could not be recognized from individual gene-based signatures. We integrated gene co-expression profile with protein-protein interaction and transcriptional regulation information to construct a comprehensive gene co-expression network of Plasmodium falciparum. Based on this network, we identified 10 core modules by using ICE (Iterative Clique Enumeration) algorithm, which were essential for malaria parasite development in intraerythrocytic developmental cycle (IDC) stages. In each module, all genes were highly correlated probably due to co-regulation or formation of a protein complex. Some of these genes were recognized to be differentially coexpressed among three close-by IDC stages. The gene of prpf8 (PFD0265w) encoding pre-mRNA processing splicing factor 8 product was identified as DCGs (differentially co-expressed genes) among IDC stages, although this gene function was seldom reported in previous researches. Integrating the species-specific gene prediction and differential co-expression gene detection, we found some modules could perform species-specific functions according to some of genes in these modules were species-specific genes, like the module 10. Furthermore, in order to reveal the underlying mechanisms of the erythrocyte invasion by P. falciparum, Steiner Tree algorithm was employed to identify the invasion subnetwork from our gene co-expression network. The subnetwork-based analysis indicated that some important Plasmodium parasite specific genes could corporate with each other and be co-regulated during the parasite invasion process, which including a head-to-head gene pair of PfRH2a (PF13_0198) and PfRH2b (MAL13P1.176). This study based on gene co-expression network could shed new insights on the mechanisms of pathogenesis, even virulence and P. falciparum development. Crown Copyright © 2012. Published by Elsevier B.V. All rights reserved.

Model-based design of RNA hybridization networks implemented in living cells.

PubMed

Rodrigo, Guillermo; Prakash, Satya; Shen, Shensi; Majer, Eszter; Daròs, José-Antonio; Jaramillo, Alfonso

2017-09-19

Synthetic gene circuits allow the behavior of living cells to be reprogrammed, and non-coding small RNAs (sRNAs) are increasingly being used as programmable regulators of gene expression. However, sRNAs (natural or synthetic) are generally used to regulate single target genes, while complex dynamic behaviors would require networks of sRNAs regulating each other. Here, we report a strategy for implementing such networks that exploits hybridization reactions carried out exclusively by multifaceted sRNAs that are both targets of and triggers for other sRNAs. These networks are ultimately coupled to the control of gene expression. We relied on a thermodynamic model of the different stable conformational states underlying this system at the nucleotide level. To test our model, we designed five different RNA hybridization networks with a linear architecture, and we implemented them in Escherichia coli. We validated the network architecture at the molecular level by native polyacrylamide gel electrophoresis, as well as the network function at the bacterial population and single-cell levels with a fluorescent reporter. Our results suggest that it is possible to engineer complex cellular programs based on RNA from first principles. Because these networks are mainly based on physical interactions, our designs could be expanded to other organisms as portable regulatory resources or to implement biological computations. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Auxin crosstalk to plant immune networks: a plant-pathogen interaction perspective.

PubMed

Naseem, Muhammad; Srivastava, Mugdha; Tehseen, Muhammad; Ahmed, Nazeer

2015-01-01

The plant hormone auxin regulates a whole repertoire of plant growth and development. Many plant-associated microorganisms, by virtue of their auxin production capability, mediate phytostimulation effects on plants. Recent studies, however, demonstrate diverse mechanisms whereby plant pathogens manipulate auxin biosynthesis, signaling and transport pathways to promote host susceptibility. Auxin responses have been coupled to their antagonistic and synergistic interactions with salicylic acid and jasmonate mediated defenses, respectively. Here, we discuss that a better understanding of auxin crosstalk to plant immune networks would enable us to engineer crop plants with higher protection and low unintended yield losses.

CoryneRegNet: an ontology-based data warehouse of corynebacterial transcription factors and regulatory networks.

PubMed

Baumbach, Jan; Brinkrolf, Karina; Czaja, Lisa F; Rahmann, Sven; Tauch, Andreas

2006-02-14

The application of DNA microarray technology in post-genomic analysis of bacterial genome sequences has allowed the generation of huge amounts of data related to regulatory networks. This data along with literature-derived knowledge on regulation of gene expression has opened the way for genome-wide reconstruction of transcriptional regulatory networks. These large-scale reconstructions can be converted into in silico models of bacterial cells that allow a systematic analysis of network behavior in response to changing environmental conditions. CoryneRegNet was designed to facilitate the genome-wide reconstruction of transcriptional regulatory networks of corynebacteria relevant in biotechnology and human medicine. During the import and integration process of data derived from experimental studies or literature knowledge CoryneRegNet generates links to genome annotations, to identified transcription factors and to the corresponding cis-regulatory elements. CoryneRegNet is based on a multi-layered, hierarchical and modular concept of transcriptional regulation and was implemented by using the relational database management system MySQL and an ontology-based data structure. Reconstructed regulatory networks can be visualized by using the yFiles JAVA graph library. As an application example of CoryneRegNet, we have reconstructed the global transcriptional regulation of a cellular module involved in SOS and stress response of corynebacteria. CoryneRegNet is an ontology-based data warehouse that allows a pertinent data management of regulatory interactions along with the genome-scale reconstruction of transcriptional regulatory networks. These models can further be combined with metabolic networks to build integrated models of cellular function including both metabolism and its transcriptional regulation.

Advantages of mixing bioinformatics and visualization approaches for analyzing sRNA-mediated regulatory bacterial networks

PubMed Central

Bourqui, Romain; Benchimol, William; Gaspin, Christine; Sirand-Pugnet, Pascal; Uricaru, Raluca; Dutour, Isabelle

2015-01-01

The revolution in high-throughput sequencing technologies has enabled the acquisition of gigabytes of RNA sequences in many different conditions and has highlighted an unexpected number of small RNAs (sRNAs) in bacteria. Ongoing exploitation of these data enables numerous applications for investigating bacterial transacting sRNA-mediated regulation networks. Focusing on sRNAs that regulate mRNA translation in trans, recent works have noted several sRNA-based regulatory pathways that are essential for key cellular processes. Although the number of known bacterial sRNAs is increasing, the experimental validation of their interactions with mRNA targets remains challenging and involves expensive and time-consuming experimental strategies. Hence, bioinformatics is crucial for selecting and prioritizing candidates before designing any experimental work. However, current software for target prediction produces a prohibitive number of candidates because of the lack of biological knowledge regarding the rules governing sRNA–mRNA interactions. Therefore, there is a real need to develop new approaches to help biologists focus on the most promising predicted sRNA–mRNA interactions. In this perspective, this review aims at presenting the advantages of mixing bioinformatics and visualization approaches for analyzing predicted sRNA-mediated regulatory bacterial networks. PMID:25477348

Advantages of mixing bioinformatics and visualization approaches for analyzing sRNA-mediated regulatory bacterial networks.

PubMed

Thébault, Patricia; Bourqui, Romain; Benchimol, William; Gaspin, Christine; Sirand-Pugnet, Pascal; Uricaru, Raluca; Dutour, Isabelle

2015-09-01

The revolution in high-throughput sequencing technologies has enabled the acquisition of gigabytes of RNA sequences in many different conditions and has highlighted an unexpected number of small RNAs (sRNAs) in bacteria. Ongoing exploitation of these data enables numerous applications for investigating bacterial transacting sRNA-mediated regulation networks. Focusing on sRNAs that regulate mRNA translation in trans, recent works have noted several sRNA-based regulatory pathways that are essential for key cellular processes. Although the number of known bacterial sRNAs is increasing, the experimental validation of their interactions with mRNA targets remains challenging and involves expensive and time-consuming experimental strategies. Hence, bioinformatics is crucial for selecting and prioritizing candidates before designing any experimental work. However, current software for target prediction produces a prohibitive number of candidates because of the lack of biological knowledge regarding the rules governing sRNA-mRNA interactions. Therefore, there is a real need to develop new approaches to help biologists focus on the most promising predicted sRNA-mRNA interactions. In this perspective, this review aims at presenting the advantages of mixing bioinformatics and visualization approaches for analyzing predicted sRNA-mediated regulatory bacterial networks. © The Author 2014. Published by Oxford University Press.

Network-Based Comparative Analysis of Arabidopsis Immune Responses to Golovinomyces orontii and Botrytis cinerea Infections.

PubMed

Jiang, Zhenhong; Dong, Xiaobao; Zhang, Ziding

2016-01-11

A comprehensive exploration of common and specific plant responses to biotrophs and necrotrophs is necessary for a better understanding of plant immunity. Here, we compared the Arabidopsis defense responses evoked by the biotrophic fungus Golovinomyces orontii and the necrotrophic fungus Botrytis cinerea through integrative network analysis. Two time-course transcriptional datasets were integrated with an Arabidopsis protein-protein interaction (PPI) network to construct a G. orontii conditional PPI sub-network (gCPIN) and a B. cinerea conditional PPI sub-network (bCPIN). We found that hubs in gCPIN and bCPIN played important roles in disease resistance. Hubs in bCPIN evolved faster than hubs in gCPIN, indicating the different selection pressures imposed on plants by different pathogens. By analyzing the common network from gCPIN and bCPIN, we identified two network components in which the genes were heavily involved in defense and development, respectively. The co-expression relationships between interacting proteins connecting the two components were different under G. orontii and B. cinerea infection conditions. Closer inspection revealed that auxin-related genes were overrepresented in the interactions connecting these two components, suggesting a critical role of auxin signaling in regulating the different co-expression relationships. Our work may provide new insights into plant defense responses against pathogens with different lifestyles.

Exploration and Modulation of Brain Network Interactions with Noninvasive Brain Stimulation in Combination with Neuroimaging

PubMed Central

Shafi, Mouhsin M.; Westover, M. Brandon; Fox, Michael D.; Pascual-Leone, Alvaro

2012-01-01

Much recent work in systems neuroscience has focused on how dynamic interactions between different cortical regions underlie complex brain functions such as motor coordination, language, and emotional regulation. Various studies using neuroimaging and neurophysiologic techniques have suggested that in many neuropsychiatric disorders, these dynamic brain networks are dysregulated. Here we review the utility of combined noninvasive brain stimulation and neuroimaging approaches towards greater understanding of dynamic brain networks in health and disease. Brain stimulation techniques, such as transcranial magnetic stimulation and transcranial direct current stimulation, use electromagnetic principles to noninvasively alter brain activity, and induce focal but also network effects beyond the stimulation site. When combined with brain imaging techniques such as functional MRI, PET and EEG, these brain stimulation techniques enable a causal assessment of the interaction between different network components, and their respective functional roles. The same techniques can also be applied to explore hypotheses regarding the changes in functional connectivity that occur during task performance and in various disease states such as stroke, depression and schizophrenia. Finally, in diseases characterized by pathologic alterations in either the excitability within a single region or in the activity of distributed networks, such techniques provide a potential mechanism to alter cortical network function and architectures in a beneficial manner. PMID:22429242

Systems Modeling at Multiple Levels of Regulation: Linking Systems and Genetic Networks to Spatially Explicit Plant Populations

PubMed Central

Kitchen, James L.; Allaby, Robin G.

2013-01-01

Selection and adaptation of individuals to their underlying environments are highly dynamical processes, encompassing interactions between the individual and its seasonally changing environment, synergistic or antagonistic interactions between individuals and interactions amongst the regulatory genes within the individual. Plants are useful organisms to study within systems modeling because their sedentary nature simplifies interactions between individuals and the environment, and many important plant processes such as germination or flowering are dependent on annual cycles which can be disrupted by climate behavior. Sedentism makes plants relevant candidates for spatially explicit modeling that is tied in with dynamical environments. We propose that in order to fully understand the complexities behind plant adaptation, a system that couples aspects from systems biology with population and landscape genetics is required. A suitable system could be represented by spatially explicit individual-based models where the virtual individuals are located within time-variable heterogeneous environments and contain mutable regulatory gene networks. These networks could directly interact with the environment, and should provide a useful approach to studying plant adaptation. PMID:27137364

Integrating Genetic and Gene Co-expression Analysis Identifies Gene Networks Involved in Alcohol and Stress Responses

PubMed Central

Luo, Jie; Xu, Pei; Cao, Peijian; Wan, Hongjian; Lv, Xiaonan; Xu, Shengchun; Wang, Gangjun; Cook, Melloni N.; Jones, Byron C.; Lu, Lu; Wang, Xusheng

2018-01-01

Although the link between stress and alcohol is well recognized, the underlying mechanisms of how they interplay at the molecular level remain unclear. The purpose of this study is to identify molecular networks underlying the effects of alcohol and stress responses, as well as their interaction on anxiety behaviors in the hippocampus of mice using a systems genetics approach. Here, we applied a gene co-expression network approach to transcriptomes of 41 BXD mouse strains under four conditions: stress, alcohol, stress-induced alcohol and control. The co-expression analysis identified 14 modules and characterized four expression patterns across the four conditions. The four expression patterns include up-regulation in no restraint stress and given an ethanol injection (NOE) but restoration in restraint stress followed by an ethanol injection (RSE; pattern 1), down-regulation in NOE but rescue in RSE (pattern 2), up-regulation in both restraint stress followed by a saline injection (RSS) and NOE, and further amplification in RSE (pattern 3), and up-regulation in RSS but reduction in both NOE and RSE (pattern 4). We further identified four functional subnetworks by superimposing protein-protein interactions (PPIs) to the 14 co-expression modules, including γ-aminobutyric acid receptor (GABA) signaling, glutamate signaling, neuropeptide signaling, cAMP-dependent signaling. We further performed module specificity analysis to identify modules that are specific to stress, alcohol, or stress-induced alcohol responses. Finally, we conducted causality analysis to link genetic variation to these identified modules, and anxiety behaviors after stress and alcohol treatments. This study underscores the importance of integrative analysis and offers new insights into the molecular networks underlying stress and alcohol responses. PMID:29674951

Integrated Analysis of Long Noncoding RNA and mRNA Expression Profile in Advanced Laryngeal Squamous Cell Carcinoma.

PubMed

Feng, Ling; Wang, Ru; Lian, Meng; Ma, Hongzhi; He, Ning; Liu, Honggang; Wang, Haizhou; Fang, Jugao

2016-01-01

Long non-coding RNA (lncRNA) plays an important role in tumorigenesis. However, the expression pattern and function of lncRNAs in laryngeal squamous cell carcinoma (LSCC) are still unclear. To investigate the aberrantly expressed lncRNAs and mRNAs in advanced LSCC, we screened lncRNA and mRNA expression profiles in 9 pairs of primary Stage IVA LSCC tissues and adjacent non-neoplastic tissues by lncRNA and mRNA integrated microarrays. Gene Ontology and pathway analysis were performed to find out the significant function and pathway of the differentially expressed mRNAs, gene-gene functional interaction network and ceRNA network were constructed to select core mRNAs, and lncRNA-mRNA expression correlation network was built to identify the interactions between lncRNA and mRNA. qRT-PCR was performed to further validate the expressions of selected lncRNAs and mRNAs in advanced LSCC. We found 1459 differentially expressed lncRNAs and 2381 differentially expressed mRNAs, including 846 up-regulated lncRNAs and 613 down-regulated lncRNAs, 1542 up-regulated mRNAs and 839 down-regulated mRNAs. The mRNAs ITGB1, HIF1A, and DDIT4 were selected as core mRNAs, which are mainly involved in biological processes, such as matrix organization, cell cycle, adhesion, and metabolic pathway. LncRNA-mRNA expression correlation network showed LncRNA NR_027340, MIR31HG were positively correlated with ITGB1, HIF1A respectively. LncRNA SOX2-OT was negatively correlated with DDIT4. qRT-PCR further validated the expression of these lncRNAs and mRNAs. The work provides convincing evidence that the identified lncRNAs and mRNAs are potential biomarkers in advanced LSCC for further future studies.

Circuit variability interacts with excitatory-inhibitory diversity of interneurons to regulate network encoding capacity.

PubMed

Tsai, Kuo-Ting; Hu, Chin-Kun; Li, Kuan-Wei; Hwang, Wen-Liang; Chou, Ya-Hui

2018-05-23

Local interneurons (LNs) in the Drosophila olfactory system exhibit neuronal diversity and variability, yet it is still unknown how these features impact information encoding capacity and reliability in a complex LN network. We employed two strategies to construct a diverse excitatory-inhibitory neural network beginning with a ring network structure and then introduced distinct types of inhibitory interneurons and circuit variability to the simulated network. The continuity of activity within the node ensemble (oscillation pattern) was used as a readout to describe the temporal dynamics of network activity. We found that inhibitory interneurons enhance the encoding capacity by protecting the network from extremely short activation periods when the network wiring complexity is very high. In addition, distinct types of interneurons have differential effects on encoding capacity and reliability. Circuit variability may enhance the encoding reliability, with or without compromising encoding capacity. Therefore, we have described how circuit variability of interneurons may interact with excitatory-inhibitory diversity to enhance the encoding capacity and distinguishability of neural networks. In this work, we evaluate the effects of different types and degrees of connection diversity on a ring model, which may simulate interneuron networks in the Drosophila olfactory system or other biological systems.

Inference of RhoGAP/GTPase regulation using single-cell morphological data from a combinatorial RNAi screen.

PubMed

Nir, Oaz; Bakal, Chris; Perrimon, Norbert; Berger, Bonnie

2010-03-01

Biological networks are highly complex systems, consisting largely of enzymes that act as molecular switches to activate/inhibit downstream targets via post-translational modification. Computational techniques have been developed to perform signaling network inference using some high-throughput data sources, such as those generated from transcriptional and proteomic studies, but comparable methods have not been developed to use high-content morphological data, which are emerging principally from large-scale RNAi screens, to these ends. Here, we describe a systematic computational framework based on a classification model for identifying genetic interactions using high-dimensional single-cell morphological data from genetic screens, apply it to RhoGAP/GTPase regulation in Drosophila, and evaluate its efficacy. Augmented by knowledge of the basic structure of RhoGAP/GTPase signaling, namely, that GAPs act directly upstream of GTPases, we apply our framework for identifying genetic interactions to predict signaling relationships between these proteins. We find that our method makes mediocre predictions using only RhoGAP single-knockdown morphological data, yet achieves vastly improved accuracy by including original data from a double-knockdown RhoGAP genetic screen, which likely reflects the redundant network structure of RhoGAP/GTPase signaling. We consider other possible methods for inference and show that our primary model outperforms the alternatives. This work demonstrates the fundamental fact that high-throughput morphological data can be used in a systematic, successful fashion to identify genetic interactions and, using additional elementary knowledge of network structure, to infer signaling relations.

An Interaction Library for the FcεRI Signaling Network

DOE PAGES

Chylek, Lily A.; Holowka, David A.; Baird, Barbara A.; ...

2014-04-15

Antigen receptors play a central role in adaptive immune responses. Although the molecular networks associated with these receptors have been extensively studied, we currently lack a systems-level understanding of how combinations of non-covalent interactions and post-translational modifications are regulated during signaling to impact cellular decision-making. To fill this knowledge gap, it will be necessary to formalize and piece together information about individual molecular mechanisms to form large-scale computational models of signaling networks. To this end, we have developed an interaction library for signaling by the high-affinity IgE receptor, FcεRI. The library consists of executable rules for protein–protein and protein–lipid interactions.more » This library extends earlier models for FcεRI signaling and introduces new interactions that have not previously been considered in a model. Thus, this interaction library is a toolkit with which existing models can be expanded and from which new models can be built. As an example, we present models of branching pathways from the adaptor protein Lat, which influence production of the phospholipid PIP 3 at the plasma membrane and the soluble second messenger IP 3. We find that inclusion of a positive feedback loop gives rise to a bistable switch, which may ensure robust responses to stimulation above a threshold level. In addition, the library is visualized to facilitate understanding of network circuitry and identification of network motifs.« less

An Interaction Library for the FcεRI Signaling Network

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

Chylek, Lily A.; Holowka, David A.; Baird, Barbara A.

Antigen receptors play a central role in adaptive immune responses. Although the molecular networks associated with these receptors have been extensively studied, we currently lack a systems-level understanding of how combinations of non-covalent interactions and post-translational modifications are regulated during signaling to impact cellular decision-making. To fill this knowledge gap, it will be necessary to formalize and piece together information about individual molecular mechanisms to form large-scale computational models of signaling networks. To this end, we have developed an interaction library for signaling by the high-affinity IgE receptor, FcεRI. The library consists of executable rules for protein–protein and protein–lipid interactions.more » This library extends earlier models for FcεRI signaling and introduces new interactions that have not previously been considered in a model. Thus, this interaction library is a toolkit with which existing models can be expanded and from which new models can be built. As an example, we present models of branching pathways from the adaptor protein Lat, which influence production of the phospholipid PIP 3 at the plasma membrane and the soluble second messenger IP 3. We find that inclusion of a positive feedback loop gives rise to a bistable switch, which may ensure robust responses to stimulation above a threshold level. In addition, the library is visualized to facilitate understanding of network circuitry and identification of network motifs.« less

Robustness of the p53 network and biological hackers.

PubMed

Dartnell, Lewis; Simeonidis, Evangelos; Hubank, Michael; Tsoka, Sophia; Bogle, I David L; Papageorgiou, Lazaros G

2005-06-06

The p53 protein interaction network is crucial in regulating the metazoan cell cycle and apoptosis. Here, the robustness of the p53 network is studied by analyzing its degeneration under two modes of attack. Linear Programming is used to calculate average path lengths among proteins and the network diameter as measures of functionality. The p53 network is found to be robust to random loss of nodes, but vulnerable to a targeted attack against its hubs, as a result of its architecture. The significance of the results is considered with respect to mutational knockouts of proteins and the directed attacks mounted by tumour inducing viruses.

SATRAT: Staphylococcus aureus transcript regulatory network analysis tool.

PubMed

Gopal, Tamilselvi; Nagarajan, Vijayaraj; Elasri, Mohamed O

2015-01-01

Staphylococcus aureus is a commensal organism that primarily colonizes the nose of healthy individuals. S. aureus causes a spectrum of infections that range from skin and soft-tissue infections to fatal invasive diseases. S. aureus uses a large number of virulence factors that are regulated in a coordinated fashion. The complex regulatory mechanisms have been investigated in numerous high-throughput experiments. Access to this data is critical to studying this pathogen. Previously, we developed a compilation of microarray experimental data to enable researchers to search, browse, compare, and contrast transcript profiles. We have substantially updated this database and have built a novel exploratory tool-SATRAT-the S. aureus transcript regulatory network analysis tool, based on the updated database. This tool is capable of performing deep searches using a query and generating an interactive regulatory network based on associations among the regulators of any query gene. We believe this integrated regulatory network analysis tool would help researchers explore the missing links and identify novel pathways that regulate virulence in S. aureus. Also, the data model and the network generation code used to build this resource is open sourced, enabling researchers to build similar resources for other bacterial systems.

Large-scale investigation of Leishmania interaction networks with host extracellular matrix by surface plasmon resonance imaging.

PubMed

Fatoux-Ardore, Marie; Peysselon, Franck; Weiss, Anthony; Bastien, Patrick; Pratlong, Francine; Ricard-Blum, Sylvie

2014-02-01

We have set up an assay to study the interactions of live pathogens with their hosts by using protein and glycosaminoglycan arrays probed by surface plasmon resonance imaging. We have used this assay to characterize the interactions of Leishmania promastigotes with ~70 mammalian host biomolecules (extracellular proteins, glycosaminoglycans, growth factors, cell surface receptors). We have identified, in total, 27 new partners (23 proteins, 4 glycosaminoglycans) of procyclic promastigotes of six Leishmania species and 18 partners (15 proteins, 3 glycosaminoglycans) of three species of stationary-phase promastigotes for all the strains tested. The diversity of the interaction repertoires of Leishmania parasites reflects their dynamic and complex interplay with their mammalian hosts, which depends mostly on the species and strains of Leishmania. Stationary-phase Leishmania parasites target extracellular matrix proteins and glycosaminoglycans, which are highly connected in the extracellular interaction network. Heparin and heparan sulfate bind to most Leishmania strains tested, and 6-O-sulfate groups play a crucial role in these interactions. Numerous Leishmania strains bind to tropoelastin, and some strains are even able to degrade it. Several strains interact with collagen VI, which is expressed by macrophages. Most Leishmania promastigotes interact with several regulators of angiogenesis, including antiangiogenic factors (endostatin, anastellin) and proangiogenic factors (ECM-1, VEGF, and TEM8 [also known as anthrax toxin receptor 1]), which are regulated by hypoxia. Since hypoxia modulates the infection of macrophages by the parasites, these interactions might influence the infection of host cells by Leishmania.

Large-Scale Investigation of Leishmania Interaction Networks with Host Extracellular Matrix by Surface Plasmon Resonance Imaging

PubMed Central

Fatoux-Ardore, Marie; Peysselon, Franck; Weiss, Anthony; Bastien, Patrick; Pratlong, Francine

2014-01-01

We have set up an assay to study the interactions of live pathogens with their hosts by using protein and glycosaminoglycan arrays probed by surface plasmon resonance imaging. We have used this assay to characterize the interactions of Leishmania promastigotes with ∼70 mammalian host biomolecules (extracellular proteins, glycosaminoglycans, growth factors, cell surface receptors). We have identified, in total, 27 new partners (23 proteins, 4 glycosaminoglycans) of procyclic promastigotes of six Leishmania species and 18 partners (15 proteins, 3 glycosaminoglycans) of three species of stationary-phase promastigotes for all the strains tested. The diversity of the interaction repertoires of Leishmania parasites reflects their dynamic and complex interplay with their mammalian hosts, which depends mostly on the species and strains of Leishmania. Stationary-phase Leishmania parasites target extracellular matrix proteins and glycosaminoglycans, which are highly connected in the extracellular interaction network. Heparin and heparan sulfate bind to most Leishmania strains tested, and 6-O-sulfate groups play a crucial role in these interactions. Numerous Leishmania strains bind to tropoelastin, and some strains are even able to degrade it. Several strains interact with collagen VI, which is expressed by macrophages. Most Leishmania promastigotes interact with several regulators of angiogenesis, including antiangiogenic factors (endostatin, anastellin) and proangiogenic factors (ECM-1, VEGF, and TEM8 [also known as anthrax toxin receptor 1]), which are regulated by hypoxia. Since hypoxia modulates the infection of macrophages by the parasites, these interactions might influence the infection of host cells by Leishmania. PMID:24478075

Autophagy Regulatory Network - a systems-level bioinformatics resource for studying the mechanism and regulation of autophagy.

PubMed

Türei, Dénes; Földvári-Nagy, László; Fazekas, Dávid; Módos, Dezső; Kubisch, János; Kadlecsik, Tamás; Demeter, Amanda; Lenti, Katalin; Csermely, Péter; Vellai, Tibor; Korcsmáros, Tamás

2015-01-01

Autophagy is a complex cellular process having multiple roles, depending on tissue, physiological, or pathological conditions. Major post-translational regulators of autophagy are well known, however, they have not yet been collected comprehensively. The precise and context-dependent regulation of autophagy necessitates additional regulators, including transcriptional and post-transcriptional components that are listed in various datasets. Prompted by the lack of systems-level autophagy-related information, we manually collected the literature and integrated external resources to gain a high coverage autophagy database. We developed an online resource, Autophagy Regulatory Network (ARN; http://autophagy-regulation.org), to provide an integrated and systems-level database for autophagy research. ARN contains manually curated, imported, and predicted interactions of autophagy components (1,485 proteins with 4,013 interactions) in humans. We listed 413 transcription factors and 386 miRNAs that could regulate autophagy components or their protein regulators. We also connected the above-mentioned autophagy components and regulators with signaling pathways from the SignaLink 2 resource. The user-friendly website of ARN allows researchers without computational background to search, browse, and download the database. The database can be downloaded in SQL, CSV, BioPAX, SBML, PSI-MI, and in a Cytoscape CYS file formats. ARN has the potential to facilitate the experimental validation of novel autophagy components and regulators. In addition, ARN helps the investigation of transcription factors, miRNAs and signaling pathways implicated in the control of the autophagic pathway. The list of such known and predicted regulators could be important in pharmacological attempts against cancer and neurodegenerative diseases.

TGF-β/BMP signaling and other molecular events: regulation of osteoblastogenesis and bone formation

PubMed Central

Rahman, Md Shaifur; Akhtar, Naznin; Jamil, Hossen Mohammad; Banik, Rajat Suvra; Asaduzzaman, Sikder M

2015-01-01

Transforming growth factor-beta (TGF-β)/bone morphogenetic protein (BMP) plays a fundamental role in the regulation of bone organogenesis through the activation of receptor serine/threonine kinases. Perturbations of TGF-β/BMP activity are almost invariably linked to a wide variety of clinical outcomes, i.e., skeletal, extra skeletal anomalies, autoimmune, cancer, and cardiovascular diseases. Phosphorylation of TGF-β (I/II) or BMP receptors activates intracellular downstream Smads, the transducer of TGF-β/BMP signals. This signaling is modulated by various factors and pathways, including transcription factor Runx2. The signaling network in skeletal development and bone formation is overwhelmingly complex and highly time and space specific. Additive, positive, negative, or synergistic effects are observed when TGF-β/BMP interacts with the pathways of MAPK, Wnt, Hedgehog (Hh), Notch, Akt/mTOR, and miRNA to regulate the effects of BMP-induced signaling in bone dynamics. Accumulating evidence indicates that Runx2 is the key integrator, whereas Hh is a possible modulator, miRNAs are regulators, and β-catenin is a mediator/regulator within the extensive intracellular network. This review focuses on the activation of BMP signaling and interaction with other regulatory components and pathways highlighting the molecular mechanisms regarding TGF-β/BMP function and regulation that could allow understanding the complexity of bone tissue dynamics. PMID:26273537

Sailing the Cyber Sea

DTIC Science & Technology

2012-04-01

chatting, tweeting, blogging, social networking, retail activity, or business interactions, military organizations, govern- ment entities, nongovernmental...connected. The use of social media is a great idea that is growing in popularity and can be a great tool for all kinds of activities. Audience size can...realities of human expansion , commerce, and interaction typically outpace policies and regulations, much as during the days of the Wild West and

Mathematical Model of a Telomerase Transcriptional Regulatory Network Developed by Cell-Based Screening: Analysis of Inhibitor Effects and Telomerase Expression Mechanisms

PubMed Central

Bilsland, Alan E.; Stevenson, Katrina; Liu, Yu; Hoare, Stacey; Cairney, Claire J.; Roffey, Jon; Keith, W. Nicol

2014-01-01

Cancer cells depend on transcription of telomerase reverse transcriptase (TERT). Many transcription factors affect TERT, though regulation occurs in context of a broader network. Network effects on telomerase regulation have not been investigated, though deeper understanding of TERT transcription requires a systems view. However, control over individual interactions in complex networks is not easily achievable. Mathematical modelling provides an attractive approach for analysis of complex systems and some models may prove useful in systems pharmacology approaches to drug discovery. In this report, we used transfection screening to test interactions among 14 TERT regulatory transcription factors and their respective promoters in ovarian cancer cells. The results were used to generate a network model of TERT transcription and to implement a dynamic Boolean model whose steady states were analysed. Modelled effects of signal transduction inhibitors successfully predicted TERT repression by Src-family inhibitor SU6656 and lack of repression by ERK inhibitor FR180204, results confirmed by RT-QPCR analysis of endogenous TERT expression in treated cells. Modelled effects of GSK3 inhibitor 6-bromoindirubin-3′-oxime (BIO) predicted unstable TERT repression dependent on noise and expression of JUN, corresponding with observations from a previous study. MYC expression is critical in TERT activation in the model, consistent with its well known function in endogenous TERT regulation. Loss of MYC caused complete TERT suppression in our model, substantially rescued only by co-suppression of AR. Interestingly expression was easily rescued under modelled Ets-factor gain of function, as occurs in TERT promoter mutation. RNAi targeting AR, JUN, MXD1, SP3, or TP53, showed that AR suppression does rescue endogenous TERT expression following MYC knockdown in these cells and SP3 or TP53 siRNA also cause partial recovery. The model therefore successfully predicted several aspects of TERT regulation including previously unknown mechanisms. An extrapolation suggests that a dominant stimulatory system may programme TERT for transcriptional stability. PMID:24550717

Diffany: an ontology-driven framework to infer, visualise and analyse differential molecular networks.

PubMed

Van Landeghem, Sofie; Van Parys, Thomas; Dubois, Marieke; Inzé, Dirk; Van de Peer, Yves

2016-01-05

Differential networks have recently been introduced as a powerful way to study the dynamic rewiring capabilities of an interactome in response to changing environmental conditions or stimuli. Currently, such differential networks are generated and visualised using ad hoc methods, and are often limited to the analysis of only one condition-specific response or one interaction type at a time. In this work, we present a generic, ontology-driven framework to infer, visualise and analyse an arbitrary set of condition-specific responses against one reference network. To this end, we have implemented novel ontology-based algorithms that can process highly heterogeneous networks, accounting for both physical interactions and regulatory associations, symmetric and directed edges, edge weights and negation. We propose this integrative framework as a standardised methodology that allows a unified view on differential networks and promotes comparability between differential network studies. As an illustrative application, we demonstrate its usefulness on a plant abiotic stress study and we experimentally confirmed a predicted regulator. Diffany is freely available as open-source java library and Cytoscape plugin from http://bioinformatics.psb.ugent.be/supplementary_data/solan/diffany/.

Robustness in Regulatory Interaction Networks. A Generic Approach with Applications at Different Levels: Physiologic, Metabolic and Genetic

PubMed Central

Demongeot, Jacques; Ben Amor, Hedi; Elena, Adrien; Gillois, Pierre; Noual, Mathilde; Sené, Sylvain

2009-01-01

Regulatory interaction networks are often studied on their dynamical side (existence of attractors, study of their stability). We focus here also on their robustness, that is their ability to offer the same spatiotemporal patterns and to resist to external perturbations such as losses of nodes or edges in the networks interactions architecture, changes in their environmental boundary conditions as well as changes in the update schedule (or updating mode) of the states of their elements (e.g., if these elements are genes, their synchronous coexpression mode versus their sequential expression). We define the generic notions of boundary, core, and critical vertex or edge of the underlying interaction graph of the regulatory network, whose disappearance causes dramatic changes in the number and nature of attractors (e.g., passage from a bistable behaviour to a unique periodic regime) or in the range of their basins of stability. The dynamic transition of states will be presented in the framework of threshold Boolean automata rules. A panorama of applications at different levels will be given: brain and plant morphogenesis, bulbar cardio-respiratory regulation, glycolytic/oxidative metabolic coupling, and eventually cell cycle and feather morphogenesis genetic control. PMID:20057955

Exploring Plant Co-Expression and Gene-Gene Interactions with CORNET 3.0.

PubMed

Van Bel, Michiel; Coppens, Frederik

2017-01-01

Selecting and filtering a reference expression and interaction dataset when studying specific pathways and regulatory interactions can be a very time-consuming and error-prone task. In order to reduce the duplicated efforts required to amass such datasets, we have created the CORNET (CORrelation NETworks) platform which allows for easy access to a wide variety of data types: coexpression data, protein-protein interactions, regulatory interactions, and functional annotations. The CORNET platform outputs its results in either text format or through the Cytoscape framework, which is automatically launched by the CORNET website.CORNET 3.0 is the third iteration of the web platform designed for the user exploration of the coexpression space of plant genomes, with a focus on the model species Arabidopsis thaliana. Here we describe the platform: the tools, data, and best practices when using the platform. We indicate how the platform can be used to infer networks from a set of input genes, such as upregulated genes from an expression experiment. By exploring the network, new target and regulator genes can be discovered, allowing for follow-up experiments and more in-depth study. We also indicate how to avoid common pitfalls when evaluating the networks and how to avoid over interpretation of the results.All CORNET versions are available at http://bioinformatics.psb.ugent.be/cornet/ .

The condition-dependent transcriptional network in Escherichia coli.

PubMed

Lemmens, Karen; De Bie, Tijl; Dhollander, Thomas; Monsieurs, Pieter; De Moor, Bart; Collado-Vides, Julio; Engelen, Kristof; Marchal, Kathleen

2009-03-01

Thanks to the availability of high-throughput omics data, bioinformatics approaches are able to hypothesize thus-far undocumented genetic interactions. However, due to the amount of noise in these data, inferences based on a single data source are often unreliable. A popular approach to overcome this problem is to integrate different data sources. In this study, we describe DISTILLER, a novel framework for data integration that simultaneously analyzes microarray and motif information to find modules that consist of genes that are co-expressed in a subset of conditions, and their corresponding regulators. By applying our method on publicly available data, we evaluated the condition-specific transcriptional network of Escherichia coli. DISTILLER confirmed 62% of 736 interactions described in RegulonDB, and 278 novel interactions were predicted.

Novel GM animal technologies and their governance.

PubMed

Bruce, Ann; Castle, David; Gibbs, Corrina; Tait, Joyce; Whitelaw, C Bruce A

2013-08-01

Scientific advances in methods of producing genetically modified (GM) animals continue, yet few such animals have reached commercial production. Existing regulations designed for early techniques of genetic modification pose formidable barriers to commercial applications. Radically improved techniques for producing GM animals invite a re-examination of current regulatory regimes. We critically examine current GM animal regulations, with a particular focus on the European Union, through a framework that recognises the importance of interactions among regulatory regimes, innovation outcomes and industry sectors. The current focus on the regulation of risk is necessary but is unable to discriminate among applications and tends to close down broad areas of application rather than facilitate innovation and positive industry interactions. Furthermore, the fields of innovative animal biosciences appear to lack networks of organisations with co-ordinated future oriented actions. Such networks could drive coherent programmes of innovation towards particular visions and contribute actively to the development of regulatory systems for GM animals. The analysis presented makes the case for regulatory consideration of each animal bioscience related innovation on the basis of the nature of the product itself and not the process by which it was developed.

Axon tension regulates fasciculation/defasciculation through the control of axon shaft zippering

PubMed Central

Šmít, Daniel; Fouquet, Coralie; Pincet, Frédéric; Zapotocky, Martin; Trembleau, Alain

2017-01-01

While axon fasciculation plays a key role in the development of neural networks, very little is known about its dynamics and the underlying biophysical mechanisms. In a model system composed of neurons grown ex vivo from explants of embryonic mouse olfactory epithelia, we observed that axons dynamically interact with each other through their shafts, leading to zippering and unzippering behavior that regulates their fasciculation. Taking advantage of this new preparation suitable for studying such interactions, we carried out a detailed biophysical analysis of zippering, occurring either spontaneously or induced by micromanipulations and pharmacological treatments. We show that zippering arises from the competition of axon-axon adhesion and mechanical tension in the axons, and provide the first quantification of the force of axon-axon adhesion. Furthermore, we introduce a biophysical model of the zippering dynamics, and we quantitatively relate the individual zipper properties to global characteristics of the developing axon network. Our study uncovers a new role of mechanical tension in neural development: the regulation of axon fasciculation. DOI: http://dx.doi.org/10.7554/eLife.19907.001 PMID:28422009

Emotion regulation in bereavement: searching for and finding emotional support in social network sites

NASA Astrophysics Data System (ADS)

Döveling, Katrin

2015-04-01

In an age of rising impact of online communication in social network sites (SNS), emotional interaction is neither limited nor restricted by time or space. Bereavement extends to the anonymity of cyberspace. What role does virtual interaction play in SNS in dealing with the basic human emotion of grief caused by the loss of a beloved person? The analysis laid out in this article provides answers in light of an interdisciplinary perspective on online bereavement. Relevant lines of research are scrutinized. After laying out the theoretical spectrum for the study, hypotheses based on a prior in-depth qualitative content analysis of 179 postings in three different German online bereavement platforms are proposed and scrutinized in a quantitative content analysis (2127 postings from 318 users). Emotion regulation patterns in SNS and similarities as well as differences in online bereavement of children, adolescents and adults are revealed. Large-scale quantitative findings into central motives, patterns, and restorative effects of online shared bereavement in regulating distress, fostering personal empowerment, and engendering meaning are presented. The article closes with implications for further analysis in memorialization practices.

Flavivirus NS3 and NS5 proteins interaction network: a high-throughput yeast two-hybrid screen

PubMed Central

2011-01-01

Background The genus Flavivirus encompasses more than 50 distinct species of arthropod-borne viruses, including several major human pathogens, such as West Nile virus, yellow fever virus, Japanese encephalitis virus and the four serotypes of dengue viruses (DENV type 1-4). Each year, flaviviruses cause more than 100 million infections worldwide, some of which lead to life-threatening conditions such as encephalitis or haemorrhagic fever. Among the viral proteins, NS3 and NS5 proteins constitute the major enzymatic components of the viral replication complex and are essential to the flavivirus life cycle. Results We report here the results of a high-throughput yeast two-hybrid screen to identify the interactions between human host proteins and the flavivirus NS3 and NS5 proteins. Using our screen results and literature curation, we performed a global analysis of the NS3 and NS5 cellular targets based on functional annotation with the Gene Ontology features. We finally created the first flavivirus NS3 and NS5 proteins interaction network and analysed the topological features of this network. Our proteome mapping screen identified 108 human proteins interacting with NS3 or NS5 proteins or both. The global analysis of the cellular targets revealed the enrichment of host proteins involved in RNA binding, transcription regulation, vesicular transport or innate immune response regulation. Conclusions We proposed that the selective disruption of these newly identified host/virus interactions could represent a novel and attractive therapeutic strategy in treating flavivirus infections. Our virus-host interaction map provides a basis to unravel fundamental processes about flavivirus subversion of the host replication machinery and/or immune defence strategy. PMID:22014111

Flavivirus NS3 and NS5 proteins interaction network: a high-throughput yeast two-hybrid screen.

PubMed

Le Breton, Marc; Meyniel-Schicklin, Laurène; Deloire, Alexandre; Coutard, Bruno; Canard, Bruno; de Lamballerie, Xavier; Andre, Patrice; Rabourdin-Combe, Chantal; Lotteau, Vincent; Davoust, Nathalie

2011-10-20

The genus Flavivirus encompasses more than 50 distinct species of arthropod-borne viruses, including several major human pathogens, such as West Nile virus, yellow fever virus, Japanese encephalitis virus and the four serotypes of dengue viruses (DENV type 1-4). Each year, flaviviruses cause more than 100 million infections worldwide, some of which lead to life-threatening conditions such as encephalitis or haemorrhagic fever. Among the viral proteins, NS3 and NS5 proteins constitute the major enzymatic components of the viral replication complex and are essential to the flavivirus life cycle. We report here the results of a high-throughput yeast two-hybrid screen to identify the interactions between human host proteins and the flavivirus NS3 and NS5 proteins. Using our screen results and literature curation, we performed a global analysis of the NS3 and NS5 cellular targets based on functional annotation with the Gene Ontology features. We finally created the first flavivirus NS3 and NS5 proteins interaction network and analysed the topological features of this network. Our proteome mapping screen identified 108 human proteins interacting with NS3 or NS5 proteins or both. The global analysis of the cellular targets revealed the enrichment of host proteins involved in RNA binding, transcription regulation, vesicular transport or innate immune response regulation. We proposed that the selective disruption of these newly identified host/virus interactions could represent a novel and attractive therapeutic strategy in treating flavivirus infections. Our virus-host interaction map provides a basis to unravel fundamental processes about flavivirus subversion of the host replication machinery and/or immune defence strategy.

Dynamic interactions between Pit-1 and C/EBPalpha in the pituitary cell nucleus.

PubMed

Demarco, Ignacio A; Voss, Ty C; Booker, Cynthia F; Day, Richard N

2006-11-01

The homeodomain (HD) transcription factors are a structurally conserved family of proteins that, through networks of interactions with other nuclear proteins, control patterns of gene expression during development. For example, the network interactions of the pituitary-specific HD protein Pit-1 control the development of anterior pituitary cells and regulate the expression of the hormone products in the adult cells. Inactivating mutations in Pit-1 disrupt these processes, giving rise to the syndrome of combined pituitary hormone deficiency. Pit-1 interacts with CCAAT/enhancer-binding protein alpha (C/EBPalpha) to regulate prolactin transcription. Here, we used the combination of biochemical analysis and live-cell microscopy to show that two different point mutations in Pit-1, which disrupted distinct activities, affected the dynamic interactions between Pit-1 and C/EBPalpha in different ways. The results showed that the first alpha-helix of the POU-S domain is critical for the assembly of Pit-1 with C/EBPalpha, and they showed that DNA-binding activity conferred by the HD is critical for the final intranuclear positioning of the metastable complex. This likely reflects more general mechanisms that govern cell-type-specific transcriptional control, and the results from the analysis of the point mutations could indicate an important link between the mislocalization of transcriptional complexes and disease processes.

Quantifying the underlying landscape and paths of cancer

PubMed Central

Li, Chunhe; Wang, Jin

2014-01-01

Cancer is a disease regulated by the underlying gene networks. The emergence of normal and cancer states as well as the transformation between them can be thought of as a result of the gene network interactions and associated changes. We developed a global potential landscape and path framework to quantify cancer and associated processes. We constructed a cancer gene regulatory network based on the experimental evidences and uncovered the underlying landscape. The resulting tristable landscape characterizes important biological states: normal, cancer and apoptosis. The landscape topography in terms of barrier heights between stable state attractors quantifies the global stability of the cancer network system. We propose two mechanisms of cancerization: one is by the changes of landscape topography through the changes in regulation strengths of the gene networks. The other is by the fluctuations that help the system to go over the critical barrier at fixed landscape topography. The kinetic paths from least action principle quantify the transition processes among normal state, cancer state and apoptosis state. The kinetic rates provide the quantification of transition speeds among normal, cancer and apoptosis attractors. By the global sensitivity analysis of the gene network parameters on the landscape topography, we uncovered some key gene regulations determining the transitions between cancer and normal states. This can be used to guide the design of new anti-cancer tactics, through cocktail strategy of targeting multiple key regulation links simultaneously, for preventing cancer occurrence or transforming the early cancer state back to normal state. PMID:25232051

Investigation of the multifunctional gene AOP3 expands the regulatory network fine-tuning glucosinolate production in Arabidopsis

PubMed Central

Jensen, Lea M.; Kliebenstein, Daniel J.; Burow, Meike

2015-01-01

Quantitative trait loci (QTL) mapping studies enable identification of loci that are part of regulatory networks controlling various phenotypes. Detailed investigations of genes within these loci are required to ultimately understand the function of individual genes and how they interact with other players in the network. In this study, we use transgenic plants in combination with natural variation to investigate the regulatory role of the AOP3 gene found in GS-AOP locus previously suggested to contribute to the regulation of glucosinolate defense compounds. Phenotypic analysis and QTL mapping in F2 populations with different AOP3 transgenes support that the enzymatic function and the AOP3 RNA both play a significant role in controlling glucosinolate accumulation. Furthermore, we find different loci interacting with either the enzymatic activity or the RNA of AOP3 and thereby extend the regulatory network controlling glucosinolate accumulation. PMID:26442075

Identification of Causal Genes, Networks, and Transcriptional Regulators of REM Sleep and Wake

PubMed Central

Millstein, Joshua; Winrow, Christopher J.; Kasarskis, Andrew; Owens, Joseph R.; Zhou, Lili; Summa, Keith C.; Fitzpatrick, Karrie; Zhang, Bin; Vitaterna, Martha H.; Schadt, Eric E.; Renger, John J.; Turek, Fred W.

2011-01-01

Study Objective: Sleep-wake traits are well-known to be under substantial genetic control, but the specific genes and gene networks underlying primary sleep-wake traits have largely eluded identification using conventional approaches, especially in mammals. Thus, the aim of this study was to use systems genetics and statistical approaches to uncover the genetic networks underlying 2 primary sleep traits in the mouse: 24-h duration of REM sleep and wake. Design: Genome-wide RNA expression data from 3 tissues (anterior cortex, hypothalamus, thalamus/midbrain) were used in conjunction with high-density genotyping to identify candidate causal genes and networks mediating the effects of 2 QTL regulating the 24-h duration of REM sleep and one regulating the 24-h duration of wake. Setting: Basic sleep research laboratory. Patients or Participants: Male [C57BL/6J × (BALB/cByJ × C57BL/6J*) F1] N2 mice (n = 283). Interventions: None. Measurements and Results: The genetic variation of a mouse N2 mapping cross was leveraged against sleep-state phenotypic variation as well as quantitative gene expression measurement in key brain regions using integrative genomics approaches to uncover multiple causal sleep-state regulatory genes, including several surprising novel candidates, which interact as components of networks that modulate REM sleep and wake. In particular, it was discovered that a core network module, consisting of 20 genes, involved in the regulation of REM sleep duration is conserved across the cortex, hypothalamus, and thalamus. A novel application of a formal causal inference test was also used to identify those genes directly regulating sleep via control of expression. Conclusion: Systems genetics approaches reveal novel candidate genes, complex networks and specific transcriptional regulators of REM sleep and wake duration in mammals. Citation: Millstein J; Winrow CJ; Kasarskis A; Owens JR; Zhou L; Summa KC; Fitzpatrick K; Zhang B; Vitaterna MH; Schadt EE; Renger JJ; Turek FW. Identification of causal genes, networks, and transcriptional regulators of REM sleep and wake. SLEEP 2011;34(11):1469-1477. PMID:22043117

A Clb/Cdk1-mediated regulation of Fkh2 synchronizes CLB expression in the budding yeast cell cycle.

PubMed

Linke, Christian; Chasapi, Anastasia; González-Novo, Alberto; Al Sawad, Istabrak; Tognetti, Silvia; Klipp, Edda; Loog, Mart; Krobitsch, Sylvia; Posas, Francesc; Xenarios, Ioannis; Barberis, Matteo

2017-01-01

Precise timing of cell division is achieved by coupling waves of cyclin-dependent kinase (Cdk) activity with a transcriptional oscillator throughout cell cycle progression. Although details of transcription of cyclin genes are known, it is unclear which is the transcriptional cascade that modulates their expression in a timely fashion. Here, we demonstrate that a Clb/Cdk1-mediated regulation of the Fkh2 transcription factor synchronizes the temporal mitotic CLB expression in budding yeast. A simplified kinetic model of the cyclin/Cdk network predicts a linear cascade where a Clb/Cdk1-mediated regulation of an activator molecule drives CLB3 and CLB2 expression. Experimental validation highlights Fkh2 as modulator of CLB3 transcript levels, besides its role in regulating CLB2 expression. A Boolean model based on the minimal number of interactions needed to capture the information flow of the Clb/Cdk1 network supports the role of an activator molecule in the sequential activation, and oscillatory behavior, of mitotic Clb cyclins. This work illustrates how transcription and phosphorylation networks can be coupled by a Clb/Cdk1-mediated regulation that synchronizes them.

GeneNetFinder2: Improved Inference of Dynamic Gene Regulatory Relations with Multiple Regulators.

PubMed

Han, Kyungsook; Lee, Jeonghoon

2016-01-01

A gene involved in complex regulatory interactions may have multiple regulators since gene expression in such interactions is often controlled by more than one gene. Another thing that makes gene regulatory interactions complicated is that regulatory interactions are not static, but change over time during the cell cycle. Most research so far has focused on identifying gene regulatory relations between individual genes in a particular stage of the cell cycle. In this study we developed a method for identifying dynamic gene regulations of several types from the time-series gene expression data. The method can find gene regulations with multiple regulators that work in combination or individually as well as those with single regulators. The method has been implemented as the second version of GeneNetFinder (hereafter called GeneNetFinder2) and tested on several gene expression datasets. Experimental results with gene expression data revealed the existence of genes that are not regulated by individual genes but rather by a combination of several genes. Such gene regulatory relations cannot be found by conventional methods. Our method finds such regulatory relations as well as those with multiple, independent regulators or single regulators, and represents gene regulatory relations as a dynamic network in which different gene regulatory relations are shown in different stages of the cell cycle. GeneNetFinder2 is available at http://bclab.inha.ac.kr/GeneNetFinder and will be useful for modeling dynamic gene regulations with multiple regulators.

Network dysfunction predicts speech production after left hemisphere stroke.

PubMed

Geranmayeh, Fatemeh; Leech, Robert; Wise, Richard J S

2016-03-09

To investigate the role of multiple distributed brain networks, including the default mode, fronto-temporo-parietal, and cingulo-opercular networks, which mediate domain-general and task-specific processes during speech production after aphasic stroke. We conducted an observational functional MRI study to investigate the effects of a previous left hemisphere stroke on functional connectivity within and between distributed networks as patients described pictures. Study design included various baseline tasks, and we compared results to those of age-matched healthy participants performing the same tasks. We used independent component and psychophysiological interaction analyses. Although activity within individual networks was not predictive of speech production, relative activity between networks was a predictor of both within-scanner and out-of-scanner language performance, over and above that predicted from lesion volume, age, sex, and years of education. Specifically, robust functional imaging predictors were the differential activity between the default mode network and both the left and right fronto-temporo-parietal networks, respectively activated and deactivated during speech. We also observed altered between-network functional connectivity of these networks in patients during speech production. Speech production is dependent on complex interactions among widely distributed brain networks, indicating that residual speech production after stroke depends on more than the restoration of local domain-specific functions. Our understanding of the recovery of function following focal lesions is not adequately captured by consideration of ipsilesional or contralesional brain regions taking over lost domain-specific functions, but is perhaps best considered as the interaction between what remains of domain-specific networks and domain-general systems that regulate behavior. © 2016 American Academy of Neurology.

Network dysfunction predicts speech production after left hemisphere stroke

PubMed Central

Leech, Robert; Wise, Richard J.S.

2016-01-01

Objective: To investigate the role of multiple distributed brain networks, including the default mode, fronto-temporo-parietal, and cingulo-opercular networks, which mediate domain-general and task-specific processes during speech production after aphasic stroke. Methods: We conducted an observational functional MRI study to investigate the effects of a previous left hemisphere stroke on functional connectivity within and between distributed networks as patients described pictures. Study design included various baseline tasks, and we compared results to those of age-matched healthy participants performing the same tasks. We used independent component and psychophysiological interaction analyses. Results: Although activity within individual networks was not predictive of speech production, relative activity between networks was a predictor of both within-scanner and out-of-scanner language performance, over and above that predicted from lesion volume, age, sex, and years of education. Specifically, robust functional imaging predictors were the differential activity between the default mode network and both the left and right fronto-temporo-parietal networks, respectively activated and deactivated during speech. We also observed altered between-network functional connectivity of these networks in patients during speech production. Conclusions: Speech production is dependent on complex interactions among widely distributed brain networks, indicating that residual speech production after stroke depends on more than the restoration of local domain-specific functions. Our understanding of the recovery of function following focal lesions is not adequately captured by consideration of ipsilesional or contralesional brain regions taking over lost domain-specific functions, but is perhaps best considered as the interaction between what remains of domain-specific networks and domain-general systems that regulate behavior. PMID:26962070

The Topology of the Growing Human Interactome Data.

PubMed

Janjić, Vuk; Pržulj, Nataša

2014-06-01

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

The topology of the growing human interactome data.

PubMed

Janjić, Vuk; Pržulj, Nataša

2014-06-23

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

Modular biological function is most effectively captured by combining molecular interaction data types.

PubMed

Ames, Ryan M; Macpherson, Jamie I; Pinney, John W; Lovell, Simon C; Robertson, David L

2013-01-01

Large-scale molecular interaction data sets have the potential to provide a comprehensive, system-wide understanding of biological function. Although individual molecules can be promiscuous in terms of their contribution to function, molecular functions emerge from the specific interactions of molecules giving rise to modular organisation. As functions often derive from a range of mechanisms, we demonstrate that they are best studied using networks derived from different sources. Implementing a graph partitioning algorithm we identify subnetworks in yeast protein-protein interaction (PPI), genetic interaction and gene co-regulation networks. Among these subnetworks we identify cohesive subgraphs that we expect to represent functional modules in the different data types. We demonstrate significant overlap between the subgraphs generated from the different data types and show these overlaps can represent related functions as represented by the Gene Ontology (GO). Next, we investigate the correspondence between our subgraphs and the Gene Ontology. This revealed varying degrees of coverage of the biological process, molecular function and cellular component ontologies, dependent on the data type. For example, subgraphs from the PPI show enrichment for 84%, 58% and 93% of annotated GO terms, respectively. Integrating the interaction data into a combined network increases the coverage of GO. Furthermore, the different annotation types of GO are not predominantly associated with one of the interaction data types. Collectively our results demonstrate that successful capture of functional relationships by network data depends on both the specific biological function being characterised and the type of network data being used. We identify functions that require integrated information to be accurately represented, demonstrating the limitations of individual data types. Combining interaction subnetworks across data types is therefore essential for fully understanding the complex and emergent nature of biological function.

SH3 interactome conserves general function over specific form

PubMed Central

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

2013-01-01

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

Ethylene-responsive element-binding factor 5, ERF5, is involved in chitin-induced innate immunity response.

PubMed

Son, Geon Hui; Wan, Jinrong; Kim, Hye Jin; Nguyen, Xuan Canh; Chung, Woo Sik; Hong, Jong Chan; Stacey, Gary

2012-01-01

Our recent work demonstrated that chitin treatment modulated the expression of 118 transcription factor (TF) genes in Arabidopsis. To investigate the potential roles of these TF in chitin signaling and plant defense, we initiated an interaction study among these TF proteins, as well as two chitin-activated mitogen-activated protein kinases (MPK3 and MPK6), using a yeast two-hybrid system. This study revealed interactions among the following proteins: three ethylene-responsive element-binding factors (ERF), five WRKY transcription factors, one scarecrow-like (SCL), and the two MPK, in addition to many other interactions, reflecting a complex TF interaction network. Most of these interactions were subsequently validated by other methods, such as pull-down and in planta bimolecular fluorescence complementation assays. The key node ERF5 was shown to interact with multiple proteins in the network, such as ERF6, ERF8, and SCL13, as well as MPK3 and MPK6. Interestingly, ERF5 appeared to negatively regulate chitin signaling and plant defense against the fungal pathogen Alternaria brassicicola and positively regulate salicylic acid signaling and plant defense against the bacterial pathogen Pseudomonas syringae pv. tomato DC3000. Therefore, ERF5 may play an important role in plant innate immunity, likely through coordinating chitin and other defense pathways in plants in response to different pathogens.

MiRNA-miRNA synergistic network: construction via co-regulating functional modules and disease miRNA topological features.

PubMed

Xu, Juan; Li, Chuan-Xing; Li, Yong-Sheng; Lv, Jun-Ying; Ma, Ye; Shao, Ting-Ting; Xu, Liang-De; Wang, Ying-Ying; Du, Lei; Zhang, Yun-Peng; Jiang, Wei; Li, Chun-Quan; Xiao, Yun; Li, Xia

2011-02-01

Synergistic regulations among multiple microRNAs (miRNAs) are important to understand the mechanisms of complex post-transcriptional regulations in humans. Complex diseases are affected by several miRNAs rather than a single miRNA. So, it is a challenge to identify miRNA synergism and thereby further determine miRNA functions at a system-wide level and investigate disease miRNA features in the miRNA-miRNA synergistic network from a new view. Here, we constructed a miRNA-miRNA functional synergistic network (MFSN) via co-regulating functional modules that have three features: common targets of corresponding miRNA pairs, enriched in the same gene ontology category and close proximity in the protein interaction network. Predicted miRNA synergism is validated by significantly high co-expression of functional modules and significantly negative regulation to functional modules. We found that the MFSN exhibits a scale free, small world and modular architecture. Furthermore, the topological features of disease miRNAs in the MFSN are distinct from non-disease miRNAs. They have more synergism, indicating their higher complexity of functions and are the global central cores of the MFSN. In addition, miRNAs associated with the same disease are close to each other. The structure of the MFSN and the features of disease miRNAs are validated to be robust using different miRNA target data sets.

Cognitive Network Modeling as a Basis for Characterizing Human Communication Dynamics and Belief Contagion in Technology Adoption

NASA Technical Reports Server (NTRS)

Hutto, Clayton; Briscoe, Erica; Trewhitt, Ethan

2012-01-01

Societal level macro models of social behavior do not sufficiently capture nuances needed to adequately represent the dynamics of person-to-person interactions. Likewise, individual agent level micro models have limited scalability - even minute parameter changes can drastically affect a model's response characteristics. This work presents an approach that uses agent-based modeling to represent detailed intra- and inter-personal interactions, as well as a system dynamics model to integrate societal-level influences via reciprocating functions. A Cognitive Network Model (CNM) is proposed as a method of quantitatively characterizing cognitive mechanisms at the intra-individual level. To capture the rich dynamics of interpersonal communication for the propagation of beliefs and attitudes, a Socio-Cognitive Network Model (SCNM) is presented. The SCNM uses socio-cognitive tie strength to regulate how agents influence--and are influenced by--one another's beliefs during social interactions. We then present experimental results which support the use of this network analytical approach, and we discuss its applicability towards characterizing and understanding human information processing.

CoryneRegNet: An ontology-based data warehouse of corynebacterial transcription factors and regulatory networks

PubMed Central

Baumbach, Jan; Brinkrolf, Karina; Czaja, Lisa F; Rahmann, Sven; Tauch, Andreas

2006-01-01

Background The application of DNA microarray technology in post-genomic analysis of bacterial genome sequences has allowed the generation of huge amounts of data related to regulatory networks. This data along with literature-derived knowledge on regulation of gene expression has opened the way for genome-wide reconstruction of transcriptional regulatory networks. These large-scale reconstructions can be converted into in silico models of bacterial cells that allow a systematic analysis of network behavior in response to changing environmental conditions. Description CoryneRegNet was designed to facilitate the genome-wide reconstruction of transcriptional regulatory networks of corynebacteria relevant in biotechnology and human medicine. During the import and integration process of data derived from experimental studies or literature knowledge CoryneRegNet generates links to genome annotations, to identified transcription factors and to the corresponding cis-regulatory elements. CoryneRegNet is based on a multi-layered, hierarchical and modular concept of transcriptional regulation and was implemented by using the relational database management system MySQL and an ontology-based data structure. Reconstructed regulatory networks can be visualized by using the yFiles JAVA graph library. As an application example of CoryneRegNet, we have reconstructed the global transcriptional regulation of a cellular module involved in SOS and stress response of corynebacteria. Conclusion CoryneRegNet is an ontology-based data warehouse that allows a pertinent data management of regulatory interactions along with the genome-scale reconstruction of transcriptional regulatory networks. These models can further be combined with metabolic networks to build integrated models of cellular function including both metabolism and its transcriptional regulation. PMID:16478536

Particle transport through hydrogels is charge asymmetric.

PubMed

Zhang, Xiaolu; Hansing, Johann; Netz, Roland R; DeRouchey, Jason E

2015-02-03

Transport processes within biological polymer networks, including mucus and the extracellular matrix, play an important role in the human body, where they serve as a filter for the exchange of molecules and nanoparticles. Such polymer networks are complex and heterogeneous hydrogel environments that regulate diffusive processes through finely tuned particle-network interactions. In this work, we present experimental and theoretical studies to examine the role of electrostatics on the basic mechanisms governing the diffusion of charged probe molecules inside model polymer networks. Translational diffusion coefficients are determined by fluorescence correlation spectroscopy measurements for probe molecules in uncharged as well as cationic and anionic polymer solutions. We show that particle transport in the charged hydrogels is highly asymmetric, with diffusion slowed down much more by electrostatic attraction than by repulsion, and that the filtering capability of the gel is sensitive to the solution ionic strength. Brownian dynamics simulations of a simple model are used to examine key parameters, including interaction strength and interaction range within the model networks. Simulations, which are in quantitative agreement with our experiments, reveal the charge asymmetry to be due to the sticking of particles at the vertices of the oppositely charged polymer networks. Copyright © 2015 Biophysical Society. Published by Elsevier Inc. All rights reserved.

A transcriptional dynamic network during Arabidopsis thaliana pollen development.

PubMed

Wang, Jigang; Qiu, Xiaojie; Li, Yuhua; Deng, Youping; Shi, Tieliu

2011-01-01

To understand transcriptional regulatory networks (TRNs), especially the coordinated dynamic regulation between transcription factors (TFs) and their corresponding target genes during development, computational approaches would represent significant advances in the genome-wide expression analysis. The major challenges for the experiments include monitoring the time-specific TFs' activities and identifying the dynamic regulatory relationships between TFs and their target genes, both of which are currently not yet available at the large scale. However, various methods have been proposed to computationally estimate those activities and regulations. During the past decade, significant progresses have been made towards understanding pollen development at each development stage under the molecular level, yet the regulatory mechanisms that control the dynamic pollen development processes remain largely unknown. Here, we adopt Networks Component Analysis (NCA) to identify TF activities over time course, and infer their regulatory relationships based on the coexpression of TFs and their target genes during pollen development. We carried out meta-analysis by integrating several sets of gene expression data related to Arabidopsis thaliana pollen development (stages range from UNM, BCP, TCP, HP to 0.5 hr pollen tube and 4 hr pollen tube). We constructed a regulatory network, including 19 TFs, 101 target genes and 319 regulatory interactions. The computationally estimated TF activities were well correlated to their coordinated genes' expressions during the development process. We clustered the expression of their target genes in the context of regulatory influences, and inferred new regulatory relationships between those TFs and their target genes, such as transcription factor WRKY34, which was identified that specifically expressed in pollen, and regulated several new target genes. Our finding facilitates the interpretation of the expression patterns with more biological relevancy, since the clusters corresponding to the activity of specific TF or the combination of TFs suggest the coordinated regulation of TFs to their target genes. Through integrating different resources, we constructed a dynamic regulatory network of Arabidopsis thaliana during pollen development with gene coexpression and NCA. The network illustrated the relationships between the TFs' activities and their target genes' expression, as well as the interactions between TFs, which provide new insight into the molecular mechanisms that control the pollen development.

Innate Immune Regulations and Liver Ischemia Reperfusion Injury

PubMed Central

Lu, Ling; Zhou, Haoming; Ni, Ming; Wang, Xuehao; Busuttil, Ronald; Kupiec-Weglinski, Jerzy; Zhai, Yuan

2016-01-01

Liver ischemia reperfusion activates innate immune system to drive the full development of inflammatory hepatocellular injury. Damage-associated molecular patterns (DAMPs) stimulate myeloid and dendritic cells via pattern recognition receptors (PRRs) to initiate the immune response. Complex intracellular signaling network transduces inflammatory signaling to regulate both innate immune cell activation and parenchymal cell death. Recent studies have revealed that DAMPs may trigger not only proinflammatory, but also immune regulatory responses by activating different PRRs or distinctive intracellular signaling pathways or in special cell populations. Additionally, tissue injury milieu activates PRR-independent receptors which also regulate inflammatory disease processes. Thus, the innate immune mechanism of liver IRI involves diverse molecular and cellular interactions, subjected to both endogenous and exogenous regulation in different cells. A better understanding of these complicated regulatory pathways/network is imperative for us in designing safe and effective therapeutic strategy to ameliorate liver IRI in patients. PMID:27861288

Pre-Clinical Drug Prioritization via Prognosis-Guided Genetic Interaction Networks

PubMed Central

Xiong, Jianghui; Liu, Juan; Rayner, Simon; Tian, Ze; Li, Yinghui; Chen, Shanguang

2010-01-01

The high rates of failure in oncology drug clinical trials highlight the problems of using pre-clinical data to predict the clinical effects of drugs. Patient population heterogeneity and unpredictable physiology complicate pre-clinical cancer modeling efforts. We hypothesize that gene networks associated with cancer outcome in heterogeneous patient populations could serve as a reference for identifying drug effects. Here we propose a novel in vivo genetic interaction which we call ‘synergistic outcome determination’ (SOD), a concept similar to ‘Synthetic Lethality’. SOD is defined as the synergy of a gene pair with respect to cancer patients' outcome, whose correlation with outcome is due to cooperative, rather than independent, contributions of genes. The method combines microarray gene expression data with cancer prognostic information to identify synergistic gene-gene interactions that are then used to construct interaction networks based on gene modules (a group of genes which share similar function). In this way, we identified a cluster of important epigenetically regulated gene modules. By projecting drug sensitivity-associated genes on to the cancer-specific inter-module network, we defined a perturbation index for each drug based upon its characteristic perturbation pattern on the inter-module network. Finally, by calculating this index for compounds in the NCI Standard Agent Database, we significantly discriminated successful drugs from a broad set of test compounds, and further revealed the mechanisms of drug combinations. Thus, prognosis-guided synergistic gene-gene interaction networks could serve as an efficient in silico tool for pre-clinical drug prioritization and rational design of combinatorial therapies. PMID:21085674

Reverse engineering a mouse embryonic stem cell-specific transcriptional network reveals a new modulator of neuronal differentiation.

PubMed

De Cegli, Rossella; Iacobacci, Simona; Flore, Gemma; Gambardella, Gennaro; Mao, Lei; Cutillo, Luisa; Lauria, Mario; Klose, Joachim; Illingworth, Elizabeth; Banfi, Sandro; di Bernardo, Diego

2013-01-01

Gene expression profiles can be used to infer previously unknown transcriptional regulatory interaction among thousands of genes, via systems biology 'reverse engineering' approaches. We 'reverse engineered' an embryonic stem (ES)-specific transcriptional network from 171 gene expression profiles, measured in ES cells, to identify master regulators of gene expression ('hubs'). We discovered that E130012A19Rik (E13), highly expressed in mouse ES cells as compared with differentiated cells, was a central 'hub' of the network. We demonstrated that E13 is a protein-coding gene implicated in regulating the commitment towards the different neuronal subtypes and glia cells. The overexpression and knock-down of E13 in ES cell lines, undergoing differentiation into neurons and glia cells, caused a strong up-regulation of the glutamatergic neurons marker Vglut2 and a strong down-regulation of the GABAergic neurons marker GAD65 and of the radial glia marker Blbp. We confirmed E13 expression in the cerebral cortex of adult mice and during development. By immuno-based affinity purification, we characterized protein partners of E13, involved in the Polycomb complex. Our results suggest a role of E13 in regulating the division between glutamatergic projection neurons and GABAergic interneurons and glia cells possibly by epigenetic-mediated transcriptional regulation.

Two-Component Elements Mediate Interactions between Cytokinin and Salicylic Acid in Plant Immunity

PubMed Central

Argueso, Cristiana T.; Ferreira, Fernando J.; Epple, Petra; To, Jennifer P. C.; Hutchison, Claire E.; Schaller, G. Eric; Dangl, Jeffery L.; Kieber, Joseph J.

2012-01-01

Recent studies have revealed an important role for hormones in plant immunity. We are now beginning to understand the contribution of crosstalk among different hormone signaling networks to the outcome of plant–pathogen interactions. Cytokinins are plant hormones that regulate development and responses to the environment. Cytokinin signaling involves a phosphorelay circuitry similar to two-component systems used by bacteria and fungi to perceive and react to various environmental stimuli. In this study, we asked whether cytokinin and components of cytokinin signaling contribute to plant immunity. We demonstrate that cytokinin levels in Arabidopsis are important in determining the amplitude of immune responses, ultimately influencing the outcome of plant–pathogen interactions. We show that high concentrations of cytokinin lead to increased defense responses to a virulent oomycete pathogen, through a process that is dependent on salicylic acid (SA) accumulation and activation of defense gene expression. Surprisingly, treatment with lower concentrations of cytokinin results in increased susceptibility. These functions for cytokinin in plant immunity require a host phosphorelay system and are mediated in part by type-A response regulators, which act as negative regulators of basal and pathogen-induced SA–dependent gene expression. Our results support a model in which cytokinin up-regulates plant immunity via an elevation of SA–dependent defense responses and in which SA in turn feedback-inhibits cytokinin signaling. The crosstalk between cytokinin and SA signaling networks may help plants fine-tune defense responses against pathogens. PMID:22291601

SignaLink 2 – a signaling pathway resource with multi-layered regulatory networks

PubMed Central

2013-01-01

Background Signaling networks in eukaryotes are made up of upstream and downstream subnetworks. The upstream subnetwork contains the intertwined network of signaling pathways, while the downstream regulatory part contains transcription factors and their binding sites on the DNA as well as microRNAs and their mRNA targets. Currently, most signaling and regulatory databases contain only a subsection of this network, making comprehensive analyses highly time-consuming and dependent on specific data handling expertise. The need for detailed mapping of signaling systems is also supported by the fact that several drug development failures were caused by undiscovered cross-talk or regulatory effects of drug targets. We previously created a uniformly curated signaling pathway resource, SignaLink, to facilitate the analysis of pathway cross-talks. Here, we present SignaLink 2, which significantly extends the coverage and applications of its predecessor. Description We developed a novel concept to integrate and utilize different subsections (i.e., layers) of the signaling network. The multi-layered (onion-like) database structure is made up of signaling pathways, their pathway regulators (e.g., scaffold and endocytotic proteins) and modifier enzymes (e.g., phosphatases, ubiquitin ligases), as well as transcriptional and post-transcriptional regulators of all of these components. The user-friendly website allows the interactive exploration of how each signaling protein is regulated. The customizable download page enables the analysis of any user-specified part of the signaling network. Compared to other signaling resources, distinctive features of SignaLink 2 are the following: 1) it involves experimental data not only from humans but from two invertebrate model organisms, C. elegans and D. melanogaster; 2) combines manual curation with large-scale datasets; 3) provides confidence scores for each interaction; 4) operates a customizable download page with multiple file formats (e.g., BioPAX, Cytoscape, SBML). Non-profit users can access SignaLink 2 free of charge at http://SignaLink.org. Conclusions With SignaLink 2 as a single resource, users can effectively analyze signaling pathways, scaffold proteins, modifier enzymes, transcription factors and miRNAs that are important in the regulation of signaling processes. This integrated resource allows the systems-level examination of how cross-talks and signaling flow are regulated, as well as provide data for cross-species comparisons and drug discovery analyses. PMID:23331499

SignaLink 2 - a signaling pathway resource with multi-layered regulatory networks.

PubMed

Fazekas, Dávid; Koltai, Mihály; Türei, Dénes; Módos, Dezső; Pálfy, Máté; Dúl, Zoltán; Zsákai, Lilian; Szalay-Bekő, Máté; Lenti, Katalin; Farkas, Illés J; Vellai, Tibor; Csermely, Péter; Korcsmáros, Tamás

2013-01-18

Signaling networks in eukaryotes are made up of upstream and downstream subnetworks. The upstream subnetwork contains the intertwined network of signaling pathways, while the downstream regulatory part contains transcription factors and their binding sites on the DNA as well as microRNAs and their mRNA targets. Currently, most signaling and regulatory databases contain only a subsection of this network, making comprehensive analyses highly time-consuming and dependent on specific data handling expertise. The need for detailed mapping of signaling systems is also supported by the fact that several drug development failures were caused by undiscovered cross-talk or regulatory effects of drug targets. We previously created a uniformly curated signaling pathway resource, SignaLink, to facilitate the analysis of pathway cross-talks. Here, we present SignaLink 2, which significantly extends the coverage and applications of its predecessor. We developed a novel concept to integrate and utilize different subsections (i.e., layers) of the signaling network. The multi-layered (onion-like) database structure is made up of signaling pathways, their pathway regulators (e.g., scaffold and endocytotic proteins) and modifier enzymes (e.g., phosphatases, ubiquitin ligases), as well as transcriptional and post-transcriptional regulators of all of these components. The user-friendly website allows the interactive exploration of how each signaling protein is regulated. The customizable download page enables the analysis of any user-specified part of the signaling network. Compared to other signaling resources, distinctive features of SignaLink 2 are the following: 1) it involves experimental data not only from humans but from two invertebrate model organisms, C. elegans and D. melanogaster; 2) combines manual curation with large-scale datasets; 3) provides confidence scores for each interaction; 4) operates a customizable download page with multiple file formats (e.g., BioPAX, Cytoscape, SBML). Non-profit users can access SignaLink 2 free of charge at http://SignaLink.org. With SignaLink 2 as a single resource, users can effectively analyze signaling pathways, scaffold proteins, modifier enzymes, transcription factors and miRNAs that are important in the regulation of signaling processes. This integrated resource allows the systems-level examination of how cross-talks and signaling flow are regulated, as well as provide data for cross-species comparisons and drug discovery analyses.

Genes uniquely expressed in human growth plate chondrocytes uncover a distinct regulatory network.

PubMed

Li, Bing; Balasubramanian, Karthika; Krakow, Deborah; Cohn, Daniel H

2017-12-20

Chondrogenesis is the earliest stage of skeletal development and is a highly dynamic process, integrating the activities and functions of transcription factors, cell signaling molecules and extracellular matrix proteins. The molecular mechanisms underlying chondrogenesis have been extensively studied and multiple key regulators of this process have been identified. However, a genome-wide overview of the gene regulatory network in chondrogenesis has not been achieved. In this study, employing RNA sequencing, we identified 332 protein coding genes and 34 long non-coding RNA (lncRNA) genes that are highly selectively expressed in human fetal growth plate chondrocytes. Among the protein coding genes, 32 genes were associated with 62 distinct human skeletal disorders and 153 genes were associated with skeletal defects in knockout mice, confirming their essential roles in skeletal formation. These gene products formed a comprehensive physical interaction network and participated in multiple cellular processes regulating skeletal development. The data also revealed 34 transcription factors and 11,334 distal enhancers that were uniquely active in chondrocytes, functioning as transcriptional regulators for the cartilage-selective genes. Our findings revealed a complex gene regulatory network controlling skeletal development whereby transcription factors, enhancers and lncRNAs participate in chondrogenesis by transcriptional regulation of key genes. Additionally, the cartilage-selective genes represent candidate genes for unsolved human skeletal disorders.

Protein interaction network topology uncovers melanogenesis regulatory network components within functional genomics datasets.

PubMed

Ho, Hsiang; Milenković, Tijana; Memisević, Vesna; Aruri, Jayavani; Przulj, Natasa; Ganesan, Anand K

2010-06-15

RNA-mediated interference (RNAi)-based functional genomics is a systems-level approach to identify novel genes that control biological phenotypes. Existing computational approaches can identify individual genes from RNAi datasets that regulate a given biological process. However, currently available methods cannot identify which RNAi screen "hits" are novel components of well-characterized biological pathways known to regulate the interrogated phenotype. In this study, we describe a method to identify genes from RNAi datasets that are novel components of known biological pathways. We experimentally validate our approach in the context of a recently completed RNAi screen to identify novel regulators of melanogenesis. In this study, we utilize a PPI network topology-based approach to identify targets within our RNAi dataset that may be components of known melanogenesis regulatory pathways. Our computational approach identifies a set of screen targets that cluster topologically in a human PPI network with the known pigment regulator Endothelin receptor type B (EDNRB). Validation studies reveal that these genes impact pigment production and EDNRB signaling in pigmented melanoma cells (MNT-1) and normal melanocytes. We present an approach that identifies novel components of well-characterized biological pathways from functional genomics datasets that could not have been identified by existing statistical and computational approaches.

Protein interaction network topology uncovers melanogenesis regulatory network components within functional genomics datasets

PubMed Central

2010-01-01

Background RNA-mediated interference (RNAi)-based functional genomics is a systems-level approach to identify novel genes that control biological phenotypes. Existing computational approaches can identify individual genes from RNAi datasets that regulate a given biological process. However, currently available methods cannot identify which RNAi screen "hits" are novel components of well-characterized biological pathways known to regulate the interrogated phenotype. In this study, we describe a method to identify genes from RNAi datasets that are novel components of known biological pathways. We experimentally validate our approach in the context of a recently completed RNAi screen to identify novel regulators of melanogenesis. Results In this study, we utilize a PPI network topology-based approach to identify targets within our RNAi dataset that may be components of known melanogenesis regulatory pathways. Our computational approach identifies a set of screen targets that cluster topologically in a human PPI network with the known pigment regulator Endothelin receptor type B (EDNRB). Validation studies reveal that these genes impact pigment production and EDNRB signaling in pigmented melanoma cells (MNT-1) and normal melanocytes. Conclusions We present an approach that identifies novel components of well-characterized biological pathways from functional genomics datasets that could not have been identified by existing statistical and computational approaches. PMID:20550706

Microglia recapitulate a hematopoietic master regulator network in the aging human frontal cortex

PubMed Central

Wehrspaun, Claudia C.; Haerty, Wilfried; Ponting, Chris P.

2015-01-01

Microglia form the immune system of the brain. Previous studies in cell cultures and animal models suggest altered activation states and cellular senescence in the aged brain. Instead, we analyzed 3 transcriptome data sets from the postmortem frontal cortex of 381 control individuals to show that microglia gene markers assemble into a transcriptional module in a gene coexpression network. These markers predominantly represented M1 and M1/M2b activation phenotypes. Expression of genes in this module generally declines over the adult life span. This decrease was more pronounced in microglia surface receptors for microglia and/or neuron crosstalk than in markers for activation state phenotypes. In addition to these receptors for exogenous signals, microglia are controlled by brain-expressed regulatory factors. We identified a subnetwork of transcription factors, including RUNX1, IRF8, PU.1, and TAL1, which are master regulators (MRs) for the age-dependent microglia module. The causal contributions of these MRs on the microglia module were verified using publicly available ChIP-Seq data. Interactions of these key MRs were preserved in a protein-protein interaction network. Importantly, these MRs appear to be essential for regulating microglia homeostasis in the adult human frontal cortex in addition to their crucial roles in hematopoiesis and myeloid cell-fate decisions during embryogenesis. PMID:26002684

Signed weighted gene co-expression network analysis of transcriptional regulation in murine embryonic stem cells

PubMed Central

Mason, Mike J; Fan, Guoping; Plath, Kathrin; Zhou, Qing; Horvath, Steve

2009-01-01

Background Recent work has revealed that a core group of transcription factors (TFs) regulates the key characteristics of embryonic stem (ES) cells: pluripotency and self-renewal. Current efforts focus on identifying genes that play important roles in maintaining pluripotency and self-renewal in ES cells and aim to understand the interactions among these genes. To that end, we investigated the use of unsigned and signed network analysis to identify pluripotency and differentiation related genes. Results We show that signed networks provide a better systems level understanding of the regulatory mechanisms of ES cells than unsigned networks, using two independent murine ES cell expression data sets. Specifically, using signed weighted gene co-expression network analysis (WGCNA), we found a pluripotency module and a differentiation module, which are not identified in unsigned networks. We confirmed the importance of these modules by incorporating genome-wide TF binding data for key ES cell regulators. Interestingly, we find that the pluripotency module is enriched with genes related to DNA damage repair and mitochondrial function in addition to transcriptional regulation. Using a connectivity measure of module membership, we not only identify known regulators of ES cells but also show that Mrpl15, Msh6, Nrf1, Nup133, Ppif, Rbpj, Sh3gl2, and Zfp39, among other genes, have important roles in maintaining ES cell pluripotency and self-renewal. We also report highly significant relationships between module membership and epigenetic modifications (histone modifications and promoter CpG methylation status), which are known to play a role in controlling gene expression during ES cell self-renewal and differentiation. Conclusion Our systems biologic re-analysis of gene expression, transcription factor binding, epigenetic and gene ontology data provides a novel integrative view of ES cell biology. PMID:19619308

A system view and analysis of essential hypertension.

PubMed

Botzer, Alon; Grossman, Ehud; Moult, John; Unger, Ron

2018-05-01

The goal of this study was to investigate genes associated with essential hypertension from a system perspective, making use of bioinformatic tools to gain insights that are not evident when focusing at a detail-based resolution. Using various databases (pathways, Genome Wide Association Studies, knockouts etc.), we compiled a set of about 200 genes that play a major role in hypertension and identified the interactions between them. This enabled us to create a protein-protein interaction network graph, from which we identified key elements, based on graph centrality analysis. Enriched gene regulatory elements (transcription factors and microRNAs) were extracted by motif finding techniques and knowledge-based tools. We found that the network is composed of modules associated with functions such as water retention, endothelial vasoconstriction, sympathetic activity and others. We identified the transcription factor SP1 and the two microRNAs miR27 (a and b) and miR548c-3p that seem to play a major role in regulating the network as they exert their control over several modules and are not restricted to specific functions. We also noticed that genes involved in metabolic diseases (e.g. insulin) are central to the network. We view the blood-pressure regulation mechanism as a system-of-systems, composed of several contributing subsystems and pathways rather than a single module. The system is regulated by distributed elements. Understanding this mode of action can lead to a more precise treatment and drug target discovery. Our analysis suggests that insulin plays a primary role in hypertension, highlighting the tight link between essential hypertension and diseases associated with the metabolic syndrome.

TimeXNet Web: Identifying cellular response networks from diverse omics time-course data.

PubMed

Tan, Phit Ling; López, Yosvany; Nakai, Kenta; Patil, Ashwini

2018-05-14

Condition-specific time-course omics profiles are frequently used to study cellular response to stimuli and identify associated signaling pathways. However, few online tools allow users to analyze multiple types of high-throughput time-course data. TimeXNet Web is a web server that extracts a time-dependent gene/protein response network from time-course transcriptomic, proteomic or phospho-proteomic data, and an input interaction network. It classifies the given genes/proteins into time-dependent groups based on the time of their highest activity and identifies the most probable paths connecting genes/proteins in consecutive groups. The response sub-network is enriched in activated genes/proteins and contains novel regulators that do not show any observable change in the input data. Users can view the resultant response network and analyze it for functional enrichment. TimeXNet Web supports the analysis of high-throughput data from multiple species by providing high quality, weighted protein-protein interaction networks for 12 model organisms. http://txnet.hgc.jp/. ashwini@hgc.jp. Supplementary data are available at Bioinformatics online.

Differential Occurrence of Interactions and Interaction Domains in Proteins Containing Homopolymeric Amino Acid Repeats

PubMed Central

Pelassa, Ilaria; Fiumara, Ferdinando

2015-01-01

Homopolymeric amino acids repeats (AARs), which are widespread in proteomes, have often been viewed simply as spacers between protein domains, or even as “junk” sequences with no obvious function but with a potential to cause harm upon expansion as in genetic diseases associated with polyglutamine or polyalanine expansions, including Huntington disease and cleidocranial dysplasia. A growing body of evidence indicates however that at least some AARs can form organized, functional protein structures, and can regulate protein function. In particular, certain AARs can mediate protein-protein interactions, either through homotypic AAR-AAR contacts or through heterotypic contacts with other protein domains. It is still unclear however, whether AARs may have a generalized, proteome-wide role in shaping protein-protein interaction networks. Therefore, we have undertaken here a bioinformatics screening of the human proteome and interactome in search of quantitative evidence of such a role. We first identified the sets of proteins that contain repeats of any one of the 20 amino acids, as well as control sets of proteins chosen at random in the proteome. We then analyzed the connectivity between the proteins of the AAR-containing protein sets and we compared it with that observed in the corresponding control networks. We find evidence for different degrees of connectivity in the different AAR-containing protein networks. Indeed, networks of proteins containing polyglutamine, polyglutamate, polyproline, and other AARs show significantly increased levels of connectivity, whereas networks containing polyleucine and other hydrophobic repeats show lower degrees of connectivity. Furthermore, we observed that numerous protein-protein, -nucleic acid, and -lipid interaction domains are significantly enriched in specific AAR protein groups. These findings support the notion of a generalized, combinatorial role of AARs, together with conventional protein interaction domains, in shaping the interaction networks of the human proteome, and define proteome-wide knowledge that may guide the informed biological exploration of the role of AARs in protein interactions. PMID:26734058

Arabidopsis ROP-interactive CRIB motif-containing protein 1 (RIC1) positively regulates auxin signalling and negatively regulates abscisic acid (ABA) signalling during root development.

PubMed

Choi, Yunjung; Lee, Yuree; Kim, Soo Young; Lee, Youngsook; Hwang, Jae-Ung

2013-05-01

Auxin and abscisic acid (ABA) modulate numerous aspects of plant development together, mostly in opposite directions, suggesting that extensive crosstalk occurs between the signalling pathways of the two hormones. However, little is known about the nature of this crosstalk. We demonstrate that ROP-interactive CRIB motif-containing protein 1 (RIC1) is involved in the interaction between auxin- and ABA-regulated root growth and lateral root formation. RIC1 expression is highly induced by both hormones, and expressed in the roots of young seedlings. Whereas auxin-responsive gene induction and the effect of auxin on root growth and lateral root formation were suppressed in the ric1 knockout, ABA-responsive gene induction and the effect of ABA on seed germination, root growth and lateral root formation were potentiated. Thus, RIC1 positively regulates auxin responses, but negatively regulates ABA responses. Together, our results suggest that RIC1 is a component of the intricate signalling network that underlies auxin and ABA crosstalk. © 2012 Blackwell Publishing Ltd.

An in vivo and in silico approach to study cis-antisense: a short cut to higher order response

NASA Astrophysics Data System (ADS)

Courtney, Colleen; Varanasi, Usha; Chatterjee, Anushree

2014-03-01

Antisense interactions are present in all domains of life. Typically sense, antisense RNA pairs originate from overlapping genes with convergent face to face promoters, and are speculated to be involved in gene regulation. Recent studies indicate the role of transcriptional interference (TI) in regulating expression of genes in convergent orientation. Modeling antisense, TI gene regulation mechanisms allows us to understand how organisms control gene expression. We present a modeling and experimental framework to understand convergent transcription that combines the effects of transcriptional interference and cis-antisense regulation. Our model shows that combining transcriptional interference and antisense RNA interaction adds multiple-levels of regulation which affords a highly tunable biological output, ranging from first order response to complex higher-order response. To study this system we created a library of experimental constructs with engineered TI and antisense interaction by using face-to-face inducible promoters separated by carefully tailored overlapping DNA sequences to control expression of a set of fluorescent reporter proteins. Studying this gene expression mechanism allows for an understanding of higher order behavior of gene expression networks.

Automatic reconstruction of a bacterial regulatory network using Natural Language Processing

PubMed Central

Rodríguez-Penagos, Carlos; Salgado, Heladia; Martínez-Flores, Irma; Collado-Vides, Julio

2007-01-01

Background Manual curation of biological databases, an expensive and labor-intensive process, is essential for high quality integrated data. In this paper we report the implementation of a state-of-the-art Natural Language Processing system that creates computer-readable networks of regulatory interactions directly from different collections of abstracts and full-text papers. Our major aim is to understand how automatic annotation using Text-Mining techniques can complement manual curation of biological databases. We implemented a rule-based system to generate networks from different sets of documents dealing with regulation in Escherichia coli K-12. Results Performance evaluation is based on the most comprehensive transcriptional regulation database for any organism, the manually-curated RegulonDB, 45% of which we were able to recreate automatically. From our automated analysis we were also able to find some new interactions from papers not already curated, or that were missed in the manual filtering and review of the literature. We also put forward a novel Regulatory Interaction Markup Language better suited than SBML for simultaneously representing data of interest for biologists and text miners. Conclusion Manual curation of the output of automatic processing of text is a good way to complement a more detailed review of the literature, either for validating the results of what has been already annotated, or for discovering facts and information that might have been overlooked at the triage or curation stages. PMID:17683642

An Arabidopsis gene regulatory network for secondary cell wall synthesis

DOE PAGES

Taylor-Teeples, M.; Lin, L.; de Lucas, M.; ...

2014-12-24

The plant cell wall is an important factor for determining cell shape, function and response to the environment. Secondary cell walls, such as those found in xylem, are composed of cellulose, hemicelluloses and lignin and account for the bulk of plant biomass. The coordination between transcriptional regulation of synthesis for each polymer is complex and vital to cell function. A regulatory hierarchy of developmental switches has been proposed, although the full complement of regulators remains unknown. In this paper, we present a protein–DNA network between Arabidopsis thaliana transcription factors and secondary cell wall metabolic genes with gene expression regulated bymore » a series of feed-forward loops. This model allowed us to develop and validate new hypotheses about secondary wall gene regulation under abiotic stress. Distinct stresses are able to perturb targeted genes to potentially promote functional adaptation. Finally, these interactions will serve as a foundation for understanding the regulation of a complex, integral plant component.« less

Network portal: a database for storage, analysis and visualization of biological networks

PubMed Central

Turkarslan, Serdar; Wurtmann, Elisabeth J.; Wu, Wei-Ju; Jiang, Ning; Bare, J. Christopher; Foley, Karen; Reiss, David J.; Novichkov, Pavel; Baliga, Nitin S.

2014-01-01

The ease of generating high-throughput data has enabled investigations into organismal complexity at the systems level through the inference of networks of interactions among the various cellular components (genes, RNAs, proteins and metabolites). The wider scientific community, however, currently has limited access to tools for network inference, visualization and analysis because these tasks often require advanced computational knowledge and expensive computing resources. We have designed the network portal (http://networks.systemsbiology.net) to serve as a modular database for the integration of user uploaded and public data, with inference algorithms and tools for the storage, visualization and analysis of biological networks. The portal is fully integrated into the Gaggle framework to seamlessly exchange data with desktop and web applications and to allow the user to create, save and modify workspaces, and it includes social networking capabilities for collaborative projects. While the current release of the database contains networks for 13 prokaryotic organisms from diverse phylogenetic clades (4678 co-regulated gene modules, 3466 regulators and 9291 cis-regulatory motifs), it will be rapidly populated with prokaryotic and eukaryotic organisms as relevant data become available in public repositories and through user input. The modular architecture, simple data formats and open API support community development of the portal. PMID:24271392

[Study on intersection and regulation mechanism of "efficacy-toxicity network" of aconite in combination environment of Sini decoction].

PubMed

Li, Zhi-yong; Bao, Hong-juan; Zhang, Shuo-feng; Ye, Tian-yuan; Yang, Ce; Li, Yan-wen

2015-02-01

To explore the intersection and regulation mechanism of "efficacy-toxicity network" of Glycyrrhizae Radix et Rhizoma, Zingiberis Rhizoma and Aconiti Lateralis Radix Praeparata's action gene in the combination environment of Sini decoction with the network pharmacological method. The gene interaction network of Aconiti Lateralis Radix Praeparata, Glycyrrhizae Radix et Rhizoma, Zingiberis Rhizoma were mined and established with Cytoscape software and Agilent literature search plug-in. The "efficiency-toxicity network" intersection of Aconiti Lateralis Radix Praeparata was formed according to its effects in anti-heart failure, neurotoxicity and cardiotoxicity. The target genes were clustered with Clusterviz plug-in. And the possible pathways of the "efficacy-tox- icity network" intersection of Glycyrrhizae Radix et Rhizoma, Zingiberis Rhizoma and Aconiti Lateralis Radix Praeparata were forecasted in DAVID database. There were five genes related to neurotoxicity, cardiotoxicity and anti-heart failure function of Aconiti Lateralis Radix Praeparata, namely AKT1, BAX, HCC, IL6 and IL8, which formed 47 nodes genes in the "efficiency-toxicity network" intersection of Aconiti Lateralis Radix Praeparata. There were 29 and 27 coincident genes in the "efficiency-toxicity network" of Glycyrrhizae Radix et Rhizoma, Zingiberis Rhizoma and Aconiti Lateralis Radix Praeparata. There were 23 and 17 possible regulatory pathways. In the combination environment of Sini decoction, Glycyrrhizae Radix et Rhizoma and Zingiberis Rhizoma may regulate the efficiency-toxicity network of Aconiti Lateralis Radix Praeparata by influencing immune-inflammatory signaling pathway, apoptosis-autophagy signaling pathway, nerve cell and myocardial ischemia and hypoxia protection signaling pathways.

Abnormally high expression of POLD1, MCM2, and PLK4 promotes relapse of acute lymphoblastic leukemia.

PubMed

Li, Sheng; Wang, Chengzhong; Wang, Weikai; Liu, Weidong; Zhang, Guiqin

2018-05-01

This study aimed to explore the underlying mechanism of relapsed acute lymphoblastic leukemia (ALL).Datasets of GSE28460 and GSE18497 were downloaded from Gene Expression Omnibus (GEO). Differentially expressed genes (DEGs) between diagnostic and relapsed ALL samples were identified using Limma package in R, and a Venn diagram was drawn. Next, functional enrichment analyses of co-regulated DEGs were performed. Based on the String database, protein-protein interaction network and module analyses were also conducted. Moreover, transcription factors and miRNAs targeting co-regulated DEGs were predicted using the WebGestalt online tool.A total of 71 co-regulated DEGs were identified, including 56 co-upregulated genes and 15 co-downregulated genes. Functional enrichment analyses showed that upregulated DEGs were significantly enriched in the cell cycle, and DNA replication, and repair related pathways. POLD1, MCM2, and PLK4 were hub proteins in both protein-protein interaction network and module, and might be potential targets of E2F. Additionally, POLD1 and MCM2 were found to be regulated by miR-520H via E2F1.High expression of POLD1, MCM2, and PLK4 might play positive roles in the recurrence of ALL, and could serve as potential therapeutic targets for the treatment of relapsed ALL.

EGRINs (Environmental Gene Regulatory Influence Networks) in Rice That Function in the Response to Water Deficit, High Temperature, and Agricultural Environments[OPEN

PubMed Central

Hafemeister, Christoph; Nicotra, Adrienne B.; Jagadish, S.V. Krishna; Bonneau, Richard; Purugganan, Michael

2016-01-01

Environmental gene regulatory influence networks (EGRINs) coordinate the timing and rate of gene expression in response to environmental signals. EGRINs encompass many layers of regulation, which culminate in changes in accumulated transcript levels. Here, we inferred EGRINs for the response of five tropical Asian rice (Oryza sativa) cultivars to high temperatures, water deficit, and agricultural field conditions by systematically integrating time-series transcriptome data, patterns of nucleosome-free chromatin, and the occurrence of known cis-regulatory elements. First, we identified 5447 putative target genes for 445 transcription factors (TFs) by connecting TFs with genes harboring known cis-regulatory motifs in nucleosome-free regions proximal to their transcriptional start sites. We then used network component analysis to estimate the regulatory activity for each TF based on the expression of its putative target genes. Finally, we inferred an EGRIN using the estimated transcription factor activity (TFA) as the regulator. The EGRINs include regulatory interactions between 4052 target genes regulated by 113 TFs. We resolved distinct regulatory roles for members of the heat shock factor family, including a putative regulatory connection between abiotic stress and the circadian clock. TFA estimation using network component analysis is an effective way of incorporating multiple genome-scale measurements into network inference. PMID:27655842

Evolutionarily Conserved Sequence Features Regulate the Formation of the FG Network at the Center of the Nuclear Pore Complex

PubMed Central

Peyro, M.; Soheilypour, M.; Lee, B.L.; Mofrad, M.R.K.

2015-01-01

The nuclear pore complex (NPC) is the portal for bidirectional transportation of cargos between the nucleus and the cytoplasm. While most of the structural elements of the NPC, i.e. nucleoporins (Nups), are well characterized, the exact transport mechanism is still under much debate. Many of the functional Nups are rich in phenylalanine-glycine (FG) repeats and are believed to play the key role in nucleocytoplasmic transport. We present a bioinformatics study conducted on more than a thousand FG Nups across 252 species. Our results reveal the regulatory role of polar residues and specific sequences of charged residues, named ‘like charge regions’ (LCRs), in the formation of the FG network at the center of the NPC. Positively charged LCRs prepare the environment for negatively charged cargo complexes and regulate the size of the FG network. The low number density of charged residues in these regions prevents FG domains from forming a relaxed coil structure. Our results highlight the significant role of polar interactions in FG network formation at the center of the NPC and demonstrate that the specific localization of LCRs, FG motifs, charged, and polar residues regulate the formation of the FG network at the center of the NPC. PMID:26541386

Abasy Atlas: a comprehensive inventory of systems, global network properties and systems-level elements across bacteria.

PubMed

Ibarra-Arellano, Miguel A; Campos-González, Adrián I; Treviño-Quintanilla, Luis G; Tauch, Andreas; Freyre-González, Julio A

2016-01-01

The availability of databases electronically encoding curated regulatory networks and of high-throughput technologies and methods to discover regulatory interactions provides an invaluable source of data to understand the principles underpinning the organization and evolution of these networks responsible for cellular regulation. Nevertheless, data on these sources never goes beyond the regulon level despite the fact that regulatory networks are complex hierarchical-modular structures still challenging our understanding. This brings the necessity for an inventory of systems across a large range of organisms, a key step to rendering feasible comparative systems biology approaches. In this work, we take the first step towards a global understanding of the regulatory networks organization by making a cartography of the functional architectures of diverse bacteria. Abasy ( A: cross- BA: cteria SY: stems) Atlas provides a comprehensive inventory of annotated functional systems, global network properties and systems-level elements (global regulators, modular genes shaping functional systems, basal machinery genes and intermodular genes) predicted by the natural decomposition approach for reconstructed and meta-curated regulatory networks across a large range of bacteria, including pathogenically and biotechnologically relevant organisms. The meta-curation of regulatory datasets provides the most complete and reliable set of regulatory interactions currently available, which can even be projected into subsets by considering the force or weight of evidence supporting them or the systems that they belong to. Besides, Abasy Atlas provides data enabling large-scale comparative systems biology studies aimed at understanding the common principles and particular lifestyle adaptions of systems across bacteria. Abasy Atlas contains systems and system-level elements for 50 regulatory networks comprising 78 649 regulatory interactions covering 42 bacteria in nine taxa, containing 3708 regulons and 1776 systems. All this brings together a large corpus of data that will surely inspire studies to generate hypothesis regarding the principles governing the evolution and organization of systems and the functional architectures controlling them.Database URL: http://abasy.ccg.unam.mx. © The Author(s) 2016. Published by Oxford University Press.

Protein complexes and functional modules in molecular networks

NASA Astrophysics Data System (ADS)

Spirin, Victor; Mirny, Leonid A.

2003-10-01

Proteins, nucleic acids, and small molecules form a dense network of molecular interactions in a cell. Molecules are nodes of this network, and the interactions between them are edges. The architecture of molecular networks can reveal important principles of cellular organization and function, similarly to the way that protein structure tells us about the function and organization of a protein. Computational analysis of molecular networks has been primarily concerned with node degree [Wagner, A. & Fell, D. A. (2001) Proc. R. Soc. London Ser. B 268, 1803-1810; Jeong, H., Tombor, B., Albert, R., Oltvai, Z. N. & Barabasi, A. L. (2000) Nature 407, 651-654] or degree correlation [Maslov, S. & Sneppen, K. (2002) Science 296, 910-913], and hence focused on single/two-body properties of these networks. Here, by analyzing the multibody structure of the network of protein-protein interactions, we discovered molecular modules that are densely connected within themselves but sparsely connected with the rest of the network. Comparison with experimental data and functional annotation of genes showed two types of modules: (i) protein complexes (splicing machinery, transcription factors, etc.) and (ii) dynamic functional units (signaling cascades, cell-cycle regulation, etc.). Discovered modules are highly statistically significant, as is evident from comparison with random graphs, and are robust to noise in the data. Our results provide strong support for the network modularity principle introduced by Hartwell et al. [Hartwell, L. H., Hopfield, J. J., Leibler, S. & Murray, A. W. (1999) Nature 402, C47-C52], suggesting that found modules constitute the "building blocks" of molecular networks.

An association network analysis among microeukaryotes and bacterioplankton reveals algal bloom dynamics.

PubMed

Tan, Shangjin; Zhou, Jin; Zhu, Xiaoshan; Yu, Shichen; Zhan, Wugen; Wang, Bo; Cai, Zhonghua

2015-02-01

Algal blooms are a worldwide phenomenon and the biological interactions that underlie their regulation are only just beginning to be understood. It is established that algal microorganisms associate with many other ubiquitous, oceanic organisms, but the interactions that lead to the dynamics of bloom formation are currently unknown. To address this gap, we used network approaches to investigate the association patterns among microeukaryotes and bacterioplankton in response to a natural Scrippsiella trochoidea bloom. This is the first study to apply network approaches to bloom dynamics. To this end, terminal restriction fragment (T-RF) length polymorphism analysis showed dramatic changes in community compositions of microeukaryotes and bacterioplankton over the blooming period. A variance ratio test revealed significant positive overall associations both within and between microeukaryotic and bacterioplankton communities. An association network generated from significant correlations between T-RFs revealed that S. trochoidea had few connections to other microeukaryotes and bacterioplankton and was placed on the edge. This lack of connectivity allowed for the S. trochoidea sub-network to break off from the overall network. These results allowed us to propose a conceptual model for explaining how changes in microbial associations regulate the dynamics of an algal bloom. In addition, key T-RFs were screened by principal components analysis, correlation coefficients, and network analysis. Dominant T-RFs were then identified through 18S and 16S rRNA gene clone libraries. Results showed that microeukaryotes clustered predominantly with Dinophyceae and Perkinsea while the majority of bacterioplankton identified were Alphaproteobacteria, Gammaproteobacteria, and Bacteroidetes. The ecologi-cal roles of both were discussed in the context of these findings. © 2014 Phycological Society of America.

Directed random walks and constraint programming reveal active pathways in hepatocyte growth factor signaling.

PubMed

Kittas, Aristotelis; Delobelle, Aurélien; Schmitt, Sabrina; Breuhahn, Kai; Guziolowski, Carito; Grabe, Niels

2016-01-01

An effective means to analyze mRNA expression data is to take advantage of established knowledge from pathway databases, using methods such as pathway-enrichment analyses. However, pathway databases are not case-specific and expression data could be used to infer gene-regulation patterns in the context of specific pathways. In addition, canonical pathways may not always describe the signaling mechanisms properly, because interactions can frequently occur between genes in different pathways. Relatively few methods have been proposed to date for generating and analyzing such networks, preserving the causality between gene interactions and reasoning over the qualitative logic of regulatory effects. We present an algorithm (MCWalk) integrated with a logic programming approach, to discover subgraphs in large-scale signaling networks by random walks in a fully automated pipeline. As an exemplary application, we uncover the signal transduction mechanisms in a gene interaction network describing hepatocyte growth factor-stimulated cell migration and proliferation from gene-expression measured with microarray and RT-qPCR using in-house perturbation experiments in a keratinocyte-fibroblast co-culture. The resulting subgraphs illustrate possible associations of hepatocyte growth factor receptor c-Met nodes, differentially expressed genes and cellular states. Using perturbation experiments and Answer Set programming, we are able to select those which are more consistent with the experimental data. We discover key regulator nodes by measuring the frequency with which they are traversed when connecting signaling between receptors and significantly regulated genes and predict their expression-shift consistently with the measured data. The Java implementation of MCWalk is publicly available under the MIT license at: https://bitbucket.org/akittas/biosubg. © 2015 FEBS.

Porcine Tissue-Specific Regulatory Networks Derived from Meta-Analysis of the Transcriptome

PubMed Central

Pérez-Montarelo, Dafne; Hudson, Nicholas J.; Fernández, Ana I.; Ramayo-Caldas, Yuliaxis; Dalrymple, Brian P.; Reverter, Antonio

2012-01-01

The processes that drive tissue identity and differentiation remain unclear for most tissue types. So are the gene networks and transcription factors (TF) responsible for the differential structure and function of each particular tissue, and this is particularly true for non model species with incomplete genomic resources. To better understand the regulation of genes responsible for tissue identity in pigs, we have inferred regulatory networks from a meta-analysis of 20 gene expression studies spanning 480 Porcine Affymetrix chips for 134 experimental conditions on 27 distinct tissues. We developed a mixed-model normalization approach with a covariance structure that accommodated the disparity in the origin of the individual studies, and obtained the normalized expression of 12,320 genes across the 27 tissues. Using this resource, we constructed a network, based on the co-expression patterns of 1,072 TF and 1,232 tissue specific genes. The resulting network is consistent with the known biology of tissue development. Within the network, genes clustered by tissue and tissues clustered by site of embryonic origin. These clusters were significantly enriched for genes annotated in key relevant biological processes and confirm gene functions and interactions from the literature. We implemented a Regulatory Impact Factor (RIF) metric to identify the key regulators in skeletal muscle and tissues from the central nervous systems. The normalization of the meta-analysis, the inference of the gene co-expression network and the RIF metric, operated synergistically towards a successful search for tissue-specific regulators. Novel among these findings are evidence suggesting a novel key role of ERCC3 as a muscle regulator. Together, our results recapitulate the known biology behind tissue specificity and provide new valuable insights in a less studied but valuable model species. PMID:23049964

A microRNA-mRNA expression network during oral siphon regeneration in Ciona.

PubMed

Spina, Elijah J; Guzman, Elmer; Zhou, Hongjun; Kosik, Kenneth S; Smith, William C

2017-05-15

Here we present a parallel study of mRNA and microRNA expression during oral siphon (OS) regeneration in Ciona robusta , and the derived network of their interactions. In the process of identifying 248 mRNAs and 15 microRNAs as differentially expressed, we also identified 57 novel microRNAs, several of which are among the most highly differentially expressed. Analysis of functional categories identified enriched transcripts related to stress responses and apoptosis at the wound healing stage, signaling pathways including Wnt and TGFβ during early regrowth, and negative regulation of extracellular proteases in late stage regeneration. Consistent with the expression results, we found that inhibition of TGFβ signaling blocked OS regeneration. A correlation network was subsequently inferred for all predicted microRNA-mRNA target pairs expressed during regeneration. Network-based clustering associated transcripts into 22 non-overlapping groups, the functional analysis of which showed enrichment of stress response, signaling pathway and extracellular protease categories that could be related to specific microRNAs. Predicted targets of the miR-9 cluster suggest a role in regulating differentiation and the proliferative state of neural progenitors through regulation of the cytoskeleton and cell cycle. © 2017. Published by The Company of Biologists Ltd.

A microRNA-mRNA expression network during oral siphon regeneration in Ciona

PubMed Central

Spina, Elijah J.; Guzman, Elmer; Zhou, Hongjun; Kosik, Kenneth S.

2017-01-01

Here we present a parallel study of mRNA and microRNA expression during oral siphon (OS) regeneration in Ciona robusta, and the derived network of their interactions. In the process of identifying 248 mRNAs and 15 microRNAs as differentially expressed, we also identified 57 novel microRNAs, several of which are among the most highly differentially expressed. Analysis of functional categories identified enriched transcripts related to stress responses and apoptosis at the wound healing stage, signaling pathways including Wnt and TGFβ during early regrowth, and negative regulation of extracellular proteases in late stage regeneration. Consistent with the expression results, we found that inhibition of TGFβ signaling blocked OS regeneration. A correlation network was subsequently inferred for all predicted microRNA-mRNA target pairs expressed during regeneration. Network-based clustering associated transcripts into 22 non-overlapping groups, the functional analysis of which showed enrichment of stress response, signaling pathway and extracellular protease categories that could be related to specific microRNAs. Predicted targets of the miR-9 cluster suggest a role in regulating differentiation and the proliferative state of neural progenitors through regulation of the cytoskeleton and cell cycle. PMID:28432214

Prediction of cassava protein interactome based on interolog method.

PubMed

Thanasomboon, Ratana; Kalapanulak, Saowalak; Netrphan, Supatcharee; Saithong, Treenut

2017-12-08

Cassava is a starchy root crop whose role in food security becomes more significant nowadays. Together with the industrial uses for versatile purposes, demand for cassava starch is continuously growing. However, in-depth study to uncover the mystery of cellular regulation, especially the interaction between proteins, is lacking. To reduce the knowledge gap in protein-protein interaction (PPI), genome-scale PPI network of cassava was constructed using interolog-based method (MePPI-In, available at http://bml.sbi.kmutt.ac.th/ppi ). The network was constructed from the information of seven template plants. The MePPI-In included 90,173 interactions from 7,209 proteins. At least, 39 percent of the total predictions were found with supports from gene/protein expression data, while further co-expression analysis yielded 16 highly promising PPIs. In addition, domain-domain interaction information was employed to increase reliability of the network and guide the search for more groups of promising PPIs. Moreover, the topology and functional content of MePPI-In was similar to the networks of Arabidopsis and rice. The potential contribution of MePPI-In for various applications, such as protein-complex formation and prediction of protein function, was discussed and exemplified. The insights provided by our MePPI-In would hopefully enable us to pursue precise trait improvement in cassava.

Myosin II–interacting guanine nucleotide exchange factor promotes bleb retraction via stimulating cortex reassembly at the bleb membrane

PubMed Central

Jiao, Meng; Wu, Di; Wei, Qize

2018-01-01

Blebs are involved in various biological processes such as cell migration, cytokinesis, and apoptosis. While the expansion of blebs is largely an intracellular pressure-driven process, the retraction of blebs is believed to be driven by RhoA activation that leads to the reassembly of the actomyosin cortex at the bleb membrane. However, it is still poorly understood how RhoA is activated at the bleb membrane. Here, we provide evidence demonstrating that myosin II–interacting guanine nucleotide exchange factor (MYOGEF) is implicated in bleb retraction via stimulating RhoA activation and the reassembly of an actomyosin network at the bleb membrane during bleb retraction. Interaction of MYOGEF with ezrin, a well-known regulator of bleb retraction, is required for MYOGEF localization to retracting blebs. Notably, knockout of MYOGEF or ezrin not only disrupts RhoA activation at the bleb membrane, but also interferes with nonmuscle myosin II localization and activation, as well as actin polymerization in retracting blebs. Importantly, MYOGEF knockout slows down bleb retraction. We propose that ezrin interacts with MYOGEF and recruits it to retracting blebs, where MYOGEF activates RhoA and promotes the reassembly of the cortical actomyosin network at the bleb membrane, thus contributing to the regulation of bleb retraction. PMID:29321250

Homoeolog-specific transcriptional bias in allopolyploid wheat

PubMed Central

2010-01-01

Background Interaction between parental genomes is accompanied by global changes in gene expression which, eventually, contributes to growth vigor and the broader phenotypic diversity of allopolyploid species. In order to gain a better understanding of the effects of allopolyploidization on the regulation of diverged gene networks, we performed a genome-wide analysis of homoeolog-specific gene expression in re-synthesized allohexaploid wheat created by the hybridization of a tetraploid derivative of hexaploid wheat with the diploid ancestor of the wheat D genome Ae. tauschii. Results Affymetrix wheat genome arrays were used for both the discovery of divergent homoeolog-specific mutations and analysis of homoeolog-specific gene expression in re-synthesized allohexaploid wheat. More than 34,000 detectable parent-specific features (PSF) distributed across the wheat genome were used to assess AB genome (could not differentiate A and B genome contributions) and D genome parental expression in the allopolyploid transcriptome. In re-synthesized polyploid 81% of PSFs detected mid-parent levels of gene expression, and only 19% of PSFs showed the evidence of non-additive expression. Non-additive expression in both AB and D genomes was strongly biased toward up-regulation of parental type of gene expression with only 6% and 11% of genes, respectively, being down-regulated. Of all the non-additive gene expression, 84% can be explained by differences in the parental genotypes used to make the allopolyploid. Homoeolog-specific co-regulation of several functional gene categories was found, particularly genes involved in photosynthesis and protein biosynthesis in wheat. Conclusions Here, we have demonstrated that the establishment of interactions between the diverged regulatory networks in allopolyploids is accompanied by massive homoeolog-specific up- and down-regulation of gene expression. This study provides insights into interactions between homoeologous genomes and their role in growth vigor, development, and fertility of allopolyploid species. PMID:20849627

A protein interaction map for cell polarity development

PubMed Central

Drees, Becky L.; Sundin, Bryan; Brazeau, Elizabeth; Caviston, Juliane P.; Chen, Guang-Chao; Guo, Wei; Kozminski, Keith G.; Lau, Michelle W.; Moskow, John J.; Tong, Amy; Schenkman, Laura R.; McKenzie, Amos; Brennwald, Patrick; Longtine, Mark; Bi, Erfei; Chan, Clarence; Novick, Peter; Boone, Charles; Pringle, John R.; Davis, Trisha N.; Fields, Stanley; Drubin, David G.

2001-01-01

Many genes required for cell polarity development in budding yeast have been identified and arranged into a functional hierarchy. Core elements of the hierarchy are widely conserved, underlying cell polarity development in diverse eukaryotes. To enumerate more fully the protein–protein interactions that mediate cell polarity development, and to uncover novel mechanisms that coordinate the numerous events involved, we carried out a large-scale two-hybrid experiment. 68 Gal4 DNA binding domain fusions of yeast proteins associated with the actin cytoskeleton, septins, the secretory apparatus, and Rho-type GTPases were used to screen an array of yeast transformants that express ∼90% of the predicted Saccharomyces cerevisiae open reading frames as Gal4 activation domain fusions. 191 protein–protein interactions were detected, of which 128 had not been described previously. 44 interactions implicated 20 previously uncharacterized proteins in cell polarity development. Further insights into possible roles of 13 of these proteins were revealed by their multiple two-hybrid interactions and by subcellular localization. Included in the interaction network were associations of Cdc42 and Rho1 pathways with proteins involved in exocytosis, septin organization, actin assembly, microtubule organization, autophagy, cytokinesis, and cell wall synthesis. Other interactions suggested direct connections between Rho1- and Cdc42-regulated pathways; the secretory apparatus and regulators of polarity establishment; actin assembly and the morphogenesis checkpoint; and the exocytic and endocytic machinery. In total, a network of interactions that provide an integrated response of signaling proteins, the cytoskeleton, and organelles to the spatial cues that direct polarity development was revealed. PMID:11489916

Incorporating time-delays in S-System model for reverse engineering genetic networks.

PubMed

Chowdhury, Ahsan Raja; Chetty, Madhu; Vinh, Nguyen Xuan

2013-06-18

In any gene regulatory network (GRN), the complex interactions occurring amongst transcription factors and target genes can be either instantaneous or time-delayed. However, many existing modeling approaches currently applied for inferring GRNs are unable to represent both these interactions simultaneously. As a result, all these approaches cannot detect important interactions of the other type. S-System model, a differential equation based approach which has been increasingly applied for modeling GRNs, also suffers from this limitation. In fact, all S-System based existing modeling approaches have been designed to capture only instantaneous interactions, and are unable to infer time-delayed interactions. In this paper, we propose a novel Time-Delayed S-System (TDSS) model which uses a set of delay differential equations to represent the system dynamics. The ability to incorporate time-delay parameters in the proposed S-System model enables simultaneous modeling of both instantaneous and time-delayed interactions. Furthermore, the delay parameters are not limited to just positive integer values (corresponding to time stamps in the data), but can also take fractional values. Moreover, we also propose a new criterion for model evaluation exploiting the sparse and scale-free nature of GRNs to effectively narrow down the search space, which not only reduces the computation time significantly but also improves model accuracy. The evaluation criterion systematically adapts the max-min in-degrees and also systematically balances the effect of network accuracy and complexity during optimization. The four well-known performance measures applied to the experimental studies on synthetic networks with various time-delayed regulations clearly demonstrate that the proposed method can capture both instantaneous and delayed interactions correctly with high precision. The experiments carried out on two well-known real-life networks, namely IRMA and SOS DNA repair network in Escherichia coli show a significant improvement compared with other state-of-the-art approaches for GRN modeling.

Fiber Optics: Deregulate and Deploy.

ERIC Educational Resources Information Center

Suwinski, Jan H.

1993-01-01

Describes fiber optic technology, explains its use in education and commercial settings, and recommends regulations and legislation that will speed its use to create broadband information networks. Topics discussed include distance learning; interactive video; costs; and the roles of policy makers, lawmakers, public advocacy groups, and consumers.…

Construction of phosphorylation interaction networks by text mining of full-length articles using the eFIP system.

PubMed

Tudor, Catalina O; Ross, Karen E; Li, Gang; Vijay-Shanker, K; Wu, Cathy H; Arighi, Cecilia N

2015-01-01

Protein phosphorylation is a reversible post-translational modification where a protein kinase adds a phosphate group to a protein, potentially regulating its function, localization and/or activity. Phosphorylation can affect protein-protein interactions (PPIs), abolishing interaction with previous binding partners or enabling new interactions. Extracting phosphorylation information coupled with PPI information from the scientific literature will facilitate the creation of phosphorylation interaction networks of kinases, substrates and interacting partners, toward knowledge discovery of functional outcomes of protein phosphorylation. Increasingly, PPI databases are interested in capturing the phosphorylation state of interacting partners. We have previously developed the eFIP (Extracting Functional Impact of Phosphorylation) text mining system, which identifies phosphorylated proteins and phosphorylation-dependent PPIs. In this work, we present several enhancements for the eFIP system: (i) text mining for full-length articles from the PubMed Central open-access collection; (ii) the integration of the RLIMS-P 2.0 system for the extraction of phosphorylation events with kinase, substrate and site information; (iii) the extension of the PPI module with new trigger words/phrases describing interactions and (iv) the addition of the iSimp tool for sentence simplification to aid in the matching of syntactic patterns. We enhance the website functionality to: (i) support searches based on protein roles (kinases, substrates, interacting partners) or using keywords; (ii) link protein entities to their corresponding UniProt identifiers if mapped and (iii) support visual exploration of phosphorylation interaction networks using Cytoscape. The evaluation of eFIP on full-length articles achieved 92.4% precision, 76.5% recall and 83.7% F-measure on 100 article sections. To demonstrate eFIP for knowledge extraction and discovery, we constructed phosphorylation-dependent interaction networks involving 14-3-3 proteins identified from cancer-related versus diabetes-related articles. Comparison of the phosphorylation interaction network of kinases, phosphoproteins and interactants obtained from eFIP searches, along with enrichment analysis of the protein set, revealed several shared interactions, highlighting common pathways discussed in the context of both diseases. © The Author(s) 2015. Published by Oxford University Press.

A comprehensive map of the mTOR signaling network

PubMed Central

Caron, Etienne; Ghosh, Samik; Matsuoka, Yukiko; Ashton-Beaucage, Dariel; Therrien, Marc; Lemieux, Sébastien; Perreault, Claude; Roux, Philippe P; Kitano, Hiroaki

2010-01-01

The mammalian target of rapamycin (mTOR) is a central regulator of cell growth and proliferation. mTOR signaling is frequently dysregulated in oncogenic cells, and thus an attractive target for anticancer therapy. Using CellDesigner, a modeling support software for graphical notation, we present herein a comprehensive map of the mTOR signaling network, which includes 964 species connected by 777 reactions. The map complies with both the systems biology markup language (SBML) and graphical notation (SBGN) for computational analysis and graphical representation, respectively. As captured in the mTOR map, we review and discuss our current understanding of the mTOR signaling network and highlight the impact of mTOR feedback and crosstalk regulations on drug-based cancer therapy. This map is available on the Payao platform, a Web 2.0 based community-wide interactive process for creating more accurate and information-rich databases. Thus, this comprehensive map of the mTOR network will serve as a tool to facilitate systems-level study of up-to-date mTOR network components and signaling events toward the discovery of novel regulatory processes and therapeutic strategies for cancer. PMID:21179025

Multistability in the lactose utilization network of Escherichia coli

NASA Astrophysics Data System (ADS)

Ozbudak, Ertugrul M.; Thattai, Mukund; Lim, Han N.; Shraiman, Boris I.; van Oudenaarden, Alexander

2004-02-01

Multistability, the capacity to achieve multiple internal states in response to a single set of external inputs, is the defining characteristic of a switch. Biological switches are essential for the determination of cell fate in multicellular organisms, the regulation of cell-cycle oscillations during mitosis and the maintenance of epigenetic traits in microbes. The multistability of several natural and synthetic systems has been attributed to positive feedback loops in their regulatory networks. However, feedback alone does not guarantee multistability. The phase diagram of a multistable system, a concise description of internal states as key parameters are varied, reveals the conditions required to produce a functional switch. Here we present the phase diagram of the bistable lactose utilization network of Escherichia coli. We use this phase diagram, coupled with a mathematical model of the network, to quantitatively investigate processes such as sugar uptake and transcriptional regulation in vivo. We then show how the hysteretic response of the wild-type system can be converted to an ultrasensitive graded response. The phase diagram thus serves as a sensitive probe of molecular interactions and as a powerful tool for rational network design.

Phosphorylation status determines the opposing functions of Smad2/Smad3 as STAT3 cofactors in TH17 differentiation

PubMed Central

Yoon, Jeong-Hwan; Sudo, Katsuko; Kuroda, Masahiko; Kato, Mitsuyasu; Lee, In-Kyu; Han, Jin Soo; Nakae, Susumu; Imamura, Takeshi; Kim, Juryun; Ju, Ji Hyeon; Kim, Dae-Kee; Matsuzaki, Koichi; Weinstein, Michael; Matsumoto, Isao; Sumida, Takayuki; Mamura, Mizuko

2015-01-01

Transforming growth factor-β (TGF-β) and interleukin-6 (IL-6) are the pivotal cytokines to induce IL-17-producing CD4+ T helper cells (TH17); yet their signalling network remains largely unknown. Here we show that the highly homologous TGF-β receptor-regulated Smads (R-Smads): Smad2 and Smad3 oppositely modify STAT3-induced transcription of IL-17A and retinoic acid receptor-related orphan nuclear receptor, RORγt encoded by Rorc, by acting as a co-activator and co-repressor of STAT3, respectively. Smad2 linker phosphorylated by extracellular signal-regulated kinase (ERK) at the serine 255 residue interacts with STAT3 and p300 to transactivate, whereas carboxy-terminal unphosphorylated Smad3 interacts with STAT3 and protein inhibitor of activated STAT3 (PIAS3) to repress the Rorc and Il17a genes. Our work uncovers carboxy-terminal phosphorylation-independent noncanonical R-Smad–STAT3 signalling network in TH17 differentiation. PMID:26194464

Phosphorylation status determines the opposing functions of Smad2/Smad3 as STAT3 cofactors in TH17 differentiation.

PubMed

Yoon, Jeong-Hwan; Sudo, Katsuko; Kuroda, Masahiko; Kato, Mitsuyasu; Lee, In-Kyu; Han, Jin Soo; Nakae, Susumu; Imamura, Takeshi; Kim, Juryun; Ju, Ji Hyeon; Kim, Dae-Kee; Matsuzaki, Koichi; Weinstein, Michael; Matsumoto, Isao; Sumida, Takayuki; Mamura, Mizuko

2015-07-21

Transforming growth factor-β (TGF-β) and interleukin-6 (IL-6) are the pivotal cytokines to induce IL-17-producing CD4(+) T helper cells (TH17); yet their signalling network remains largely unknown. Here we show that the highly homologous TGF-β receptor-regulated Smads (R-Smads): Smad2 and Smad3 oppositely modify STAT3-induced transcription of IL-17A and retinoic acid receptor-related orphan nuclear receptor, RORγt encoded by Rorc, by acting as a co-activator and co-repressor of STAT3, respectively. Smad2 linker phosphorylated by extracellular signal-regulated kinase (ERK) at the serine 255 residue interacts with STAT3 and p300 to transactivate, whereas carboxy-terminal unphosphorylated Smad3 interacts with STAT3 and protein inhibitor of activated STAT3 (PIAS3) to repress the Rorc and Il17a genes. Our work uncovers carboxy-terminal phosphorylation-independent noncanonical R-Smad-STAT3 signalling network in TH17 differentiation.

Discovering Hematopoietic Mechanisms Through Genome-Wide Analysis of GATA Factor Chromatin Occupancy

PubMed Central

Fujiwara, Tohru; O'Geen, Henriette; Keles, Sunduz; Blahnik, Kimberly; Linnemann, Amelia K.; Kang, Yoon-A; Choi, Kyunghee; Farnham, Peggy J.; Bresnick, Emery H.

2009-01-01

SUMMARY GATA factors interact with simple DNA motifs (WGATAR) to regulate critical processes, including hematopoiesis, but very few WGATAR motifs are occupied in genomes. Given the rudimentary knowledge of mechanisms underlying this restriction, and how GATA factors establish genetic networks, we used ChIP-seq to define GATA-1 and GATA-2 occupancy genome-wide in erythroid cells. Coupled with genetic complementation analysis and transcriptional profiling, these studies revealed a rich collection of targets containing a characteristic binding motif of greater complexity than WGATAR. GATA factors occupied loci encoding multiple components of the Scl/TAL1 complex, a master regulator of hematopoiesis and leukemogenic target. Mechanistic analyses provided evidence for cross-regulatory and autoregulatory interactions among components of this complex, including GATA-2 induction of the hematopoietic corepressor ETO-2 and an ETO-2 negative autoregulatory loop. These results establish fundamental principles underlying GATA factor mechanisms in chromatin and illustrate a complex network of considerable importance for the control of hematopoiesis. PMID:19941826

Network integrity of the parental brain in infancy supports the development of children's social competencies.

PubMed

Abraham, Eyal; Hendler, Talma; Zagoory-Sharon, Orna; Feldman, Ruth

2016-11-01

The cross-generational transmission of mammalian sociality, initiated by the parent's postpartum brain plasticity and species-typical behavior that buttress offspring's socialization, has not been studied in humans. In this longitudinal study, we measured brain response of 45 primary-caregiving parents to their infant's stimuli, observed parent-infant interactions, and assayed parental oxytocin (OT). Intra- and inter-network connectivity were computed in three main networks of the human parental brain: core limbic, embodied simulation and mentalizing. During preschool, two key child social competencies were observed: emotion regulation and socialization. Parent's network integrity in infancy predicted preschoolers' social outcomes, with subcortical and cortical network integrity foreshadowing simple evolutionary-based regulatory tactics vs complex self-regulatory strategies and advanced socialization. Parent-infant synchrony mediated the links between connectivity of the parent's embodied simulation network and preschoolers' ability to use cognitive/executive emotion regulation strategies, highlighting the inherently dyadic nature of this network and its long-term effects on tuning young to social life. Parent's inter-network core limbic-embodied simulation connectivity predicted children's OT as moderated by parental OT. Findings challenge solipsistic neuroscience perspectives by demonstrating how the parent-offspring interface enables the brain of one human to profoundly impact long-term adaptation of another. © The Author (2016). Published by Oxford University Press.

Network integrity of the parental brain in infancy supports the development of children’s social competencies

PubMed Central

Abraham, Eyal; Hendler, Talma; Zagoory-Sharon, Orna

2016-01-01

The cross-generational transmission of mammalian sociality, initiated by the parent’s postpartum brain plasticity and species-typical behavior that buttress offspring’s socialization, has not been studied in humans. In this longitudinal study, we measured brain response of 45 primary-caregiving parents to their infant’s stimuli, observed parent–infant interactions, and assayed parental oxytocin (OT). Intra- and inter-network connectivity were computed in three main networks of the human parental brain: core limbic, embodied simulation and mentalizing. During preschool, two key child social competencies were observed: emotion regulation and socialization. Parent’s network integrity in infancy predicted preschoolers’ social outcomes, with subcortical and cortical network integrity foreshadowing simple evolutionary-based regulatory tactics vs complex self-regulatory strategies and advanced socialization. Parent–infant synchrony mediated the links between connectivity of the parent’s embodied simulation network and preschoolers' ability to use cognitive/executive emotion regulation strategies, highlighting the inherently dyadic nature of this network and its long-term effects on tuning young to social life. Parent’s inter-network core limbic-embodied simulation connectivity predicted children’s OT as moderated by parental OT. Findings challenge solipsistic neuroscience perspectives by demonstrating how the parent–offspring interface enables the brain of one human to profoundly impact long-term adaptation of another. PMID:27369068

Randomizing Genome-Scale Metabolic Networks

PubMed Central

Samal, Areejit; Martin, Olivier C.

2011-01-01

Networks coming from protein-protein interactions, transcriptional regulation, signaling, or metabolism may appear to have “unusual” properties. To quantify this, it is appropriate to randomize the network and test the hypothesis that the network is not statistically different from expected in a motivated ensemble. However, when dealing with metabolic networks, the randomization of the network using edge exchange generates fictitious reactions that are biochemically meaningless. Here we provide several natural ensembles of randomized metabolic networks. A first constraint is to use valid biochemical reactions. Further constraints correspond to imposing appropriate functional constraints. We explain how to perform these randomizations with the help of Markov Chain Monte Carlo (MCMC) and show that they allow one to approach the properties of biological metabolic networks. The implication of the present work is that the observed global structural properties of real metabolic networks are likely to be the consequence of simple biochemical and functional constraints. PMID:21779409

A Knockout Screen of ApiAP2 Genes Reveals Networks of Interacting Transcriptional Regulators Controlling the Plasmodium Life Cycle.

PubMed

Modrzynska, Katarzyna; Pfander, Claudia; Chappell, Lia; Yu, Lu; Suarez, Catherine; Dundas, Kirsten; Gomes, Ana Rita; Goulding, David; Rayner, Julian C; Choudhary, Jyoti; Billker, Oliver

2017-01-11

A family of apicomplexa-specific proteins containing AP2 DNA-binding domains (ApiAP2s) was identified in malaria parasites. This family includes sequence-specific transcription factors that are key regulators of development. However, functions for the majority of ApiAP2 genes remain unknown. Here, a systematic knockout screen in Plasmodium berghei identified ten ApiAP2 genes that were essential for mosquito transmission: four were critical for the formation of infectious ookinetes, and three were required for sporogony. We describe non-essential functions for AP2-O and AP2-SP proteins in blood stages, and identify AP2-G2 as a repressor active in both asexual and sexual stages. Comparative transcriptomics across mutants and developmental stages revealed clusters of co-regulated genes with shared cis promoter elements, whose expression can be controlled positively or negatively by different ApiAP2 factors. We propose that stage-specific interactions between ApiAP2 proteins on partly overlapping sets of target genes generate the complex transcriptional network that controls the Plasmodium life cycle. Copyright © 2017 The Author(s). Published by Elsevier Inc. All rights reserved.

Quaking and PTB control overlapping splicing regulatory networks during muscle cell differentiation

PubMed Central

Hall, Megan P.; Nagel, Roland J.; Fagg, W. Samuel; Shiue, Lily; Cline, Melissa S.; Perriman, Rhonda J.; Donohue, John Paul; Ares, Manuel

2013-01-01

Alternative splicing contributes to muscle development, but a complete set of muscle-splicing factors and their combinatorial interactions are unknown. Previous work identified ACUAA (“STAR” motif) as an enriched intron sequence near muscle-specific alternative exons such as Capzb exon 9. Mass spectrometry of myoblast proteins selected by the Capzb exon 9 intron via RNA affinity chromatography identifies Quaking (QK), a protein known to regulate mRNA function through ACUAA motifs in 3′ UTRs. We find that QK promotes inclusion of Capzb exon 9 in opposition to repression by polypyrimidine tract-binding protein (PTB). QK depletion alters inclusion of 406 cassette exons whose adjacent intron sequences are also enriched in ACUAA motifs. During differentiation of myoblasts to myotubes, QK levels increase two- to threefold, suggesting a mechanism for QK-responsive exon regulation. Combined analysis of the PTB- and QK-splicing regulatory networks during myogenesis suggests that 39% of regulated exons are under the control of one or both of these splicing factors. This work provides the first evidence that QK is a global regulator of splicing during muscle development in vertebrates and shows how overlapping splicing regulatory networks contribute to gene expression programs during differentiation. PMID:23525800

[Identification and analysis of the proteins interacted with Prestin in cochlear outer hair cells of guinea pig].

PubMed

Luo, X; Wang, J Y; Zhang, F L; Xia, Y

2018-01-07

Objective: To explore the regulation and mechanism of Prestin protein by identifying the proteins interacted with Prestin in cochlear outer hair cell(OHC) and analyzing their biological function. Methods: Co-immunoprecipitation combined mass spectrometry technology was used to isolate and identify the proteins interacted with Prestin protein of OHC, bioinformatics was used to construct Prestin protein interaction network. The proteins interacted with Prestin in OHC of guinea pig were determined by matching primary interaction mass spectrometry with protein interaction network, and annotated their functions. Results: The results of co-immunoprecipitation combined with mass spectrometry showed that 116 kinds of credible proteins could interact with Prestin. By constructing Prestin protein interaction network, matching the results of mass spectrometry and analyzing of sub-cellular localization, eight kinds of proteins were confirmed that they interacted with Prestin directly, namely EEF2, HSP90AB1, FN1, FLNA, EEF1A1, HSP90B1, ATP5A1, and ERH, respectively, which were mainly involved in the synthesis and transportation, transmembrane folding and localization, structural stability and signal transduction of Prestin protein. Conclusion: EEF2, HSP90AB1, FN1, FLNA, EEF1A1, HSP90B1, ATP5A1 and ERH provide molecular basis for sensory amplification function of OHCs by participating in biotransformation, transmembrane folding and localization, signal transduction and other biological processes of Prestin protein.

Interaction of Proteins Identified in Human Thyroid Cells

PubMed Central

Pietsch, Jessica; Riwaldt, Stefan; Bauer, Johann; Sickmann, Albert; Weber, Gerhard; Grosse, Jirka; Infanger, Manfred; Eilles, Christoph; Grimm, Daniela

2013-01-01

Influence of gravity forces on the regulation of protein expression by healthy and malignant thyroid cells was studied with the aim to identify protein interactions. Western blot analyses of a limited number of proteins suggested a time-dependent regulation of protein expression by simulated microgravity. After applying free flow isoelectric focusing and mass spectrometry to search for differently expressed proteins by thyroid cells exposed to simulated microgravity for three days, a considerable number of candidates for gravi-sensitive proteins were detected. In order to show how proteins sensitive to microgravity could directly influence other proteins, we investigated all polypeptide chains identified with Mascot scores above 100, looking for groups of interacting proteins. Hence, UniProtKB entry numbers of all detected proteins were entered into the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) and processed. The program indicated that we had detected various groups of interacting proteins in each of the three cell lines studied. The major groups of interacting proteins play a role in pathways of carbohydrate and protein metabolism, regulation of cell growth and cell membrane structuring. Analyzing these groups, networks of interaction could be established which show how a punctual influence of simulated microgravity may propagate via various members of interaction chains. PMID:23303277

Abnormalities in the structural covariance of emotion regulation networks in major depressive disorder.

PubMed

Wu, Huawang; Sun, Hui; Wang, Chao; Yu, Lin; Li, Yilan; Peng, Hongjun; Lu, Xiaobing; Hu, Qingmao; Ning, Yuping; Jiang, Tianzi; Xu, Jinping; Wang, Jiaojian

2017-01-01

Major depressive disorder (MDD) is a common psychiatric disorder that is characterized by cognitive deficits and affective symptoms. To date, an increasing number of neuroimaging studies have focused on emotion regulation and have consistently shown that emotion dysregulation is one of the central features and underlying mechanisms of MDD. Although gray matter morphological abnormalities in regions within emotion regulation networks have been identified in MDD, the interactions and relationships between these gray matter structures remain largely unknown. Thus, in this study, we adopted a structural covariance method based on gray matter volume to investigate the brain morphological abnormalities within the emotion regulation networks in a large cohort of 65 MDD patients and 65 age- and gender-matched healthy controls. A permutation test with p < 0.05 was used to identify the significant changes in covariance connectivity strengths between MDD patients and healthy controls. The structural covariance analysis revealed an increased correlation strength of gray matter volume between the left angular gyrus and the left amygdala and between the right angular gyrus and the right amygdala, as well as a decreased correlation strength of the gray matter volume between the right angular gyrus and the posterior cingulate cortex in MDD. Our findings support the notion that emotion dysregulation is an underlying mechanism of MDD by revealing disrupted structural covariance patterns in the emotion regulation network. Copyright © 2016 Elsevier Ltd. All rights reserved.

Chemical camouflage: a key process in shaping an ant-treehopper and fig-fig wasp mutualistic network.

PubMed

Wang, Bo; Lu, Min; Cook, James M; Yang, Da-Rong; Dunn, Derek W; Wang, Rui-Wu

2018-01-30

Different types of mutualisms may interact, co-evolve and form complex networks of interdependences, but how species interact in networks of a mutualistic community and maintain its stability remains unclear. In a mutualistic network between treehoppers-weaver ants and fig-pollinating wasps, we found that the cuticular hydrocarbons of the treehoppers are more similar to the surface chemical profiles of fig inflorescence branches (FIB) than the cuticular hydrocarbons of the fig wasps. Behavioral assays showed that the cuticular hydrocarbons from both treehoppers and FIBs reduce the propensity of weaver ants to attack treehoppers even in the absence of honeydew rewards, suggesting that chemical camouflage helps enforce the mutualism between weaver ants and treehoppers. High levels of weaver ant and treehopper abundances help maintain the dominance of pollinating fig wasps in the fig wasp community and also increase fig seed production, as a result of discriminative predation and disturbance by weaver ants of ovipositing non-pollinating fig wasps (NPFWs). Ants therefore help preserve this fig-pollinating wasp mutualism from over exploitation by NPFWs. Our results imply that in this mutualistic network chemical camouflage plays a decisive role in regulating the behavior of a key species and indirectly shaping the architecture of complex arthropod-plant interactions.

Investigation on Law and Economics Based on Complex Network and Time Series Analysis.

PubMed

Yang, Jian; Qu, Zhao; Chang, Hui

2015-01-01

The research focuses on the cooperative relationship and the strategy tendency among three mutually interactive parties in financing: small enterprises, commercial banks and micro-credit companies. Complex network theory and time series analysis were applied to figure out the quantitative evidence. Moreover, this paper built up a fundamental model describing the particular interaction among them through evolutionary game. Combining the results of data analysis and current situation, it is justifiable to put forward reasonable legislative recommendations for regulations on lending activities among small enterprises, commercial banks and micro-credit companies. The approach in this research provides a framework for constructing mathematical models and applying econometrics and evolutionary game in the issue of corporation financing.

Identification of common coexpression modules based on quantitative network comparison.

PubMed

Jo, Yousang; Kim, Sanghyeon; Lee, Doheon

2018-06-13

Finding common molecular interactions from different samples is essential work to understanding diseases and other biological processes. Coexpression networks and their modules directly reflect sample-specific interactions among genes. Therefore, identification of common coexpression network or modules may reveal the molecular mechanism of complex disease or the relationship between biological processes. However, there has been no quantitative network comparison method for coexpression networks and we examined previous methods for other networks that cannot be applied to coexpression network. Therefore, we aimed to propose quantitative comparison methods for coexpression networks and to find common biological mechanisms between Huntington's disease and brain aging by the new method. We proposed two similarity measures for quantitative comparison of coexpression networks. Then, we performed experiments using known coexpression networks. We showed the validity of two measures and evaluated threshold values for similar coexpression network pairs from experiments. Using these similarity measures and thresholds, we quantitatively measured the similarity between disease-specific and aging-related coexpression modules and found similar Huntington's disease-aging coexpression module pairs. We identified similar Huntington's disease-aging coexpression module pairs and found that these modules are related to brain development, cell death, and immune response. It suggests that up-regulated cell signalling related cell death and immune/ inflammation response may be the common molecular mechanisms in the pathophysiology of HD and normal brain aging in the frontal cortex.

Chromatin dynamics in plants.

PubMed

Fransz, Paul F; de Jong, J Hans

2002-12-01

Recent studies in yeast, animals and plants have provided major breakthroughs in unraveling the molecular mechanism of higher-order gene regulation. In conjunction with the DNA code, proteins that are involved in chromatin remodeling, histone modification and epigenetic imprinting form a large network of interactions that control the nuclear programming of cell identity. New insight into how chromatin conformations are regulated in plants sheds light on the relationships between chromosome function, cell differentiation and developmental patterns.

Identifying cooperative transcriptional regulations using protein–protein interactions

PubMed Central

Nagamine, Nobuyoshi; Kawada, Yuji; Sakakibara, Yasubumi

2005-01-01

Cooperative transcriptional activations among multiple transcription factors (TFs) are important to understand the mechanisms of complex transcriptional regulations in eukaryotes. Previous studies have attempted to find cooperative TFs based on gene expression data with gene expression profiles as a measure of similarity of gene regulations. In this paper, we use protein–protein interaction data to infer synergistic binding of cooperative TFs. Our fundamental idea is based on the assumption that genes contributing to a similar biological process are regulated under the same control mechanism. First, the protein–protein interaction networks are used to calculate the similarity of biological processes among genes. Second, we integrate this similarity and the chromatin immuno-precipitation data to identify cooperative TFs. Our computational experiments in yeast show that predictions made by our method have successfully identified eight pairs of cooperative TFs that have literature evidences but could not be identified by the previous method. Further, 12 new possible pairs have been inferred and we have examined the biological relevances for them. However, since a typical problem using protein–protein interaction data is that many false-positive data are contained, we propose a method combining various biological data to increase the prediction accuracy. PMID:16126847

The desmoplakin–intermediate filament linkage regulates cell mechanics

PubMed Central

Broussard, Joshua A.; Yang, Ruiguo; Huang, Changjin; Nathamgari, S. Shiva P.; Beese, Allison M.; Godsel, Lisa M.; Hegazy, Marihan H.; Lee, Sherry; Zhou, Fan; Sniadecki, Nathan J.; Green, Kathleen J.; Espinosa, Horacio D.

2017-01-01

The translation of mechanical forces into biochemical signals plays a central role in guiding normal physiological processes during tissue development and homeostasis. Interfering with this process contributes to cardiovascular disease, cancer progression, and inherited disorders. The actin-based cytoskeleton and its associated adherens junctions are well-established contributors to mechanosensing and transduction machinery; however, the role of the desmosome–intermediate filament (DSM–IF) network is poorly understood in this context. Because a force balance among different cytoskeletal systems is important to maintain normal tissue function, knowing the relative contributions of these structurally integrated systems to cell mechanics is critical. Here we modulated the interaction between DSMs and IFs using mutant forms of desmoplakin, the protein bridging these structures. Using micropillar arrays and atomic force microscopy, we demonstrate that strengthening the DSM–IF interaction increases cell–substrate and cell–cell forces and cell stiffness both in cell pairs and sheets of cells. In contrast, disrupting the interaction leads to a decrease in these forces. These alterations in cell mechanics are abrogated when the actin cytoskeleton is dismantled. These data suggest that the tissue-specific variability in DSM–IF network composition provides an opportunity to differentially regulate tissue mechanics by balancing and tuning forces among cytoskeletal systems. PMID:28495795

Reverse engineering a mouse embryonic stem cell-specific transcriptional network reveals a new modulator of neuronal differentiation

PubMed Central

De Cegli, Rossella; Iacobacci, Simona; Flore, Gemma; Gambardella, Gennaro; Mao, Lei; Cutillo, Luisa; Lauria, Mario; Klose, Joachim; Illingworth, Elizabeth; Banfi, Sandro; di Bernardo, Diego

2013-01-01

Gene expression profiles can be used to infer previously unknown transcriptional regulatory interaction among thousands of genes, via systems biology ‘reverse engineering’ approaches. We ‘reverse engineered’ an embryonic stem (ES)-specific transcriptional network from 171 gene expression profiles, measured in ES cells, to identify master regulators of gene expression (‘hubs’). We discovered that E130012A19Rik (E13), highly expressed in mouse ES cells as compared with differentiated cells, was a central ‘hub’ of the network. We demonstrated that E13 is a protein-coding gene implicated in regulating the commitment towards the different neuronal subtypes and glia cells. The overexpression and knock-down of E13 in ES cell lines, undergoing differentiation into neurons and glia cells, caused a strong up-regulation of the glutamatergic neurons marker Vglut2 and a strong down-regulation of the GABAergic neurons marker GAD65 and of the radial glia marker Blbp. We confirmed E13 expression in the cerebral cortex of adult mice and during development. By immuno-based affinity purification, we characterized protein partners of E13, involved in the Polycomb complex. Our results suggest a role of E13 in regulating the division between glutamatergic projection neurons and GABAergic interneurons and glia cells possibly by epigenetic-mediated transcriptional regulation. PMID:23180766

Accommodation of structural rearrangements in the huntingtin-interacting protein 1 coiled-coil domain

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

Wilbur, Jeremy D., E-mail: jwilbur@msg.ucsf.edu; Hwang, Peter K.; Brodsky, Frances M.

2010-03-01

Variable packing interaction related to the conformational flexibility within the huntingtin-interacting protein 1 coiled coil domain. Huntingtin-interacting protein 1 (HIP1) is an important link between the actin cytoskeleton and clathrin-mediated endocytosis machinery. HIP1 has also been implicated in the pathogenesis of Huntington’s disease. The binding of HIP1 to actin is regulated through an interaction with clathrin light chain. Clathrin light chain binds to a flexible coiled-coil domain in HIP1 and induces a compact state that is refractory to actin binding. To understand the mechanism of this conformational regulation, a high-resolution crystal structure of a stable fragment from the HIP1 coiled-coilmore » domain was determined. The flexibility of the HIP1 coiled-coil region was evident from its variation from a previously determined structure of a similar region. A hydrogen-bond network and changes in coiled-coil monomer interaction suggest that the HIP1 coiled-coil domain is uniquely suited to allow conformational flexibility.« less

Untangling complex networks: risk minimization in financial markets through accessible spin glass ground states

PubMed Central

Lisewski, Andreas Martin; Lichtarge, Olivier

2010-01-01

Recurrent international financial crises inflict significant damage to societies and stress the need for mechanisms or strategies to control risk and tamper market uncertainties. Unfortunately, the complex network of market interactions often confounds rational approaches to optimize financial risks. Here we show that investors can overcome this complexity and globally minimize risk in portfolio models for any given expected return, provided the relative margin requirement remains below a critical, empirically measurable value. In practice, for markets with centrally regulated margin requirements, a rational stabilization strategy would be keeping margins small enough. This result follows from ground states of the random field spin glass Ising model that can be calculated exactly through convex optimization when relative spin coupling is limited by the norm of the network's Laplacian matrix. In that regime, this novel approach is robust to noise in empirical data and may be also broadly relevant to complex networks with frustrated interactions that are studied throughout scientific fields. PMID:20625477

Untangling complex networks: risk minimization in financial markets through accessible spin glass ground states.

PubMed

Lisewski, Andreas Martin; Lichtarge, Olivier

2010-08-15

Recurrent international financial crises inflict significant damage to societies and stress the need for mechanisms or strategies to control risk and tamper market uncertainties. Unfortunately, the complex network of market interactions often confounds rational approaches to optimize financial risks. Here we show that investors can overcome this complexity and globally minimize risk in portfolio models for any given expected return, provided the relative margin requirement remains below a critical, empirically measurable value. In practice, for markets with centrally regulated margin requirements, a rational stabilization strategy would be keeping margins small enough. This result follows from ground states of the random field spin glass Ising model that can be calculated exactly through convex optimization when relative spin coupling is limited by the norm of the network's Laplacian matrix. In that regime, this novel approach is robust to noise in empirical data and may be also broadly relevant to complex networks with frustrated interactions that are studied throughout scientific fields.

Genome-scale reconstruction of the sigma factor network in Escherichia coli: topology and functional states

PubMed Central

2014-01-01

Background At the beginning of the transcription process, the RNA polymerase (RNAP) core enzyme requires a σ-factor to recognize the genomic location at which the process initiates. Although the crucial role of σ-factors has long been appreciated and characterized for many individual promoters, we do not yet have a genome-scale assessment of their function. Results Using multiple genome-scale measurements, we elucidated the network of σ-factor and promoter interactions in Escherichia coli. The reconstructed network includes 4,724 σ-factor-specific promoters corresponding to transcription units (TUs), representing an increase of more than 300% over what has been previously reported. The reconstructed network was used to investigate competition between alternative σ-factors (the σ70 and σ38 regulons), confirming the competition model of σ substitution and negative regulation by alternative σ-factors. Comparison with σ-factor binding in Klebsiella pneumoniae showed that transcriptional regulation of conserved genes in closely related species is unexpectedly divergent. Conclusions The reconstructed network reveals the regulatory complexity of the promoter architecture in prokaryotic genomes, and opens a path to the direct determination of the systems biology of their transcriptional regulatory networks. PMID:24461193

Engineering microbial phenotypes through rewiring of genetic networks

PubMed Central

Rodrigues, Rui T.L.; Lee, Sangjin; Haines, Matthew

2017-01-01

Abstract The ability to program cellular behaviour is a major goal of synthetic biology, with applications in health, agriculture and chemicals production. Despite efforts to build ‘orthogonal’ systems, interactions between engineered genetic circuits and the endogenous regulatory network of a host cell can have a significant impact on desired functionality. We have developed a strategy to rewire the endogenous cellular regulatory network of yeast to enhance compatibility with synthetic protein and metabolite production. We found that introducing novel connections in the cellular regulatory network enabled us to increase the production of heterologous proteins and metabolites. This strategy is demonstrated in yeast strains that show significantly enhanced heterologous protein expression and higher titers of terpenoid production. Specifically, we found that the addition of transcriptional regulation between free radical induced signalling and nitrogen regulation provided robust improvement of protein production. Assessment of rewired networks revealed the importance of key topological features such as high betweenness centrality. The generation of rewired transcriptional networks, selection for specific phenotypes, and analysis of resulting library members is a powerful tool for engineering cellular behavior and may enable improved integration of heterologous protein and metabolite pathways. PMID:28369627

Probing Molecular Mechanisms of the Hsp90 Chaperone: Biophysical Modeling Identifies Key Regulators of Functional Dynamics

PubMed Central

Dixit, Anshuman; Verkhivker, Gennady M.

2012-01-01

Deciphering functional mechanisms of the Hsp90 chaperone machinery is an important objective in cancer biology aiming to facilitate discovery of targeted anti-cancer therapies. Despite significant advances in understanding structure and function of molecular chaperones, organizing molecular principles that control the relationship between conformational diversity and functional mechanisms of the Hsp90 activity lack a sufficient quantitative characterization. We combined molecular dynamics simulations, principal component analysis, the energy landscape model and structure-functional analysis of Hsp90 regulatory interactions to systematically investigate functional dynamics of the molecular chaperone. This approach has identified a network of conserved regions common to the Hsp90 chaperones that could play a universal role in coordinating functional dynamics, principal collective motions and allosteric signaling of Hsp90. We have found that these functional motifs may be utilized by the molecular chaperone machinery to act collectively as central regulators of Hsp90 dynamics and activity, including the inter-domain communications, control of ATP hydrolysis, and protein client binding. These findings have provided support to a long-standing assertion that allosteric regulation and catalysis may have emerged via common evolutionary routes. The interaction networks regulating functional motions of Hsp90 may be determined by the inherent structural architecture of the molecular chaperone. At the same time, the thermodynamics-based “conformational selection” of functional states is likely to be activated based on the nature of the binding partner. This mechanistic model of Hsp90 dynamics and function is consistent with the notion that allosteric networks orchestrating cooperative protein motions can be formed by evolutionary conserved and sparsely connected residue clusters. Hence, allosteric signaling through a small network of distantly connected residue clusters may be a rather general functional requirement encoded across molecular chaperones. The obtained insights may be useful in guiding discovery of allosteric Hsp90 inhibitors targeting protein interfaces with co-chaperones and protein binding clients. PMID:22624053

Exploring Transcription Factors-microRNAs Co-regulation Networks in Schizophrenia.

PubMed

Xu, Yong; Yue, Weihua; Yao Shugart, Yin; Li, Sheng; Cai, Lei; Li, Qiang; Cheng, Zaohuo; Wang, Guoqiang; Zhou, Zhenhe; Jin, Chunhui; Yuan, Jianmin; Tian, Lin; Wang, Jun; Zhang, Kai; Zhang, Kerang; Liu, Sha; Song, Yuqing; Zhang, Fuquan

2016-07-01

Transcriptional factors (TFs) and microRNAs (miRNAs) have been recognized as 2 classes of principal gene regulators that may be responsible for genome coexpression changes observed in schizophrenia (SZ). This study aims to (1) identify differentially coexpressed genes (DCGs) in 3 mRNA expression microarray datasets; (2) explore potential interactions among the DCGs, and differentially expressed miRNAs identified in our dataset composed of early-onset SZ patients and healthy controls; (3) validate expression levels of some key transcripts; and (4) explore the druggability of DCGs using the curated database. We detected a differential coexpression network associated with SZ and found that 9 out of the 12 regulators were replicated in either of the 2 other datasets. Leveraging the differentially expressed miRNAs identified in our previous dataset, we constructed a miRNA-TF-gene network relevant to SZ, including an EGR1-miR-124-3p-SKIL feed-forward loop. Our real-time quantitative PCR analysis indicated the overexpression of miR-124-3p, the under expression of SKIL and EGR1 in the blood of SZ patients compared with controls, and the direction of change of miR-124-3p and SKIL mRNA levels in SZ cases were reversed after a 12-week treatment cycle. Our druggability analysis revealed that many of these genes have the potential to be drug targets. Together, our results suggest that coexpression network abnormalities driven by combinatorial and interactive action from TFs and miRNAs may contribute to the development of SZ and be relevant to the clinical treatment of the disease. © The Author 2015. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Exploring Transcription Factors-microRNAs Co-regulation Networks in Schizophrenia

PubMed Central

Xu, Yong; Yue, Weihua; Yao Shugart, Yin; Li, Sheng; Cai, Lei; Li, Qiang; Cheng, Zaohuo; Wang, Guoqiang; Zhou, Zhenhe; Jin, Chunhui; Yuan, Jianmin; Tian, Lin; Wang, Jun; Zhang, Kai; Zhang, Kerang; Liu, Sha; Song, Yuqing; Zhang, Fuquan

2016-01-01

Background: Transcriptional factors (TFs) and microRNAs (miRNAs) have been recognized as 2 classes of principal gene regulators that may be responsible for genome coexpression changes observed in schizophrenia (SZ). Methods: This study aims to (1) identify differentially coexpressed genes (DCGs) in 3 mRNA expression microarray datasets; (2) explore potential interactions among the DCGs, and differentially expressed miRNAs identified in our dataset composed of early-onset SZ patients and healthy controls; (3) validate expression levels of some key transcripts; and (4) explore the druggability of DCGs using the curated database. Results: We detected a differential coexpression network associated with SZ and found that 9 out of the 12 regulators were replicated in either of the 2 other datasets. Leveraging the differentially expressed miRNAs identified in our previous dataset, we constructed a miRNA–TF–gene network relevant to SZ, including an EGR1–miR-124-3p–SKIL feed-forward loop. Our real-time quantitative PCR analysis indicated the overexpression of miR-124-3p, the under expression of SKIL and EGR1 in the blood of SZ patients compared with controls, and the direction of change of miR-124-3p and SKIL mRNA levels in SZ cases were reversed after a 12-week treatment cycle. Our druggability analysis revealed that many of these genes have the potential to be drug targets. Conclusions: Together, our results suggest that coexpression network abnormalities driven by combinatorial and interactive action from TFs and miRNAs may contribute to the development of SZ and be relevant to the clinical treatment of the disease. PMID:26609121

Deduction and Analysis of the Interacting Stress Response Pathways of Metal/Radionuclide-reducing Bacteria

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

Zhou, Jizhong; He, Zhili

2010-02-28

Project Title: Deduction and Analysis of the Interacting Stress Response Pathways of Metal/Radionuclide-reducing Bacteria DOE Grant Number: DE-FG02-06ER64205 Principal Investigator: Jizhong (Joe) Zhou (University of Oklahoma) Key members: Zhili He, Aifen Zhou, Christopher Hemme, Joy Van Nostrand, Ye Deng, and Qichao Tu Collaborators: Terry Hazen, Judy Wall, Adam Arkin, Matthew Fields, Aindrila Mukhopadhyay, and David Stahl Summary Three major objectives have been conducted in the Zhou group at the University of Oklahoma (OU): (i) understanding of gene function, regulation, network and evolution of Desulfovibrio vugaris Hildenborough in response to environmental stresses, (ii) development of metagenomics technologies for microbial community analysis,more » and (iii) functional characterization of microbial communities with metagenomic approaches. In the past a few years, we characterized four CRP/FNR regulators, sequenced ancestor and evolved D. vulgaris strains, and functionally analyzed those mutated genes identified in salt-adapted strains. Also, a new version of GeoChip 4.0 has been developed, which also includes stress response genes (StressChip), and a random matrix theory-based conceptual framework for identifying functional molecular ecological networks has been developed with the high throughput functional gene array hybridization data as well as pyrosequencing data from 16S rRNA genes. In addition, GeoChip and sequencing technologies as well as network analysis approaches have been used to analyze microbial communities from different habitats. Those studies provide a comprehensive understanding of gene function, regulation, network, and evolution in D. vulgaris, and microbial community diversity, composition and structure as well as their linkages with environmental factors and ecosystem functioning, which has resulted in more than 60 publications.« less

Engineered 3D vascular and neuronal networks in a microfluidic platform.

PubMed

Osaki, Tatsuya; Sivathanu, Vivek; Kamm, Roger D

2018-03-26

Neurovascular coupling plays a key role in the pathogenesis of neurodegenerative disorders including motor neuron disease (MND). In vitro models provide an opportunity to understand the pathogenesis of MND, and offer the potential for drug screening. Here, we describe a new 3D microvascular and neuronal network model in a microfluidic platform to investigate interactions between these two systems. Both 3D networks were established by co-culturing human embryonic stem (ES)-derived MN spheroids and endothelial cells (ECs) in microfluidic devices. Co-culture with ECs improves neurite elongation and neuronal connectivity as measured by Ca 2+ oscillation. This improvement was regulated not only by paracrine signals such as brain-derived neurotrophic factor secreted by ECs but also through direct cell-cell interactions via the delta-notch pathway, promoting neuron differentiation and neuroprotection. Bi-directional signaling was observed in that the neural networks also affected vascular network formation under perfusion culture. This in vitro model could enable investigations of neuro-vascular coupling, essential to understanding the pathogenesis of neurodegenerative diseases including MNDs such as amyotrophic lateral sclerosis.

Metabolic Network Modeling of Microbial Interactions in Natural and Engineered Environmental Systems

PubMed Central

Perez-Garcia, Octavio; Lear, Gavin; Singhal, Naresh

2016-01-01

We review approaches to characterize metabolic interactions within microbial communities using Stoichiometric Metabolic Network (SMN) models for applications in environmental and industrial biotechnology. SMN models are computational tools used to evaluate the metabolic engineering potential of various organisms. They have successfully been applied to design and optimize the microbial production of antibiotics, alcohols and amino acids by single strains. To date however, such models have been rarely applied to analyze and control the metabolism of more complex microbial communities. This is largely attributed to the diversity of microbial community functions, metabolisms, and interactions. Here, we firstly review different types of microbial interaction and describe their relevance for natural and engineered environmental processes. Next, we provide a general description of the essential methods of the SMN modeling workflow including the steps of network reconstruction, simulation through Flux Balance Analysis (FBA), experimental data gathering, and model calibration. Then we broadly describe and compare four approaches to model microbial interactions using metabolic networks, i.e., (i) lumped networks, (ii) compartment per guild networks, (iii) bi-level optimization simulations, and (iv) dynamic-SMN methods. These approaches can be used to integrate and analyze diverse microbial physiology, ecology and molecular community data. All of them (except the lumped approach) are suitable for incorporating species abundance data but so far they have been used only to model simple communities of two to eight different species. Interactions based on substrate exchange and competition can be directly modeled using the above approaches. However, interactions based on metabolic feedbacks, such as product inhibition and synthropy require extensions to current models, incorporating gene regulation and compounding accumulation mechanisms. SMN models of microbial interactions can be used to analyze complex “omics” data and to infer and optimize metabolic processes. Thereby, SMN models are suitable to capitalize on advances in high-throughput molecular and metabolic data generation. SMN models are starting to be applied to describe microbial interactions during wastewater treatment, in-situ bioremediation, microalgae blooms methanogenic fermentation, and bioplastic production. Despite their current challenges, we envisage that SMN models have future potential for the design and development of novel growth media, biochemical pathways and synthetic microbial associations. PMID:27242701

A Multi-Method Approach for Proteomic Network Inference in 11 Human Cancers.

PubMed

Şenbabaoğlu, Yasin; Sümer, Selçuk Onur; Sánchez-Vega, Francisco; Bemis, Debra; Ciriello, Giovanni; Schultz, Nikolaus; Sander, Chris

2016-02-01

Protein expression and post-translational modification levels are tightly regulated in neoplastic cells to maintain cellular processes known as 'cancer hallmarks'. The first Pan-Cancer initiative of The Cancer Genome Atlas (TCGA) Research Network has aggregated protein expression profiles for 3,467 patient samples from 11 tumor types using the antibody based reverse phase protein array (RPPA) technology. The resultant proteomic data can be utilized to computationally infer protein-protein interaction (PPI) networks and to study the commonalities and differences across tumor types. In this study, we compare the performance of 13 established network inference methods in their capacity to retrieve the curated Pathway Commons interactions from RPPA data. We observe that no single method has the best performance in all tumor types, but a group of six methods, including diverse techniques such as correlation, mutual information, and regression, consistently rank highly among the tested methods. We utilize the high performing methods to obtain a consensus network; and identify four robust and densely connected modules that reveal biological processes as well as suggest antibody-related technical biases. Mapping the consensus network interactions to Reactome gene lists confirms the pan-cancer importance of signal transduction pathways, innate and adaptive immune signaling, cell cycle, metabolism, and DNA repair; and also suggests several biological processes that may be specific to a subset of tumor types. Our results illustrate the utility of the RPPA platform as a tool to study proteomic networks in cancer.

MicroRNA-Target Network Inference and Local Network Enrichment Analysis Identify Two microRNA Clusters with Distinct Functions in Head and Neck Squamous Cell Carcinoma

PubMed Central

Sass, Steffen; Pitea, Adriana; Unger, Kristian; Hess, Julia; Mueller, Nikola S.; Theis, Fabian J.

2015-01-01

MicroRNAs represent ~22 nt long endogenous small RNA molecules that have been experimentally shown to regulate gene expression post-transcriptionally. One main interest in miRNA research is the investigation of their functional roles, which can typically be accomplished by identification of mi-/mRNA interactions and functional annotation of target gene sets. We here present a novel method “miRlastic”, which infers miRNA-target interactions using transcriptomic data as well as prior knowledge and performs functional annotation of target genes by exploiting the local structure of the inferred network. For the network inference, we applied linear regression modeling with elastic net regularization on matched microRNA and messenger RNA expression profiling data to perform feature selection on prior knowledge from sequence-based target prediction resources. The novelty of miRlastic inference originates in predicting data-driven intra-transcriptome regulatory relationships through feature selection. With synthetic data, we showed that miRlastic outperformed commonly used methods and was suitable even for low sample sizes. To gain insight into the functional role of miRNAs and to determine joint functional properties of miRNA clusters, we introduced a local enrichment analysis procedure. The principle of this procedure lies in identifying regions of high functional similarity by evaluating the shortest paths between genes in the network. We can finally assign functional roles to the miRNAs by taking their regulatory relationships into account. We thoroughly evaluated miRlastic on a cohort of head and neck cancer (HNSCC) patients provided by The Cancer Genome Atlas. We inferred an mi-/mRNA regulatory network for human papilloma virus (HPV)-associated miRNAs in HNSCC. The resulting network best enriched for experimentally validated miRNA-target interaction, when compared to common methods. Finally, the local enrichment step identified two functional clusters of miRNAs that were predicted to mediate HPV-associated dysregulation in HNSCC. Our novel approach was able to characterize distinct pathway regulations from matched miRNA and mRNA data. An R package of miRlastic was made available through: http://icb.helmholtz-muenchen.de/mirlastic. PMID:26694379

MicroRNA-Target Network Inference and Local Network Enrichment Analysis Identify Two microRNA Clusters with Distinct Functions in Head and Neck Squamous Cell Carcinoma.

PubMed

Sass, Steffen; Pitea, Adriana; Unger, Kristian; Hess, Julia; Mueller, Nikola S; Theis, Fabian J

2015-12-18

MicroRNAs represent ~22 nt long endogenous small RNA molecules that have been experimentally shown to regulate gene expression post-transcriptionally. One main interest in miRNA research is the investigation of their functional roles, which can typically be accomplished by identification of mi-/mRNA interactions and functional annotation of target gene sets. We here present a novel method "miRlastic", which infers miRNA-target interactions using transcriptomic data as well as prior knowledge and performs functional annotation of target genes by exploiting the local structure of the inferred network. For the network inference, we applied linear regression modeling with elastic net regularization on matched microRNA and messenger RNA expression profiling data to perform feature selection on prior knowledge from sequence-based target prediction resources. The novelty of miRlastic inference originates in predicting data-driven intra-transcriptome regulatory relationships through feature selection. With synthetic data, we showed that miRlastic outperformed commonly used methods and was suitable even for low sample sizes. To gain insight into the functional role of miRNAs and to determine joint functional properties of miRNA clusters, we introduced a local enrichment analysis procedure. The principle of this procedure lies in identifying regions of high functional similarity by evaluating the shortest paths between genes in the network. We can finally assign functional roles to the miRNAs by taking their regulatory relationships into account. We thoroughly evaluated miRlastic on a cohort of head and neck cancer (HNSCC) patients provided by The Cancer Genome Atlas. We inferred an mi-/mRNA regulatory network for human papilloma virus (HPV)-associated miRNAs in HNSCC. The resulting network best enriched for experimentally validated miRNA-target interaction, when compared to common methods. Finally, the local enrichment step identified two functional clusters of miRNAs that were predicted to mediate HPV-associated dysregulation in HNSCC. Our novel approach was able to characterize distinct pathway regulations from matched miRNA and mRNA data. An R package of miRlastic was made available through: http://icb.helmholtz-muenchen.de/mirlastic.

Electricity generation and transmission planning in deregulated power markets

NASA Astrophysics Data System (ADS)

He, Yang

This dissertation addresses the long-term planning of power generation and transmission facilities in a deregulated power market. Three models with increasing complexities are developed, primarily for investment decisions in generation and transmission capacity. The models are presented in a two-stage decision context where generation and transmission capacity expansion decisions are made in the first stage, while power generation and transmission service fees are decided in the second stage. Uncertainties that exist in the second stage affect the capacity expansion decisions in the first stage. The first model assumes that the electric power market is not constrained by transmission capacity limit. The second model, which includes transmission constraints, considers the interactions between generation firms and the transmission network operator. The third model assumes that the generation and transmission sectors make capacity investment decisions separately. These models result in Nash-Cournot equilibrium among the unregulated generation firms, while the regulated transmission network operator supports the competition among generation firms. Several issues in the deregulated electric power market can be studied with these models such as market powers of generation firms and transmission network operator, uncertainties of the future market, and interactions between the generation and transmission sectors. Results deduced from the developed models include (a) regulated transmission network operator will not reserve transmission capacity to gain extra profits; instead, it will make capacity expansion decisions to support the competition in the generation sector; (b) generation firms will provide more power supplies when there is more demand; (c) in the presence of future uncertainties, the generation firms will add more generation capacity if the demand in the future power market is expected to be higher; and (d) the transmission capacity invested by the transmission network operator depends on the characteristic of the power market and the topology of the transmission network. Also, the second model, which considers interactions between generation and transmission sectors, yields higher social welfare in the electric power market, than the third model where generation firms and transmission network operator make investment decisions separately.

Understanding Regulation of Metabolism through Feasibility Analysis

PubMed Central

Nikerel, Emrah; Berkhout, Jan; Hu, Fengyuan; Teusink, Bas; Reinders, Marcel J. T.; de Ridder, Dick

2012-01-01

Understanding cellular regulation of metabolism is a major challenge in systems biology. Thus far, the main assumption was that enzyme levels are key regulators in metabolic networks. However, regulation analysis recently showed that metabolism is rarely controlled via enzyme levels only, but through non-obvious combinations of hierarchical (gene and enzyme levels) and metabolic regulation (mass action and allosteric interaction). Quantitative analyses relating changes in metabolic fluxes to changes in transcript or protein levels have revealed a remarkable lack of understanding of the regulation of these networks. We study metabolic regulation via feasibility analysis (FA). Inspired by the constraint-based approach of Flux Balance Analysis, FA incorporates a model describing kinetic interactions between molecules. We enlarge the portfolio of objectives for the cell by defining three main physiologically relevant objectives for the cell: function, robustness and temporal responsiveness. We postulate that the cell assumes one or a combination of these objectives and search for enzyme levels necessary to achieve this. We call the subspace of feasible enzyme levels the feasible enzyme space. Once this space is constructed, we can study how different objectives may (if possible) be combined, or evaluate the conditions at which the cells are faced with a trade-off among those. We apply FA to the experimental scenario of long-term carbon limited chemostat cultivation of yeast cells, studying how metabolism evolves optimally. Cells employ a mixed strategy composed of increasing enzyme levels for glucose uptake and hexokinase and decreasing levels of the remaining enzymes. This trade-off renders the cells specialized in this low-carbon flux state to compete for the available glucose and get rid of over-overcapacity. Overall, we show that FA is a powerful tool for systems biologists to study regulation of metabolism, interpret experimental data and evaluate hypotheses. PMID:22808034

Characterization of the regulatory network of BoMYB2 in controlling anthocyanin biosynthesis in purple cauliflower.

PubMed

Chiu, Li-Wei; Li, Li

2012-10-01

Purple cauliflower (Brassica oleracea L. var. botrytis) Graffiti represents a unique mutant in conferring ectopic anthocyanin biosynthesis, which is caused by the tissue-specific activation of BoMYB2, an ortholog of Arabidopsis PAP2 or MYB113. To gain a better understanding of the regulatory network of anthocyanin biosynthesis, we investigated the interaction among cauliflower MYB-bHLH-WD40 network proteins and examined the interplay of BoMYB2 with various bHLH transcription factors in planta. Yeast two-hybrid studies revealed that cauliflower BoMYBs along with the other regulators formed the MYB-bHLH-WD40 complexes and BobHLH1 acted as a bridge between BoMYB and BoWD40-1 proteins. Different BoMYBs exhibited different binding activity to BobHLH1. Examination of the BoMYB2 transgenic lines in Arabidopsis bHLH mutant backgrounds demonstrated that TT8, EGL3, and GL3 were all involved in the BoMYB2-mediated anthocyanin biosynthesis. Expression of BoMYB2 in Arabidopsis caused up-regulation of AtTT8 and AtEGL3 as well as a subset of anthocyanin structural genes encoding flavonoid 3'-hydroxylase, dihydroflavonol 4-reductase, and leucoanthocyanidin dioxygenase. Taken together, our results show that MYB-bHLH-WD40 network transcription factors regulated the bHLH gene expression, which may represent a critical feature in the control of anthocyanin biosynthesis. BoMYB2 together with various BobHLHs specifically regulated the late anthocyanin biosynthetic pathway genes for anthocyanin biosynthesis. Our findings provide additional information for the complicated regulatory network of anthocyanin biosynthesis and the transcriptional regulation of transcription factors in vegetable crops.

Stability of Control Networks in Autonomous Homeostatic Regulation of Stem Cell Lineages.

PubMed

Komarova, Natalia L; van den Driessche, P

2018-05-01

Design principles of biological networks have been studied extensively in the context of protein-protein interaction networks, metabolic networks, and regulatory (transcriptional) networks. Here we consider regulation networks that occur on larger scales, namely the cell-to-cell signaling networks that connect groups of cells in multicellular organisms. These are the feedback loops that orchestrate the complex dynamics of cell fate decisions and are necessary for the maintenance of homeostasis in stem cell lineages. We focus on "minimal" networks that are those that have the smallest possible numbers of controls. For such minimal networks, the number of controls must be equal to the number of compartments, and the reducibility/irreducibility of the network (whether or not it can be split into smaller independent sub-networks) is defined by a matrix comprised of the cell number increments induced by each of the controlled processes in each of the compartments. Using the formalism of digraphs, we show that in two-compartment lineages, reducible systems must contain two 1-cycles, and irreducible systems one 1-cycle and one 2-cycle; stability follows from the signs of the controls and does not require magnitude restrictions. In three-compartment systems, irreducible digraphs have a tree structure or have one 3-cycle and at least two more shorter cycles, at least one of which is a 1-cycle. With further work and proper biological validation, our results may serve as a first step toward an understanding of ways in which these networks become dysregulated in cancer.

A Combined Computational and Genetic Approach Uncovers Network Interactions of the Cyanobacterial Circadian Clock.

PubMed

Boyd, Joseph S; Cheng, Ryan R; Paddock, Mark L; Sancar, Cigdem; Morcos, Faruck; Golden, Susan S

2016-09-15

Two-component systems (TCS) that employ histidine kinases (HK) and response regulators (RR) are critical mediators of cellular signaling in bacteria. In the model cyanobacterium Synechococcus elongatus PCC 7942, TCSs control global rhythms of transcription that reflect an integration of time information from the circadian clock with a variety of cellular and environmental inputs. The HK CikA and the SasA/RpaA TCS transduce time information from the circadian oscillator to modulate downstream cellular processes. Despite immense progress in understanding of the circadian clock itself, many of the connections between the clock and other cellular signaling systems have remained enigmatic. To narrow the search for additional TCS components that connect to the clock, we utilized direct-coupling analysis (DCA), a statistical analysis of covariant residues among related amino acid sequences, to infer coevolution of new and known clock TCS components. DCA revealed a high degree of interaction specificity between SasA and CikA with RpaA, as expected, but also with the phosphate-responsive response regulator SphR. Coevolutionary analysis also predicted strong specificity between RpaA and a previously undescribed kinase, HK0480 (herein CikB). A knockout of the gene for CikB (cikB) in a sasA cikA null background eliminated the RpaA phosphorylation and RpaA-controlled transcription that is otherwise present in that background and suppressed cell elongation, supporting the notion that CikB is an interactor with RpaA and the clock network. This study demonstrates the power of DCA to identify subnetworks and key interactions in signaling pathways and of combinatorial mutagenesis to explore the phenotypic consequences. Such a combined strategy is broadly applicable to other prokaryotic systems. Signaling networks are complex and extensive, comprising multiple integrated pathways that respond to cellular and environmental cues. A TCS interaction model, based on DCA, independently confirmed known interactions and revealed a core set of subnetworks within the larger HK-RR set. We validated high-scoring candidate proteins via combinatorial genetics, demonstrating that DCA can be utilized to reduce the search space of complex protein networks and to infer undiscovered specific interactions for signaling proteins in vivo Significantly, new interactions that link circadian response to cell division and fitness in a light/dark cycle were uncovered. The combined analysis also uncovered a more basic core clock, illustrating the synergy and applicability of a combined computational and genetic approach for investigating prokaryotic signaling networks. Copyright © 2016, American Society for Microbiology. All Rights Reserved.

Systematic identification of an integrative network module during senescence from time-series gene expression.

PubMed

Park, Chihyun; Yun, So Jeong; Ryu, Sung Jin; Lee, Soyoung; Lee, Young-Sam; Yoon, Youngmi; Park, Sang Chul

2017-03-15

Cellular senescence irreversibly arrests growth of human diploid cells. In addition, recent studies have indicated that senescence is a multi-step evolving process related to important complex biological processes. Most studies analyzed only the genes and their functions representing each senescence phase without considering gene-level interactions and continuously perturbed genes. It is necessary to reveal the genotypic mechanism inferred by affected genes and their interaction underlying the senescence process. We suggested a novel computational approach to identify an integrative network which profiles an underlying genotypic signature from time-series gene expression data. The relatively perturbed genes were selected for each time point based on the proposed scoring measure denominated as perturbation scores. Then, the selected genes were integrated with protein-protein interactions to construct time point specific network. From these constructed networks, the conserved edges across time point were extracted for the common network and statistical test was performed to demonstrate that the network could explain the phenotypic alteration. As a result, it was confirmed that the difference of average perturbation scores of common networks at both two time points could explain the phenotypic alteration. We also performed functional enrichment on the common network and identified high association with phenotypic alteration. Remarkably, we observed that the identified cell cycle specific common network played an important role in replicative senescence as a key regulator. Heretofore, the network analysis from time series gene expression data has been focused on what topological structure was changed over time point. Conversely, we focused on the conserved structure but its context was changed in course of time and showed it was available to explain the phenotypic changes. We expect that the proposed method will help to elucidate the biological mechanism unrevealed by the existing approaches.

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

PubMed Central

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

2016-01-01

Background Atypical synapse development and plasticity are implicated in many neurodevelopmental disorders (NDDs). NDD-associated, high confidence risk genes have been identified, yet little is known about functional relationships at the level of protein-protein interactions, which are the dominant molecular bases responsible for mediating circuit development. Methods Proteomics in three independent developing neocortical synaptosomal preparations identified putative interacting proteins of the ligand-activated MET receptor tyrosine kinase, an autism risk gene that mediates synapse development. The candidates were translated into interactome networks and analyzed bioinformatically. Additionally, three independent quantitative proximity ligation assays (PLA) in cultured neurons and four independent immunoprecipitation analyses of synaptosomes validated protein interactions. Results Approximately 11% (8/72) of MET-interacting proteins, including SHANK3, SYNGAP1 and GRIN2B, are associated with NDDs. Proteins in the MET interactome were translated into a novel MET interactome network based on human protein-protein interaction databases. High confidence genes from different NDD datasets that encode synaptosomal proteins were analyzed for being enriched in MET interactome proteins. This was found for autism, but not schizophrenia, bipolar disorder, major depressive disorder or attentional deficit hyperactivity disorder. There is correlated gene expression between MET and its interactive partners in developing human temporal and visual neocortices, but not with highly expressed genes that are not in the interactome. PLA and biochemical analyses demonstrate that MET-protein partner interactions are dynamically regulated by receptor activation. Conclusions The results provide a novel molecular framework for deciphering the functional relations of key regulators of synaptogenesis that contribute to both typical cortical development and to NDDs. PMID:27086544

Identification of a molecular recognition feature in the E1A oncoprotein that binds the SUMO conjugase UBC9 and likely interferes with polySUMOylation.

PubMed

Yousef, A F; Fonseca, G J; Pelka, P; Ablack, J N G; Walsh, C; Dick, F A; Bazett-Jones, D P; Shaw, G S; Mymryk, J S

2010-08-19

Hub proteins have central roles in regulating cellular processes. By targeting a single cellular hub, a viral oncogene may gain control over an entire module in the cellular interaction network that is potentially comprised of hundreds of proteins. The adenovirus E1A oncoprotein is a viral hub that interacts with many cellular hub proteins by short linear motifs/molecular recognition features (MoRFs). These interactions transform the architecture of the cellular protein interaction network and virtually reprogram the cell. To identify additional MoRFs within E1A, we screened portions of E1A for their ability to activate yeast pseudohyphal growth or differentiation. This identified a novel functional region within E1A conserved region 2 comprised of the sequence EVIDLT. This MoRF is necessary and sufficient to bind the N-terminal region of the SUMO conjugase UBC9, which also interacts with SUMO noncovalently and is involved in polySUMOylation. Our results suggest that E1A interferes with polySUMOylation, but not with monoSUMOylation. These data provide the first insight into the consequences of the interaction of E1A with UBC9, which was initially described in 1996. We further demonstrate that polySUMOylation regulates pseudohyphal growth and promyelocytic leukemia body reorganization by E1A. In conclusion, the interaction of the E1A oncogene with UBC9 mimics the normal binding between SUMO and UBC9 and represents a novel mechanism to modulate polySUMOylation.

An Integrated Systems Biology Approach Identifies TRIM25 as a Key Determinant of Breast Cancer Metastasis.

PubMed

Walsh, Logan A; Alvarez, Mariano J; Sabio, Erich Y; Reyngold, Marsha; Makarov, Vladimir; Mukherjee, Suranjit; Lee, Ken-Wing; Desrichard, Alexis; Turcan, Şevin; Dalin, Martin G; Rajasekhar, Vinagolu K; Chen, Shuibing; Vahdat, Linda T; Califano, Andrea; Chan, Timothy A

2017-08-15

At the root of most fatal malignancies are aberrantly activated transcriptional networks that drive metastatic dissemination. Although individual metastasis-associated genes have been described, the complex regulatory networks presiding over the initiation and maintenance of metastatic tumors are still poorly understood. There is untapped value in identifying therapeutic targets that broadly govern coordinated transcriptional modules dictating metastatic progression. Here, we reverse engineered and interrogated a breast cancer-specific transcriptional interaction network (interactome) to define transcriptional control structures causally responsible for regulating genetic programs underlying breast cancer metastasis in individual patients. Our analyses confirmed established pro-metastatic transcription factors, and they uncovered TRIM25 as a key regulator of metastasis-related transcriptional programs. Further, in vivo analyses established TRIM25 as a potent regulator of metastatic disease and poor survival outcome. Our findings suggest that identifying and targeting keystone proteins, like TRIM25, can effectively collapse transcriptional hierarchies necessary for metastasis formation, thus representing an innovative cancer intervention strategy. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Accommodation of structural rearrangements in the huntingtin-interacting protein 1 coiled-coil domain.

PubMed

Wilbur, Jeremy D; Hwang, Peter K; Brodsky, Frances M; Fletterick, Robert J

2010-03-01

Huntingtin-interacting protein 1 (HIP1) is an important link between the actin cytoskeleton and clathrin-mediated endocytosis machinery. HIP1 has also been implicated in the pathogenesis of Huntington's disease. The binding of HIP1 to actin is regulated through an interaction with clathrin light chain. Clathrin light chain binds to a flexible coiled-coil domain in HIP1 and induces a compact state that is refractory to actin binding. To understand the mechanism of this conformational regulation, a high-resolution crystal structure of a stable fragment from the HIP1 coiled-coil domain was determined. The flexibility of the HIP1 coiled-coil region was evident from its variation from a previously determined structure of a similar region. A hydrogen-bond network and changes in coiled-coil monomer interaction suggest that the HIP1 coiled-coil domain is uniquely suited to allow conformational flexibility.

Hsp70-Bag3 interactions regulate cancer-related signaling networks.

PubMed

Colvin, Teresa A; Gabai, Vladimir L; Gong, Jianlin; Calderwood, Stuart K; Li, Hu; Gummuluru, Suryaram; Matchuk, Olga N; Smirnova, Svetlana G; Orlova, Nina V; Zamulaeva, Irina A; Garcia-Marcos, Mikel; Li, Xiaokai; Young, Z T; Rauch, Jennifer N; Gestwicki, Jason E; Takayama, Shinichi; Sherman, Michael Y

2014-09-01

Bag3, a nucleotide exchange factor of the heat shock protein Hsp70, has been implicated in cell signaling. Here, we report that Bag3 interacts with the SH3 domain of Src, thereby mediating the effects of Hsp70 on Src signaling. Using several complementary approaches, we established that the Hsp70-Bag3 module is a broad-acting regulator of cancer cell signaling by modulating the activity of the transcription factors NF-κB, FoxM1, Hif1α, the translation regulator HuR, and the cell-cycle regulators p21 and survivin. We also identified a small-molecule inhibitor, YM-1, that disrupts the Hsp70-Bag3 interaction. YM-1 mirrored the effects of Hsp70 depletion on these signaling pathways, and in vivo administration of this drug was sufficient to suppress tumor growth in mice. Overall, our results defined Bag3 as a critical factor in Hsp70-modulated signaling and offered a preclinical proof-of-concept that the Hsp70-Bag3 complex may offer an appealing anticancer target. ©2014 American Association for Cancer Research.

Hsp70-Bag3 interactions regulate cancer-related signaling networks

PubMed Central

Colvin, T.A.; Gabai, V.L.; Gong, J.; Calderwood, S.K.; Li, H.; Gummuluru, S.; Matchuk, O.N; Smirnova, S.G; Orlova, N.V; Zamulaeva, I.A; Garcia-Marcos, M.; Li, X.; Young, Z.T.; Rauch, J.N.; Gestwicki, J.E.; Takayama, S.; Sherman, M.Y.

2014-01-01

Bag3, a nucleotide exchange factor of the heat shock protein Hsp70, has been implicated in cell signaling. Here we report that Bag3 interacts with the SH3 domain of Src, thereby mediating the effects of Hsp70 on Src signaling. Using several complementary approaches, we established that the Hsp70-Bag3 module is a broad-acting regulator of cancer cell signaling, including by modulating the activity of the transcription factors NF-kB, FoxM1 and Hif1α, the translation regulator HuR and the cell cycle regulators p21 and survivin. We also identified a small molecule inhibitor, YM-1, that disrupts Hsp70-Bag3 interaction. YM-1 mirrored the effects of Hsp70 depletion on these signaling pathways, and in vivo administration of this drug was sufficient to suppress tumor growth in mice. Overall, our results defined Bag3 as a critical factor in Hsp70-modulated signaling and offered a preclinical proof-of-concept that the Hsp70-Bag3 complex may offer an appealing anti-cancer target. PMID:24994713

Network Biomarkers of Bladder Cancer Based on a Genome-Wide Genetic and Epigenetic Network Derived from Next-Generation Sequencing Data.

PubMed

Li, Cheng-Wei; Chen, Bor-Sen

2016-01-01

Epigenetic and microRNA (miRNA) regulation are associated with carcinogenesis and the development of cancer. By using the available omics data, including those from next-generation sequencing (NGS), genome-wide methylation profiling, candidate integrated genetic and epigenetic network (IGEN) analysis, and drug response genome-wide microarray analysis, we constructed an IGEN system based on three coupling regression models that characterize protein-protein interaction networks (PPINs), gene regulatory networks (GRNs), miRNA regulatory networks (MRNs), and epigenetic regulatory networks (ERNs). By applying system identification method and principal genome-wide network projection (PGNP) to IGEN analysis, we identified the core network biomarkers to investigate bladder carcinogenic mechanisms and design multiple drug combinations for treating bladder cancer with minimal side-effects. The progression of DNA repair and cell proliferation in stage 1 bladder cancer ultimately results not only in the derepression of miR-200a and miR-200b but also in the regulation of the TNF pathway to metastasis-related genes or proteins, cell proliferation, and DNA repair in stage 4 bladder cancer. We designed a multiple drug combination comprising gefitinib, estradiol, yohimbine, and fulvestrant for treating stage 1 bladder cancer with minimal side-effects, and another multiple drug combination comprising gefitinib, estradiol, chlorpromazine, and LY294002 for treating stage 4 bladder cancer with minimal side-effects.

The Prediction of Key Cytoskeleton Components Involved in Glomerular Diseases Based on a Protein-Protein Interaction Network.

PubMed

Ding, Fangrui; Tan, Aidi; Ju, Wenjun; Li, Xuejuan; Li, Shao; Ding, Jie

2016-01-01

Maintenance of the physiological morphologies of different types of cells and tissues is essential for the normal functioning of each system in the human body. Dynamic variations in cell and tissue morphologies depend on accurate adjustments of the cytoskeletal system. The cytoskeletal system in the glomerulus plays a key role in the normal process of kidney filtration. To enhance the understanding of the possible roles of the cytoskeleton in glomerular diseases, we constructed the Glomerular Cytoskeleton Network (GCNet), which shows the protein-protein interaction network in the glomerulus, and identified several possible key cytoskeletal components involved in glomerular diseases. In this study, genes/proteins annotated to the cytoskeleton were detected by Gene Ontology analysis, and glomerulus-enriched genes were selected from nine available glomerular expression datasets. Then, the GCNet was generated by combining these two sets of information. To predict the possible key cytoskeleton components in glomerular diseases, we then examined the common regulation of the genes in GCNet in the context of five glomerular diseases based on their transcriptomic data. As a result, twenty-one cytoskeleton components as potential candidate were highlighted for consistently down- or up-regulating in all five glomerular diseases. And then, these candidates were examined in relation to existing known glomerular diseases and genes to determine their possible functions and interactions. In addition, the mRNA levels of these candidates were also validated in a puromycin aminonucleoside(PAN) induced rat nephropathy model and were also matched with existing Diabetic Nephropathy (DN) transcriptomic data. As a result, there are 15 of 21 candidates in PAN induced nephropathy model were consistent with our predication and also 12 of 21 candidates were matched with differentially expressed genes in the DN transcriptomic data. By providing a novel interaction network and prediction, GCNet contributes to improving the understanding of normal glomerular function and will be useful for detecting target cytoskeleton molecules of interest that may be involved in glomerular diseases in future studies.

The Prediction of Key Cytoskeleton Components Involved in Glomerular Diseases Based on a Protein-Protein Interaction Network

PubMed Central

Ju, Wenjun; Li, Xuejuan; Li, Shao; Ding, Jie

2016-01-01

Maintenance of the physiological morphologies of different types of cells and tissues is essential for the normal functioning of each system in the human body. Dynamic variations in cell and tissue morphologies depend on accurate adjustments of the cytoskeletal system. The cytoskeletal system in the glomerulus plays a key role in the normal process of kidney filtration. To enhance the understanding of the possible roles of the cytoskeleton in glomerular diseases, we constructed the Glomerular Cytoskeleton Network (GCNet), which shows the protein-protein interaction network in the glomerulus, and identified several possible key cytoskeletal components involved in glomerular diseases. In this study, genes/proteins annotated to the cytoskeleton were detected by Gene Ontology analysis, and glomerulus-enriched genes were selected from nine available glomerular expression datasets. Then, the GCNet was generated by combining these two sets of information. To predict the possible key cytoskeleton components in glomerular diseases, we then examined the common regulation of the genes in GCNet in the context of five glomerular diseases based on their transcriptomic data. As a result, twenty-one cytoskeleton components as potential candidate were highlighted for consistently down- or up-regulating in all five glomerular diseases. And then, these candidates were examined in relation to existing known glomerular diseases and genes to determine their possible functions and interactions. In addition, the mRNA levels of these candidates were also validated in a puromycin aminonucleoside(PAN) induced rat nephropathy model and were also matched with existing Diabetic Nephropathy (DN) transcriptomic data. As a result, there are 15 of 21 candidates in PAN induced nephropathy model were consistent with our predication and also 12 of 21 candidates were matched with differentially expressed genes in the DN transcriptomic data. By providing a novel interaction network and prediction, GCNet contributes to improving the understanding of normal glomerular function and will be useful for detecting target cytoskeleton molecules of interest that may be involved in glomerular diseases in future studies. PMID:27227331

HAND2 Targets Define a Network of Transcriptional Regulators that Compartmentalize the Early Limb Bud Mesenchyme

DOE PAGES

Osterwalder, Marco; Speziale, Dario; Shoukry, Malak; ...

2014-11-10

The genetic networks that govern vertebrate development are well studied, but how the interactions of trans-acting factors with cis-regulatory modules (CRMs) are integrated into spatiotemporal regulation of gene expression is not clear. The transcriptional regulator HAND2 is required during limb, heart, and branchial arch development. Here, we identify the genomic regions enriched in HAND2 chromatin complexes from mouse embryos and limb buds. Then we analyze the HAND2 target CRMs in the genomic landscapes encoding transcriptional regulators required in early limb buds. HAND2 controls the expression of genes functioning in the proximal limb bud and orchestrates the establishment of anterior andmore » posterior polarity of the nascent limb bud mesenchyme by impacting Gli3 and Tbx3 expression. TBX3 is required downstream of HAND2 to refine the posterior Gli3 expression boundary. In conclusion, our analysis uncovers the transcriptional circuits that function in establishing distinct mesenchymal compartments downstream of HAND2 and upstream of SHH signaling.« less

Ethylene Control of Fruit Ripening: Revisiting the Complex Network of Transcriptional Regulation1

PubMed Central

Chervin, Christian; Bouzayen, Mondher

2015-01-01

The plant hormone ethylene plays a key role in climacteric fruit ripening. Studies on components of ethylene signaling have revealed a linear transduction pathway leading to the activation of ethylene response factors. However, the means by which ethylene selects the ripening-related genes and interacts with other signaling pathways to regulate the ripening process are still to be elucidated. Using tomato (Solanum lycopersicum) as a reference species, the present review aims to revisit the mechanisms by which ethylene regulates fruit ripening by taking advantage of new tools available to perform in silico studies at the genome-wide scale, leading to a global view on the expression pattern of ethylene biosynthesis and response genes throughout ripening. Overall, it provides new insights on the transcriptional network by which this hormone coordinates the ripening process and emphasizes the interplay between ethylene and ripening-associated developmental factors and the link between epigenetic regulation and ethylene during fruit ripening. PMID:26511917

PAINT: a promoter analysis and interaction network generation tool for gene regulatory network identification.

PubMed

Vadigepalli, Rajanikanth; Chakravarthula, Praveen; Zak, Daniel E; Schwaber, James S; Gonye, Gregory E

2003-01-01

We have developed a bioinformatics tool named PAINT that automates the promoter analysis of a given set of genes for the presence of transcription factor binding sites. Based on coincidence of regulatory sites, this tool produces an interaction matrix that represents a candidate transcriptional regulatory network. This tool currently consists of (1) a database of promoter sequences of known or predicted genes in the Ensembl annotated mouse genome database, (2) various modules that can retrieve and process the promoter sequences for binding sites of known transcription factors, and (3) modules for visualization and analysis of the resulting set of candidate network connections. This information provides a substantially pruned list of genes and transcription factors that can be examined in detail in further experimental studies on gene regulation. Also, the candidate network can be incorporated into network identification methods in the form of constraints on feasible structures in order to render the algorithms tractable for large-scale systems. The tool can also produce output in various formats suitable for use in external visualization and analysis software. In this manuscript, PAINT is demonstrated in two case studies involving analysis of differentially regulated genes chosen from two microarray data sets. The first set is from a neuroblastoma N1E-115 cell differentiation experiment, and the second set is from neuroblastoma N1E-115 cells at different time intervals following exposure to neuropeptide angiotensin II. PAINT is available for use as an agent in BioSPICE simulation and analysis framework (www.biospice.org), and can also be accessed via a WWW interface at www.dbi.tju.edu/dbi/tools/paint/.

SKIP Is a Component of the Spliceosome Linking Alternative Splicing and the Circadian Clock in Arabidopsis[W

PubMed Central

Wang, Xiaoxue; Wu, Fangming; Xie, Qiguang; Wang, Huamei; Wang, Ying; Yue, Yanling; Gahura, Ondrej; Ma, Shuangshuang; Liu, Lei; Cao, Ying; Jiao, Yuling; Puta, Frantisek; McClung, C. Robertson; Xu, Xiaodong; Ma, Ligeng

2012-01-01

Circadian clocks generate endogenous rhythms in most organisms from cyanobacteria to humans and facilitate entrainment to environmental diurnal cycles, thus conferring a fitness advantage. Both transcriptional and posttranslational mechanisms are prominent in the basic network architecture of circadian systems. Posttranscriptional regulation, including mRNA processing, is emerging as a critical step for clock function. However, little is known about the molecular mechanisms linking RNA metabolism to the circadian clock network. Here, we report that a conserved SNW/Ski-interacting protein (SKIP) domain protein, SKIP, a splicing factor and component of the spliceosome, is involved in posttranscriptional regulation of circadian clock genes in Arabidopsis thaliana. Mutation in SKIP lengthens the circadian period in a temperature-sensitive manner and affects light input and the sensitivity of the clock to light resetting. SKIP physically interacts with the spliceosomal splicing factor Ser/Arg-rich protein45 and associates with the pre-mRNA of clock genes, such as PSEUDORESPONSE REGULATOR7 (PRR7) and PRR9, and is necessary for the regulation of their alternative splicing and mRNA maturation. Genome-wide investigations reveal that SKIP functions in regulating alternative splicing of many genes, presumably through modulating recognition or cleavage of 5′ and 3′ splice donor and acceptor sites. Our study addresses a fundamental question on how the mRNA splicing machinery contributes to circadian clock function at a posttranscriptional level. PMID:22942380

From SNP co-association to RNA co-expression: novel insights into gene networks for intramuscular fatty acid composition in porcine.

PubMed

Ramayo-Caldas, Yuliaxis; Ballester, Maria; Fortes, Marina R S; Esteve-Codina, Anna; Castelló, Anna; Noguera, Jose L; Fernández, Ana I; Pérez-Enciso, Miguel; Reverter, Antonio; Folch, Josep M

2014-03-26

Fatty acids (FA) play a critical role in energy homeostasis and metabolic diseases; in the context of livestock species, their profile also impacts on meat quality for healthy human consumption. Molecular pathways controlling lipid metabolism are highly interconnected and are not fully understood. Elucidating these molecular processes will aid technological development towards improvement of pork meat quality and increased knowledge of FA metabolism, underpinning metabolic diseases in humans. The results from genome-wide association studies (GWAS) across 15 phenotypes were subjected to an Association Weight Matrix (AWM) approach to predict a network of 1,096 genes related to intramuscular FA composition in pigs. To identify the key regulators of FA metabolism, we focused on the minimal set of transcription factors (TF) that the explored the majority of the network topology. Pathway and network analyses pointed towards a trio of TF as key regulators of FA metabolism: NCOA2, FHL2 and EP300. Promoter sequence analyses confirmed that these TF have binding sites for some well-know regulators of lipid and carbohydrate metabolism. For the first time in a non-model species, some of the co-associations observed at the genetic level were validated through co-expression at the transcriptomic level based on real-time PCR of 40 genes in adipose tissue, and a further 55 genes in liver. In particular, liver expression of NCOA2 and EP300 differed between pig breeds (Iberian and Landrace) extreme in terms of fat deposition. Highly clustered co-expression networks in both liver and adipose tissues were observed. EP300 and NCOA2 showed centrality parameters above average in the both networks. Over all genes, co-expression analyses confirmed 28.9% of the AWM predicted gene-gene interactions in liver and 33.0% in adipose tissue. The magnitude of this validation varied across genes, with up to 60.8% of the connections of NCOA2 in adipose tissue being validated via co-expression. Our results recapitulate the known transcriptional regulation of FA metabolism, predict gene interactions that can be experimentally validated, and suggest that genetic variants mapped to EP300, FHL2, and NCOA2 modulate lipid metabolism and control energy homeostasis in pigs.

Paradigm shift in consciousness research: the child's self-awareness and abnormalities in autism, ADHD and schizophrenia.

PubMed

Lou, Hans C

2012-02-01

Self-awareness is a pivotal component of any conscious experience and conscious self-regulation of behaviour. A paralimbic network is active, specific and causal in self-awareness. Its regions interact by gamma synchrony. Gamma synchrony develops throughout infancy, childhood and adolescence into adulthood and is regulated by dopamine and other neurotransmitters via GABA interneurons. Major derailments of this network and self-awareness occur in developmental disorders of conscious self-regulation like autism, attention deficit hyperactivity disorder (ADHD) and schizophrenia. Recent research on conscious experience is no longer limited to the study of neural 'correlations' but is increasingly lending itself to the study of causality. This paradigm shift opens new perspectives for understanding the neural mechanisms of the developing self and the causal effects of their disturbance in developmental disorders. © 2011 The Author(s)/Acta Paediatrica © 2011 Foundation Acta Paediatrica.

Detection of dysregulated protein-association networks by high-throughput proteomics predicts cancer vulnerabilities.

PubMed

Lapek, John D; Greninger, Patricia; Morris, Robert; Amzallag, Arnaud; Pruteanu-Malinici, Iulian; Benes, Cyril H; Haas, Wilhelm

2017-10-01

The formation of protein complexes and the co-regulation of the cellular concentrations of proteins are essential mechanisms for cellular signaling and for maintaining homeostasis. Here we use isobaric-labeling multiplexed proteomics to analyze protein co-regulation and show that this allows the identification of protein-protein associations with high accuracy. We apply this 'interactome mapping by high-throughput quantitative proteome analysis' (IMAHP) method to a panel of 41 breast cancer cell lines and show that deviations of the observed protein co-regulations in specific cell lines from the consensus network affects cellular fitness. Furthermore, these aberrant interactions serve as biomarkers that predict the drug sensitivity of cell lines in screens across 195 drugs. We expect that IMAHP can be broadly used to gain insight into how changing landscapes of protein-protein associations affect the phenotype of biological systems.

Metabolic Profiling of a Mapping Population Exposes New Insights in the Regulation of Seed Metabolism and Seed, Fruit, and Plant Relations

PubMed Central

Toubiana, David; Semel, Yaniv; Tohge, Takayuki; Beleggia, Romina; Cattivelli, Luigi; Rosental, Leah; Nikoloski, Zoran; Zamir, Dani; Fernie, Alisdair R.; Fait, Aaron

2012-01-01

To investigate the regulation of seed metabolism and to estimate the degree of metabolic natural variability, metabolite profiling and network analysis were applied to a collection of 76 different homozygous tomato introgression lines (ILs) grown in the field in two consecutive harvest seasons. Factorial ANOVA confirmed the presence of 30 metabolite quantitative trait loci (mQTL). Amino acid contents displayed a high degree of variability across the population, with similar patterns across the two seasons, while sugars exhibited significant seasonal fluctuations. Upon integration of data for tomato pericarp metabolite profiling, factorial ANOVA identified the main factor for metabolic polymorphism to be the genotypic background rather than the environment or the tissue. Analysis of the coefficient of variance indicated greater phenotypic plasticity in the ILs than in the M82 tomato cultivar. Broad-sense estimate of heritability suggested that the mode of inheritance of metabolite traits in the seed differed from that in the fruit. Correlation-based metabolic network analysis comparing metabolite data for the seed with that for the pericarp showed that the seed network displayed tighter interdependence of metabolic processes than the fruit. Amino acids in the seed metabolic network were shown to play a central hub-like role in the topology of the network, maintaining high interactions with other metabolite categories, i.e., sugars and organic acids. Network analysis identified six exceptionally highly co-regulated amino acids, Gly, Ser, Thr, Ile, Val, and Pro. The strong interdependence of this group was confirmed by the mQTL mapping. Taken together these results (i) reflect the extensive redundancy of the regulation underlying seed metabolism, (ii) demonstrate the tight co-ordination of seed metabolism with respect to fruit metabolism, and (iii) emphasize the centrality of the amino acid module in the seed metabolic network. Finally, the study highlights the added value of integrating metabolic network analysis with mQTL mapping. PMID:22479206

Evolutionary trends and functional anatomy of the human expanded autophagy network

PubMed Central

Till, Andreas; Saito, Rintaro; Merkurjev, Daria; Liu, Jing-Jing; Syed, Gulam Hussain; Kolnik, Martin; Siddiqui, Aleem; Glas, Martin; Scheffler, Björn; Ideker, Trey; Subramani, Suresh

2015-01-01

All eukaryotic cells utilize autophagy for protein and organelle turnover, thus assuring subcellular quality control, homeostasis, and survival. In order to address recent advances in identification of human autophagy associated genes, and to describe autophagy on a system-wide level, we established an autophagy-centered gene interaction network by merging various primary data sets and by retrieving respective interaction data. The resulting network (‘AXAN’) was analyzed with respect to subnetworks, e.g. the prime gene subnetwork (including the core machinery, signaling pathways and autophagy receptors) and the transcription subnetwork. To describe aspects of evolution within this network, we assessed the presence of protein orthologs across 99 eukaryotic model organisms. We visualized evolutionary trends for prime gene categories and evolutionary tracks for selected AXAN genes. This analysis confirms the eukaryotic origin of autophagy core genes while it points to a diverse evolutionary history of autophagy receptors. Next, we used module identification to describe the functional anatomy of the network at the level of pathway modules. In addition to obvious pathways (e.g., lysosomal degradation, insulin signaling) our data unveil the existence of context-related modules such as Rho GTPase signaling. Last, we used a tripartite, image-based RNAi – screen to test candidate genes predicted to play a role in regulation of autophagy. We verified the Rho GTPase, CDC42, as a novel regulator of autophagy-related signaling. This study emphasizes the applicability of system-wide approaches to gain novel insights into a complex biological process and to describe the human autophagy pathway at a hitherto unprecedented level of detail. PMID:26103419

Large-Scale Mapping and Validation of Escherichia coli Transcriptional Regulation from a Compendium of Expression Profiles

PubMed Central

Thaden, Joshua T; Mogno, Ilaria; Wierzbowski, Jamey; Cottarel, Guillaume; Kasif, Simon; Collins, James J; Gardner, Timothy S

2007-01-01

Machine learning approaches offer the potential to systematically identify transcriptional regulatory interactions from a compendium of microarray expression profiles. However, experimental validation of the performance of these methods at the genome scale has remained elusive. Here we assess the global performance of four existing classes of inference algorithms using 445 Escherichia coli Affymetrix arrays and 3,216 known E. coli regulatory interactions from RegulonDB. We also developed and applied the context likelihood of relatedness (CLR) algorithm, a novel extension of the relevance networks class of algorithms. CLR demonstrates an average precision gain of 36% relative to the next-best performing algorithm. At a 60% true positive rate, CLR identifies 1,079 regulatory interactions, of which 338 were in the previously known network and 741 were novel predictions. We tested the predicted interactions for three transcription factors with chromatin immunoprecipitation, confirming 21 novel interactions and verifying our RegulonDB-based performance estimates. CLR also identified a regulatory link providing central metabolic control of iron transport, which we confirmed with real-time quantitative PCR. The compendium of expression data compiled in this study, coupled with RegulonDB, provides a valuable model system for further improvement of network inference algorithms using experimental data. PMID:17214507

ReNE: A Cytoscape Plugin for Regulatory Network Enhancement

PubMed Central

Politano, Gianfranco; Benso, Alfredo; Savino, Alessandro; Di Carlo, Stefano

2014-01-01

One of the biggest challenges in the study of biological regulatory mechanisms is the integration, americanmodeling, and analysis of the complex interactions which take place in biological networks. Despite post transcriptional regulatory elements (i.e., miRNAs) are widely investigated in current research, their usage and visualization in biological networks is very limited. Regulatory networks are commonly limited to gene entities. To integrate networks with post transcriptional regulatory data, researchers are therefore forced to manually resort to specific third party databases. In this context, we introduce ReNE, a Cytoscape 3.x plugin designed to automatically enrich a standard gene-based regulatory network with more detailed transcriptional, post transcriptional, and translational data, resulting in an enhanced network that more precisely models the actual biological regulatory mechanisms. ReNE can automatically import a network layout from the Reactome or KEGG repositories, or work with custom pathways described using a standard OWL/XML data format that the Cytoscape import procedure accepts. Moreover, ReNE allows researchers to merge multiple pathways coming from different sources. The merged network structure is normalized to guarantee a consistent and uniform description of the network nodes and edges and to enrich all integrated data with additional annotations retrieved from genome-wide databases like NCBI, thus producing a pathway fully manageable through the Cytoscape environment. The normalized network is then analyzed to include missing transcription factors, miRNAs, and proteins. The resulting enhanced network is still a fully functional Cytoscape network where each regulatory element (transcription factor, miRNA, gene, protein) and regulatory mechanism (up-regulation/down-regulation) is clearly visually identifiable, thus enabling a better visual understanding of its role and the effect in the network behavior. The enhanced network produced by ReNE is exportable in multiple formats for further analysis via third party applications. ReNE can be freely installed from the Cytoscape App Store (http://apps.cytoscape.org/apps/rene) and the full source code is freely available for download through a SVN repository accessible at http://www.sysbio.polito.it/tools_svn/BioInformatics/Rene/releases/. ReNE enhances a network by only integrating data from public repositories, without any inference or prediction. The reliability of the introduced interactions only depends on the reliability of the source data, which is out of control of ReNe developers. PMID:25541727

Identification and functional analysis of risk-related microRNAs for the prognosis of patients with bladder urothelial carcinoma.

PubMed

Gao, Ji; Li, Hongyan; Liu, Lei; Song, Lide; Lv, Yanting; Han, Yuping

2017-12-01

The aim of the present study was to investigate risk-related microRNAs (miRs) for bladder urothelial carcinoma (BUC) prognosis. Clinical and microRNA expression data downloaded from the Cancer Genome Atlas were utilized for survival analysis. Risk factor estimation was performed using Cox's proportional regression analysis. A microRNA-regulated target gene network was constructed and presented using Cytoscape. In addition, the Database for Annotation, Visualization and Integrated Discovery was used for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway enrichment, followed by protein-protein interaction (PPI) network analysis. Finally, the K-clique method was applied to analyze sub-pathways. A total of 16 significant microRNAs, including hsa-miR-3622a and hsa-miR-29a, were identified (P<0.05). Following Cox's proportional regression analysis, hsa-miR-29a was screened as a prognostic marker of BUC risk (P=0.0449). A regulation network of hsa-miR-29a comprising 417 target genes was constructed. These target genes were primarily enriched in GO terms, including collagen fibril organization, extracellular matrix (ECM) organization and pathways, such as focal adhesion (P<0.05). A PPI network including 197 genes and 510 interactions, was constructed. The top 21 genes in the network module were enriched in GO terms, including collagen fibril organization and pathways, such as ECM receptor interaction (P<0.05). Finally, 4 sub-pathways of cysteine and methionine metabolism, including paths 00270_4, 00270_1, 00270_2 and 00270_5, were obtained (P<0.01) and identified to be enriched through DNA (cytosine-5)-methyltransferase ( DNMT)3A, DNMT3B , methionine adenosyltransferase 2α ( MAT2A ) and spermine synthase ( SMS ). The identified microRNAs, particularly hsa-miR-29a and its 4 associated target genes DNMT3A, DNMT3B, MAT2A and SMS , may participate in the prognostic risk mechanism of BUC.

Molecular and epigenetic regulations and functions of the LAFL transcriptional regulators that control seed development.

PubMed

Lepiniec, L; Devic, M; Roscoe, T J; Bouyer, D; Zhou, D-X; Boulard, C; Baud, S; Dubreucq, B

2018-05-24

The LAFL (i.e. LEC1, ABI3, FUS3, and LEC2) master transcriptional regulators interact to form different complexes that induce embryo development and maturation, and inhibit seed germination and vegetative growth in Arabidopsis. Orthologous genes involved in similar regulatory processes have been described in various angiosperms including important crop species. Consistent with a prominent role of the LAFL regulators in triggering and maintaining embryonic cell fate, their expression appears finely tuned in different tissues during seed development and tightly repressed in vegetative tissues by a surprisingly high number of genetic and epigenetic factors. Partial functional redundancies and intricate feedback regulations of the LAFL have hampered the elucidation of the underpinning molecular mechanisms. Nevertheless, genetic, genomic, cellular, molecular, and biochemical analyses implemented during the last years have greatly improved our knowledge of the LALF network. Here we summarize and discuss recent progress, together with current issues required to gain a comprehensive insight into the network, including the emerging function of LEC1 and possibly LEC2 as pioneer transcription factors.

Exploring the Yeast Acetylome Using Functional Genomics

PubMed Central

Duffy, Supipi Kaluarachchi; Friesen, Helena; Baryshnikova, Anastasia; Lambert, Jean-Philippe; Chong, Yolanda T.; Figeys, Daniel; Andrews, Brenda

2014-01-01

SUMMARY Lysine acetylation is a dynamic posttranslational modification with a well-defined role in regulating histones. The impact of acetylation on other cellular functions remains relatively uncharacterized. We explored the budding yeast acetylome with a functional genomics approach, assessing the effects of gene overexpression in the absence of lysine deacetylases (KDACs). We generated a network of 463 synthetic dosage lethal (SDL) interactions involving class I and II KDACs, revealing many cellular pathways regulated by different KDACs. A biochemical survey of genes interacting with the KDAC RPD3 identified 72 proteins acetylated in vivo. In-depth analysis of one of these proteins, Swi4, revealed a role for acetylation in G1-specific gene expression. Acetylation of Swi4 regulates interaction with its partner Swi6, both components of the SBF transcription factor. This study expands our view of the yeast acetylome, demonstrates the utility of functional genomic screens for exploring enzymatic pathways, and provides functional information that can be mined for future studies. PMID:22579291

The immunoregulatory role of type I and type II NKT cells in cancer and other diseases

PubMed Central

Terabe, Masaki; Berzofsky, Jay A.

2014-01-01

NKT cells are CD1d-restricted T cells that recognize lipid antigens. They also have been shown to play critical roles in the regulation of immune responses. In the immune responses against tumors, two subsets of NKT cells, type I and type II, play opposing roles and cross-regulate each other. As members of both the innate and adaptive immune systems, which form a network of multiple components, they also interact with other immune components. Here we discuss the function of NKT cells in tumor immunity and their interaction with other regulatory cells, especially CD4+CD25+Foxp3+ regulatory T cells. PMID:24384834

Stochastic simulation of enzyme-catalyzed reactions with disparate timescales.

PubMed

Barik, Debashis; Paul, Mark R; Baumann, William T; Cao, Yang; Tyson, John J

2008-10-01

Many physiological characteristics of living cells are regulated by protein interaction networks. Because the total numbers of these protein species can be small, molecular noise can have significant effects on the dynamical properties of a regulatory network. Computing these stochastic effects is made difficult by the large timescale separations typical of protein interactions (e.g., complex formation may occur in fractions of a second, whereas catalytic conversions may take minutes). Exact stochastic simulation may be very inefficient under these circumstances, and methods for speeding up the simulation without sacrificing accuracy have been widely studied. We show that the "total quasi-steady-state approximation" for enzyme-catalyzed reactions provides a useful framework for efficient and accurate stochastic simulations. The method is applied to three examples: a simple enzyme-catalyzed reaction where enzyme and substrate have comparable abundances, a Goldbeter-Koshland switch, where a kinase and phosphatase regulate the phosphorylation state of a common substrate, and coupled Goldbeter-Koshland switches that exhibit bistability. Simulations based on the total quasi-steady-state approximation accurately capture the steady-state probability distributions of all components of these reaction networks. In many respects, the approximation also faithfully reproduces time-dependent aspects of the fluctuations. The method is accurate even under conditions of poor timescale separation.

NaviCom: a web application to create interactive molecular network portraits using multi-level omics data.

PubMed

Dorel, Mathurin; Viara, Eric; Barillot, Emmanuel; Zinovyev, Andrei; Kuperstein, Inna

2017-01-01

Human diseases such as cancer are routinely characterized by high-throughput molecular technologies, and multi-level omics data are accumulated in public databases at increasing rate. Retrieval and visualization of these data in the context of molecular network maps can provide insights into the pattern of regulation of molecular functions reflected by an omics profile. In order to make this task easy, we developed NaviCom, a Python package and web platform for visualization of multi-level omics data on top of biological network maps. NaviCom is bridging the gap between cBioPortal, the most used resource of large-scale cancer omics data and NaviCell, a data visualization web service that contains several molecular network map collections. NaviCom proposes several standardized modes of data display on top of molecular network maps, allowing addressing specific biological questions. We illustrate how users can easily create interactive network-based cancer molecular portraits via NaviCom web interface using the maps of Atlas of Cancer Signalling Network (ACSN) and other maps. Analysis of these molecular portraits can help in formulating a scientific hypothesis on the molecular mechanisms deregulated in the studied disease. NaviCom is available at https://navicom.curie.fr. © The Author(s) 2017. Published by Oxford University Press.

Systems approach identifies an organic nitrogen-responsive gene network that is regulated by the master clock control gene CCA1.

PubMed

Gutiérrez, Rodrigo A; Stokes, Trevor L; Thum, Karen; Xu, Xiaodong; Obertello, Mariana; Katari, Manpreet S; Tanurdzic, Milos; Dean, Alexis; Nero, Damion C; McClung, C Robertson; Coruzzi, Gloria M

2008-03-25

Understanding how nutrients affect gene expression will help us to understand the mechanisms controlling plant growth and development as a function of nutrient availability. Nitrate has been shown to serve as a signal for the control of gene expression in Arabidopsis. There is also evidence, on a gene-by-gene basis, that downstream products of nitrogen (N) assimilation such as glutamate (Glu) or glutamine (Gln) might serve as signals of organic N status that in turn regulate gene expression. To identify genome-wide responses to such organic N signals, Arabidopsis seedlings were transiently treated with ammonium nitrate in the presence or absence of MSX, an inhibitor of glutamine synthetase, resulting in a block of Glu/Gln synthesis. Genes that responded to organic N were identified as those whose response to ammonium nitrate treatment was blocked in the presence of MSX. We showed that some genes previously identified to be regulated by nitrate are under the control of an organic N-metabolite. Using an integrated network model of molecular interactions, we uncovered a subnetwork regulated by organic N that included CCA1 and target genes involved in N-assimilation. We validated some of the predicted interactions and showed that regulation of the master clock control gene CCA1 by Glu or a Glu-derived metabolite in turn regulates the expression of key N-assimilatory genes. Phase response curve analysis shows that distinct N-metabolites can advance or delay the CCA1 phase. Regulation of CCA1 by organic N signals may represent a novel input mechanism for N-nutrients to affect plant circadian clock function.

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

PubMed Central

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

2017-01-01

High-throughput RNAi screenings (HTS) allow quantifying the impact of the deletion of each gene in any particular function, from virus-host interactions to cell differentiation. However, there has been less development for functional analysis tools dedicated to RNAi analyses. HTS-Net, a network-based analysis program, was developed to identify gene regulatory modules impacted in high-throughput screenings, by integrating transcription factors-target genes interaction data (regulome) and protein-protein interaction networks (interactome) on top of screening z-scores. HTS-Net produces exhaustive HTML reports for results navigation and exploration. HTS-Net is a new pipeline for RNA interference screening analyses that proves better performance than simple gene rankings by z-scores, by re-prioritizing genes and replacing them in their biological context, as shown by the three studies that we reanalyzed. Formatted input data for the three studied datasets, source code and web site for testing the system are available from the companion web site at http://htsnet.marseille.inserm.fr/. We also compared our program with existing algorithms (CARD and hotnet2). PMID:28949986

Investigation on Law and Economics Based on Complex Network and Time Series Analysis

PubMed Central

Yang, Jian; Qu, Zhao; Chang, Hui

2015-01-01

The research focuses on the cooperative relationship and the strategy tendency among three mutually interactive parties in financing: small enterprises, commercial banks and micro-credit companies. Complex network theory and time series analysis were applied to figure out the quantitative evidence. Moreover, this paper built up a fundamental model describing the particular interaction among them through evolutionary game. Combining the results of data analysis and current situation, it is justifiable to put forward reasonable legislative recommendations for regulations on lending activities among small enterprises, commercial banks and micro-credit companies. The approach in this research provides a framework for constructing mathematical models and applying econometrics and evolutionary game in the issue of corporation financing. PMID:26076460

Influence maximization in time bounded network identifies transcription factors regulating perturbed pathways

PubMed Central

Jo, Kyuri; Jung, Inuk; Moon, Ji Hwan; Kim, Sun

2016-01-01

Motivation: To understand the dynamic nature of the biological process, it is crucial to identify perturbed pathways in an altered environment and also to infer regulators that trigger the response. Current time-series analysis methods, however, are not powerful enough to identify perturbed pathways and regulators simultaneously. Widely used methods include methods to determine gene sets such as differentially expressed genes or gene clusters and these genes sets need to be further interpreted in terms of biological pathways using other tools. Most pathway analysis methods are not designed for time series data and they do not consider gene-gene influence on the time dimension. Results: In this article, we propose a novel time-series analysis method TimeTP for determining transcription factors (TFs) regulating pathway perturbation, which narrows the focus to perturbed sub-pathways and utilizes the gene regulatory network and protein–protein interaction network to locate TFs triggering the perturbation. TimeTP first identifies perturbed sub-pathways that propagate the expression changes along the time. Starting points of the perturbed sub-pathways are mapped into the network and the most influential TFs are determined by influence maximization technique. The analysis result is visually summarized in TF-Pathway map in time clock. TimeTP was applied to PIK3CA knock-in dataset and found significant sub-pathways and their regulators relevant to the PIP3 signaling pathway. Availability and Implementation: TimeTP is implemented in Python and available at http://biohealth.snu.ac.kr/software/TimeTP/. Supplementary information: Supplementary data are available at Bioinformatics online. Contact: sunkim.bioinfo@snu.ac.kr PMID:27307609

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

PubMed

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

2013-01-01

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

Regulation of Corneal Stroma Extracellular Matrix Assembly

PubMed Central

Chen, Shoujun; Mienaltowski, Michael J.; Birk, David E.

2014-01-01

The transparent cornea is the major refractive element of the eye. A finely controlled assembly of the stromal extracellular matrix is critical to corneal function, as well as in establishing the appropriate mechanical stability required to maintain corneal shape and curvature. In the stroma, homogeneous, small diameter collagen fibrils, regularly packed with a highly ordered hierarchical organization, are essential for function. This review focuses on corneal stroma assembly and the regulation of collagen fibrillogenesis. Corneal collagen fibrillogenesis involves multiple molecules interacting in sequential steps, as well as interactions between keratocytes and stroma matrix components. The stroma has the highest collagen V:I ratio in the body. Collagen V regulates the nucleation of protofibril assembly, thus controlling the number of fibrils and assembly of smaller diameter fibrils in the stroma. The corneal stroma is also enriched in small leucine-rich proteoglycans (SLRPs) that cooperate in a temporal and spatial manner to regulate linear and lateral collagen fibril growth. In addition, the fibril-associated collagens (FACITs) such as collagen XII and collagen XIV have roles in the regulation of fibril packing and inter-lamellar interactions. A communicating keratocyte network contributes to the overall and long-range regulation of stromal extracellular matrix assembly, by creating micro-domains where the sequential steps in stromal matrix assembly are controlled. Keratocytes control the synthesis of extracellular matrix components, which interact with the keratocytes dynamically to coordinate the regulatory steps into a cohesive process. Mutations or deficiencies in stromal regulatory molecules result in altered interactions and deficiencies in both transparency and refraction, leading to corneal stroma pathobiology such as stromal dystrophies, cornea plana and keratoconus. PMID:25819456

Interacting TCP and NLP transcription factors control plant responses to nitrate availability.

PubMed

Guan, Peizhu; Ripoll, Juan-José; Wang, Renhou; Vuong, Lam; Bailey-Steinitz, Lindsay J; Ye, Dening; Crawford, Nigel M

2017-02-28

Plants have evolved adaptive strategies that involve transcriptional networks to cope with and survive environmental challenges. Key transcriptional regulators that mediate responses to environmental fluctuations in nitrate have been identified; however, little is known about how these regulators interact to orchestrate nitrogen (N) responses and cell-cycle regulation. Here we report that teosinte branched1/cycloidea/proliferating cell factor1-20 (TCP20) and NIN-like protein (NLP) transcription factors NLP6 and NLP7, which act as activators of nitrate assimilatory genes, bind to adjacent sites in the upstream promoter region of the nitrate reductase gene, NIA1 , and physically interact under continuous nitrate and N-starvation conditions. Regions of these proteins necessary for these interactions were found to include the type I/II Phox and Bem1p (PB1) domains of NLP6&7, a protein-interaction module conserved in animals for nutrient signaling, and the histidine- and glutamine-rich domain of TCP20, which is conserved across plant species. Under N starvation, TCP20-NLP6&7 heterodimers accumulate in the nucleus, and this coincides with TCP20 and NLP6&7-dependent up-regulation of nitrate assimilation and signaling genes and down-regulation of the G 2 /M cell-cycle marker gene, CYCB1;1 TCP20 and NLP6&7 also support root meristem growth under N starvation. These findings provide insights into how plants coordinate responses to nitrate availability, linking nitrate assimilation and signaling with cell-cycle progression.

FUSE: a profit maximization approach for functional summarization of biological networks.

PubMed

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

2012-03-21

The availability of large-scale curated protein interaction datasets has given rise to the opportunity to investigate higher level organization and modularity within the protein interaction network (PPI) using graph theoretic analysis. Despite the recent progress, systems level analysis of PPIS remains a daunting task as it is challenging to make sense out of the deluge of high-dimensional interaction data. Specifically, techniques that automatically abstract and summarize PPIS at multiple resolutions to provide high level views of its functional landscape are still lacking. We present a novel data-driven and generic algorithm called FUSE (Functional Summary Generator) that generates functional maps of a PPI at different levels of organization, from broad process-process level interactions to in-depth complex-complex level interactions, through a pro t maximization approach that exploits Minimum Description Length (MDL) principle to maximize information gain of the summary graph while satisfying the level of detail constraint. We evaluate the performance of FUSE on several real-world PPIS. We also compare FUSE to state-of-the-art graph clustering methods with GO term enrichment by constructing the biological process landscape of the PPIS. Using AD network as our case study, we further demonstrate the ability of FUSE to quickly summarize the network and identify many different processes and complexes that regulate it. Finally, we study the higher-order connectivity of the human PPI. By simultaneously evaluating interaction and annotation data, FUSE abstracts higher-order interaction maps by reducing the details of the underlying PPI to form a functional summary graph of interconnected functional clusters. Our results demonstrate its effectiveness and superiority over state-of-the-art graph clustering methods with GO term enrichment.

Genome-scale cold stress response regulatory networks in ten Arabidopsis thaliana ecotypes

PubMed Central

2013-01-01

Background Low temperature leads to major crop losses every year. Although several studies have been conducted focusing on diversity of cold tolerance level in multiple phenotypically divergent Arabidopsis thaliana (A. thaliana) ecotypes, genome-scale molecular understanding is still lacking. Results In this study, we report genome-scale transcript response diversity of 10 A. thaliana ecotypes originating from different geographical locations to non-freezing cold stress (10°C). To analyze the transcriptional response diversity, we initially compared transcriptome changes in all 10 ecotypes using Arabidopsis NimbleGen ATH6 microarrays. In total 6061 transcripts were significantly cold regulated (p < 0.01) in 10 ecotypes, including 498 transcription factors and 315 transposable elements. The majority of the transcripts (75%) showed ecotype specific expression pattern. By using sequence data available from Arabidopsis thaliana 1001 genome project, we further investigated sequence polymorphisms in the core cold stress regulon genes. Significant numbers of non-synonymous amino acid changes were observed in the coding region of the CBF regulon genes. Considering the limited knowledge about regulatory interactions between transcription factors and their target genes in the model plant A. thaliana, we have adopted a powerful systems genetics approach- Network Component Analysis (NCA) to construct an in-silico transcriptional regulatory network model during response to cold stress. The resulting regulatory network contained 1,275 nodes and 7,720 connections, with 178 transcription factors and 1,331 target genes. Conclusions A. thaliana ecotypes exhibit considerable variation in transcriptome level responses to non-freezing cold stress treatment. Ecotype specific transcripts and related gene ontology (GO) categories were identified to delineate natural variation of cold stress regulated differential gene expression in the model plant A. thaliana. The predicted regulatory network model was able to identify new ecotype specific transcription factors and their regulatory interactions, which might be crucial for their local geographic adaptation to cold temperature. Additionally, since the approach presented here is general, it could be adapted to study networks regulating biological process in any biological systems. PMID:24148294

RegPrecise 3.0--a resource for genome-scale exploration of transcriptional regulation in bacteria.

PubMed

Novichkov, Pavel S; Kazakov, Alexey E; Ravcheev, Dmitry A; Leyn, Semen A; Kovaleva, Galina Y; Sutormin, Roman A; Kazanov, Marat D; Riehl, William; Arkin, Adam P; Dubchak, Inna; Rodionov, Dmitry A

2013-11-01

Genome-scale prediction of gene regulation and reconstruction of transcriptional regulatory networks in prokaryotes is one of the critical tasks of modern genomics. Bacteria from different taxonomic groups, whose lifestyles and natural environments are substantially different, possess highly diverged transcriptional regulatory networks. The comparative genomics approaches are useful for in silico reconstruction of bacterial regulons and networks operated by both transcription factors (TFs) and RNA regulatory elements (riboswitches). RegPrecise (http://regprecise.lbl.gov) is a web resource for collection, visualization and analysis of transcriptional regulons reconstructed by comparative genomics. We significantly expanded a reference collection of manually curated regulons we introduced earlier. RegPrecise 3.0 provides access to inferred regulatory interactions organized by phylogenetic, structural and functional properties. Taxonomy-specific collections include 781 TF regulogs inferred in more than 160 genomes representing 14 taxonomic groups of Bacteria. TF-specific collections include regulogs for a selected subset of 40 TFs reconstructed across more than 30 taxonomic lineages. Novel collections of regulons operated by RNA regulatory elements (riboswitches) include near 400 regulogs inferred in 24 bacterial lineages. RegPrecise 3.0 provides four classifications of the reference regulons implemented as controlled vocabularies: 55 TF protein families; 43 RNA motif families; ~150 biological processes or metabolic pathways; and ~200 effectors or environmental signals. Genome-wide visualization of regulatory networks and metabolic pathways covered by the reference regulons are available for all studied genomes. A separate section of RegPrecise 3.0 contains draft regulatory networks in 640 genomes obtained by an conservative propagation of the reference regulons to closely related genomes. RegPrecise 3.0 gives access to the transcriptional regulons reconstructed in bacterial genomes. Analytical capabilities include exploration of: regulon content, structure and function; TF binding site motifs; conservation and variations in genome-wide regulatory networks across all taxonomic groups of Bacteria. RegPrecise 3.0 was selected as a core resource on transcriptional regulation of the Department of Energy Systems Biology Knowledgebase, an emerging software and data environment designed to enable researchers to collaboratively generate, test and share new hypotheses about gene and protein functions, perform large-scale analyses, and model interactions in microbes, plants, and their communities.

Role of Osmolytes in Regulating Immune System.

PubMed

Kumar, Tarun; Yadav, Manisha; Singh, Laishram Rajendrakumar

2016-01-01

The immune system has evolved to protect the host organism from diverse range of pathogenic microbes that are themselves constantly evolving. It is a complex network of cells, humoral factors, chemokines and cytokines. Dysregulation of immune system results in various kinds of immunological disorders. There are several external agents which govern the regulation of immune system. Recent studies have indicated the role of osmolytes in regulation of various immunological processes such as Ag-Ab interaction, Ig assembly, Ag presentation etc. In this present review, we have systematically discussed the role of osmolytes involved in regulation of several key immunological processes. Osmolytes are involved in the regulation of several key immunological processes such as immunoglobulin assembly and folding, immune cells proliferation, regulation of immune cells function, Ag-Ab interaction, antigen presentation, inflammatory response and protection against photo-immunosuppression. Hence, osmolytes and their transporters might be used as potential drug and drug targets respectively. This review is therefore designed to help clinicians in development of osmolyte based therapeutic strategies in the treatment of various immunological disorders. Appropriate future perspectives have also been included.

Scanning number and brightness yields absolute protein concentrations in live cells: a crucial parameter controlling functional bio-molecular interaction networks.

PubMed

Papini, Christina; Royer, Catherine A

2018-02-01

Biological function results from properly timed bio-molecular interactions that transduce external or internal signals, resulting in any number of cellular fates, including triggering of cell-state transitions (division, differentiation, transformation, apoptosis), metabolic homeostasis and adjustment to changing physical or nutritional environments, amongst many more. These bio-molecular interactions can be modulated by chemical modifications of proteins, nucleic acids, lipids and other small molecules. They can result in bio-molecular transport from one cellular compartment to the other and often trigger specific enzyme activities involved in bio-molecular synthesis, modification or degradation. Clearly, a mechanistic understanding of any given high level biological function requires a quantitative characterization of the principal bio-molecular interactions involved and how these may change dynamically. Such information can be obtained using fluctation analysis, in particular scanning number and brightness, and used to build and test mechanistic models of the functional network to define which characteristics are the most important for its regulation.

miRNet - dissecting miRNA-target interactions and functional associations through network-based visual analysis

PubMed Central

Fan, Yannan; Siklenka, Keith; Arora, Simran K.; Ribeiro, Paula; Kimmins, Sarah; Xia, Jianguo

2016-01-01

MicroRNAs (miRNAs) can regulate nearly all biological processes and their dysregulation is implicated in various complex diseases and pathological conditions. Recent years have seen a growing number of functional studies of miRNAs using high-throughput experimental technologies, which have produced a large amount of high-quality data regarding miRNA target genes and their interactions with small molecules, long non-coding RNAs, epigenetic modifiers, disease associations, etc. These rich sets of information have enabled the creation of comprehensive networks linking miRNAs with various biologically important entities to shed light on their collective functions and regulatory mechanisms. Here, we introduce miRNet, an easy-to-use web-based tool that offers statistical, visual and network-based approaches to help researchers understand miRNAs functions and regulatory mechanisms. The key features of miRNet include: (i) a comprehensive knowledge base integrating high-quality miRNA-target interaction data from 11 databases; (ii) support for differential expression analysis of data from microarray, RNA-seq and quantitative PCR; (iii) implementation of a flexible interface for data filtering, refinement and customization during network creation; (iv) a powerful fully featured network visualization system coupled with enrichment analysis. miRNet offers a comprehensive tool suite to enable statistical analysis and functional interpretation of various data generated from current miRNA studies. miRNet is freely available at http://www.mirnet.ca. PMID:27105848

Coordination of meristem and boundary functions by transcription factors in the SHOOT MERISTEMLESS regulatory network.

PubMed

Scofield, Simon; Murison, Alexander; Jones, Angharad; Fozard, John; Aida, Mitsuhiro; Band, Leah R; Bennett, Malcolm; Murray, James A H

2018-04-30

The Arabidopsis homeodomain transcription factor SHOOT MERISTEMLESS (STM) is crucial for shoot apical meristem (SAM) function, yet the components and structure of the STM gene regulatory network (GRN) are largely unknown. Here, we show that transcriptional regulators are overrepresented among STM-regulated genes and, using these as GRN components in Bayesian network analysis, we infer STM GRN associations and reveal regulatory relationships between STM and factors involved in multiple aspects of SAM function. These include hormone regulation, TCP-mediated control of cell differentiation, AIL/PLT-mediated regulation of pluripotency and phyllotaxis, and specification of meristem-organ boundary zones via CUC1. We demonstrate a direct positive transcriptional feedback loop between STM and CUC1, despite their distinct expression patterns in the meristem and organ boundary, respectively. Our further finding that STM activates expression of the CUC1-targeting microRNA miR164c combined with mathematical modelling provides a potential solution for this apparent contradiction, demonstrating that these proposed regulatory interactions coupled with STM mobility could be sufficient to provide a mechanism for CUC1 localisation at the meristem-organ boundary. Our findings highlight the central role for the STM GRN in coordinating SAM functions. © 2018. Published by The Company of Biologists Ltd.

A high-resolution network model for global gene regulation in Mycobacterium tuberculosis

PubMed Central

Peterson, Eliza J.R.; Reiss, David J.; Turkarslan, Serdar; Minch, Kyle J.; Rustad, Tige; Plaisier, Christopher L.; Longabaugh, William J.R.; Sherman, David R.; Baliga, Nitin S.

2014-01-01

The resilience of Mycobacterium tuberculosis (MTB) is largely due to its ability to effectively counteract and even take advantage of the hostile environments of a host. In order to accelerate the discovery and characterization of these adaptive mechanisms, we have mined a compendium of 2325 publicly available transcriptome profiles of MTB to decipher a predictive, systems-scale gene regulatory network model. The resulting modular organization of 98% of all MTB genes within this regulatory network was rigorously tested using two independently generated datasets: a genome-wide map of 7248 DNA-binding locations for 143 transcription factors (TFs) and global transcriptional consequences of overexpressing 206 TFs. This analysis has discovered specific TFs that mediate conditional co-regulation of genes within 240 modules across 14 distinct environmental contexts. In addition to recapitulating previously characterized regulons, we discovered 454 novel mechanisms for gene regulation during stress, cholesterol utilization and dormancy. Significantly, 183 of these mechanisms act uniquely under conditions experienced during the infection cycle to regulate diverse functions including 23 genes that are essential to host-pathogen interactions. These and other insights underscore the power of a rational, model-driven approach to unearth novel MTB biology that operates under some but not all phases of infection. PMID:25232098

Establishing a Framework for the Ad/Abaxial Regulatory Network of Arabidopsis: Ascertaining Targets of Class III HOMEODOMAIN LEUCINE ZIPPER and KANADI Regulation[W

PubMed Central

Reinhart, Brenda J.; Liu, Tie; Newell, Nicole R.; Magnani, Enrico; Huang, Tengbo; Kerstetter, Randall; Michaels, Scott; Barton, M. Kathryn

2013-01-01

The broadly conserved Class III HOMEODOMAIN LEUCINE ZIPPER (HD-ZIPIII) and KANADI transcription factors have opposing and transformational effects on polarity and growth in all tissues and stages of the plant's life. To obtain a comprehensive understanding of how these factors work, we have identified transcripts that change in response to induced HD-ZIPIII or KANADI function. Additional criteria used to identify high-confidence targets among this set were presence of an adjacent HD-ZIPIII binding site, expression enriched within a subdomain of the shoot apical meristem, mutant phenotype showing defect in polar leaf and/or meristem development, physical interaction between target gene product and HD-ZIPIII protein, opposite regulation by HD-ZIPIII and KANADI, and evolutionary conservation of the regulator–target relationship. We find that HD-ZIPIII and KANADI regulate tissue-specific transcription factors involved in subsidiary developmental decisions, nearly all major hormone pathways, and new actors (such as INDETERMINATE DOMAIN4) in the ad/abaxial regulatory network. Multiple feedback loops regulating HD-ZIPIII and KANADI are identified, as are mechanisms through which HD-ZIPIII and KANADI oppose each other. This work lays the foundation needed to understand the components, structure, and workings of the ad/abaxial regulatory network directing basic plant growth and development. PMID:24076978

Reconstruction of the yeast Snf1 kinase regulatory network reveals its role as a global energy regulator

PubMed Central

Usaite, Renata; Jewett, Michael C; Oliveira, Ana Paula; Yates, John R; Olsson, Lisbeth; Nielsen, Jens

2009-01-01

Highly conserved among eukaryotic cells, the AMP-activated kinase (AMPK) is a central regulator of carbon metabolism. To map the complete network of interactions around AMPK in yeast (Snf1) and to evaluate the role of its regulatory subunit Snf4, we measured global mRNA, protein and metabolite levels in wild type, Δsnf1, Δsnf4, and Δsnf1Δsnf4 knockout strains. Using four newly developed computational tools, including novel DOGMA sub-network analysis, we showed the benefits of three-level ome-data integration to uncover the global Snf1 kinase role in yeast. We for the first time identified Snf1's global regulation on gene and protein expression levels, and showed that yeast Snf1 has a far more extensive function in controlling energy metabolism than reported earlier. Additionally, we identified complementary roles of Snf1 and Snf4. Similar to the function of AMPK in humans, our findings showed that Snf1 is a low-energy checkpoint and that yeast can be used more extensively as a model system for studying the molecular mechanisms underlying the global regulation of AMPK in mammals, failure of which leads to metabolic diseases. PMID:19888214

Detecting microRNAs of high influence on protein functional interaction networks: a prostate cancer case study

PubMed Central

2012-01-01

Background The use of biological molecular network information for diagnostic and prognostic purposes and elucidation of molecular disease mechanism is a key objective in systems biomedicine. The network of regulatory miRNA-target and functional protein interactions is a rich source of information to elucidate the function and the prognostic value of miRNAs in cancer. The objective of this study is to identify miRNAs that have high influence on target protein complexes in prostate cancer as a case study. This could provide biomarkers or therapeutic targets relevant for prostate cancer treatment. Results Our findings demonstrate that a miRNA’s functional role can be explained by its target protein connectivity within a physical and functional interaction network. To detect miRNAs with high influence on target protein modules, we integrated miRNA and mRNA expression profiles with a sequence based miRNA-target network and human functional and physical protein interactions (FPI). miRNAs with high influence on target protein complexes play a role in prostate cancer progression and are promising diagnostic or prognostic biomarkers. We uncovered several miRNA-regulated protein modules which were enriched in focal adhesion and prostate cancer genes. Several miRNAs such as miR-96, miR-182, and miR-143 demonstrated high influence on their target protein complexes and could explain most of the gene expression changes in our analyzed prostate cancer data set. Conclusions We describe a novel method to identify active miRNA-target modules relevant to prostate cancer progression and outcome. miRNAs with high influence on protein networks are valuable biomarkers that can be used in clinical investigations for prostate cancer treatment. PMID:22929553

Revealing the potential pathogenesis of glioma by utilizing a glioma associated protein-protein interaction network.

PubMed

Pan, Weiran; Li, Gang; Yang, Xiaoxiao; Miao, Jinming

2015-04-01

This study aims to explore the potential mechanism of glioma through bioinformatic approaches. The gene expression profile (GSE4290) of glioma tumor and non-tumor samples was downloaded from Gene Expression Omnibus database. A total of 180 samples were available, including 23 non-tumor and 157 tumor samples. Then the raw data were preprocessed using robust multiarray analysis, and 8,890 differentially expressed genes (DEGs) were identified by using t-test (false discovery rate < 0.0005). Furthermore, 16 known glioma related genes were abstracted from Genetic Association Database. After mapping 8,890 DEGs and 16 known glioma related genes to Human Protein Reference Database, a glioma associated protein-protein interaction network (GAPN) was constructed. In addition, 51 sub-networks in GAPN were screened out through Molecular Complex Detection (score ≥ 1), and sub-network 1 was found to have the closest interaction (score = 3). What' more, for the top 10 sub-networks, Gene Ontology (GO) enrichment analysis (p value < 0.05) was performed, and DEGs involved in sub-network 1 and 2, such as BRMS1L and CCNA1, were predicted to regulate cell growth, cell cycle, and DNA replication via interacting with known glioma related genes. Finally, the overlaps of DEGs and human essential, housekeeping, tissue-specific genes were calculated (p value = 1.0, 1.0, and 0.00014, respectively) and visualized by Venn Diagram package in R. About 61% of human tissue-specific genes were DEGs as well. This research shed new light on the pathogenesis of glioma based on DEGs and GAPN, and our findings might provide potential targets for clinical glioma treatment.

Injectable nano-network for glucose-mediated insulin delivery.

PubMed

Gu, Zhen; Aimetti, Alex A; Wang, Qun; Dang, Tram T; Zhang, Yunlong; Veiseh, Omid; Cheng, Hao; Langer, Robert S; Anderson, Daniel G

2013-05-28

Diabetes mellitus, a disorder of glucose regulation, is a global burden affecting 366 million people across the world. An artificial "closed-loop" system able to mimic pancreas activity and release insulin in response to glucose level changes has the potential to improve patient compliance and health. Herein we develop a glucose-mediated release strategy for the self-regulated delivery of insulin using an injectable and acid-degradable polymeric network. Formed by electrostatic interaction between oppositely charged dextran nanoparticles loaded with insulin and glucose-specific enzymes, the nanocomposite-based porous architecture can be dissociated and subsequently release insulin in a hyperglycemic state through the catalytic conversion of glucose into gluconic acid. In vitro insulin release can be modulated in a pulsatile profile in response to glucose concentrations. In vivo studies validated that these formulations provided improved glucose control in type 1 diabetic mice subcutaneously administered with a degradable nano-network. A single injection of the developed nano-network facilitated stabilization of the blood glucose levels in the normoglycemic state (<200 mg/dL) for up to 10 days.

Lysozyme adsorption in pH-responsive hydrogel thin-films: the non-trivial role of acid-base equilibrium.

PubMed

Narambuena, Claudio F; Longo, Gabriel S; Szleifer, Igal

2015-09-07

We develop and apply a molecular theory to study the adsorption of lysozyme on weak polyacid hydrogel films. The theory explicitly accounts for the conformation of the network, the structure of the proteins, the size and shape of all the molecular species, their interactions as well as the chemical equilibrium of each titratable unit of both the protein and the polymer network. The driving forces for adsorption are the electrostatic attractions between the negatively charged network and the positively charged protein. The adsorption is a non-monotonic function of the solution pH, with a maximum in the region between pH 8 and 9 depending on the salt concentration of the solution. The non-monotonic adsorption is the result of increasing negative charge of the network with pH, while the positive charge of the protein decreases. At low pH the network is roughly electroneutral, while at sufficiently high pH the protein is negatively charged. Upon adsorption, the acid-base equilibrium of the different amino acids of the protein shifts in a nontrivial fashion that depends critically on the particular kind of residue and solution composition. Thus, the proteins regulate their charge and enhance adsorption under a wide range of conditions. In particular, adsorption is predicted above the protein isoelectric point where both the solution lysozyme and the polymer network are negatively charged. This behavior occurs because the pH in the interior of the gel is significantly lower than that in the bulk solution and it is also regulated by the adsorption of the protein in order to optimize protein-gel interactions. Under high pH conditions we predict that the protein changes its charge from negative in the solution to positive within the gel. The change occurs within a few nanometers at the interface of the hydrogel film. Our predictions show the non-trivial interplay between acid-base equilibrium, physical interactions and molecular organization under nanoconfined conditions, which leads to non-trivial adsorption behavior that is qualitatively different from what would be predicted from the state of the proteins in the bulk solution.

SporeWeb: an interactive journey through the complete sporulation cycle of Bacillus subtilis.

PubMed

Eijlander, Robyn T; de Jong, Anne; Krawczyk, Antonina O; Holsappel, Siger; Kuipers, Oscar P

2014-01-01

Bacterial spores are a continuous problem for both food-based and health-related industries. Decades of scientific research dedicated towards understanding molecular and gene regulatory aspects of sporulation, spore germination and spore properties have resulted in a wealth of data and information. To facilitate obtaining a complete overview as well as new insights concerning this complex and tightly regulated process, we have developed a database-driven knowledge platform called SporeWeb (http://sporeweb.molgenrug.nl) that focuses on gene regulatory networks during sporulation in the Gram-positive bacterium Bacillus subtilis. Dynamic features allow the user to navigate through all stages of sporulation with review-like descriptions, schematic overviews on transcriptional regulation and detailed information on all regulators and the genes under their control. The Web site supports data acquisition on sporulation genes and their expression, regulon network interactions and direct links to other knowledge platforms or relevant literature. The information found on SporeWeb (including figures and tables) can and will be updated as new information becomes available in the literature. In this way, SporeWeb offers a novel, convenient and timely reference, an information source and a data acquisition tool that will aid in the general understanding of the dynamics of the complete sporulation cycle.

Top-down regulation of default mode activity in spatial visual attention

PubMed Central

Wen, Xiaotong; Liu, Yijun; Yao, Li; Ding, Mingzhou

2013-01-01

Dorsal anterior cingulate and bilateral anterior insula form a task control network (TCN) whose primary function includes initiating and maintaining task-level cognitive set and exerting top-down regulation of sensorimotor processing. The default mode network (DMN), comprising an anatomically distinct set of cortical areas, mediates introspection and self-referential processes. Resting-state data show that TCN and DMN interact. The functional ramifications of their interaction remain elusive. Recording fMRI data from human subjects performing a visual spatial attention task and correlating Granger causal influences with behavioral performance and blood-oxygen-level-dependent (BOLD) activity we report three main findings. First, causal influences from TCN to DMN, i.e., TCN→DMN, are positively correlated with behavioral performance. Second, causal influences from DMN to TCN, i.e., DMN→TCN, are negatively correlated with behavioral performance. Third, stronger DMN→TCN are associated with less elevated BOLD activity in TCN, whereas the relationship between TCN→DMN and DMN BOLD activity is unsystematic. These results suggest that during visual spatial attention, top-down signals from TCN to DMN regulate the activity in DMN to enhance behavioral performance, whereas signals from DMN to TCN, acting possibly as internal noise, interfere with task control, leading to degraded behavioral performance. PMID:23575842

Back to the biology in systems biology: what can we learn from biomolecular networks?

PubMed

Huang, Sui

2004-02-01

Genome-scale molecular networks, including protein interaction and gene regulatory networks, have taken centre stage in the investigation of the burgeoning disciplines of systems biology and biocomplexity. What do networks tell us? Some see in networks simply the comprehensive, detailed description of all cellular pathways, others seek in networks simple, higher-order qualities that emerge from the collective action of the individual pathways. This paper discusses networks from an encompassing category of thinking that will hopefully help readers to bridge the gap between these polarised viewpoints. Systems biology so far has emphasised the characterisation of large pathway maps. Now one has to ask: where is the actual biology in 'systems biology'? As structures midway between genome and phenome, and by serving as an 'extended genotype' or an 'elementary phenotype', molecular networks open a new window to the study of evolution and gene function in complex living systems. For the study of evolution, features in network topology offer a novel starting point for addressing the old debate on the relative contributions of natural selection versus intrinsic constraints to a particular trait. To study the function of genes, it is necessary not only to see them in the context of gene networks, but also to reach beyond describing network topology and to embrace the global dynamics of networks that will reveal higher-order, collective behaviour of the interacting genes. This will pave the way to understanding how the complexity of genome-wide molecular networks collapses to produce a robust whole-cell behaviour that manifests as tightly-regulated switching between distinct cell fates - the basis for multicellular life.

Microenvironment Influences Interaction of Signaling Molecules | Center for Cancer Research

Cancer.gov

Tumor progression depends not only on events that occur within cancer cells but also on the interaction of cancer cells with their environment, which can regulate tumor growth and metastasis and modulate the formation of new blood vessels to nourish the tumor. All cells communicate with other cells around them, including endothelial cells (the cells that make up blood vessels). They also interact with the extracellular matrix (ECM), a network of sugars and proteins that supports cells. Communication between neighboring cells and molecules often occurs through interaction among and between molecules on the cell surface and molecules of the ECM. Defining these interactions should facilitate the development of novel approaches to limit tumor progression.

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

USDA-ARS?s Scientific Manuscript database

Potato leafroll virus (PLRV) produces a readthrough protein (RTP) via translational readthrough of the coat protein amber stop codon. The RTP functions as a structural component of the virion and as a non-incorporated protein in concert with numerous insect and plant proteins to regulate virus movem...

Vertebrate Presynaptic Active Zone Assembly: a Role Accomplished by Diverse Molecular and Cellular Mechanisms.

PubMed

Torres, Viviana I; Inestrosa, Nibaldo C

2018-06-01

Among all the biological systems in vertebrates, the central nervous system (CNS) is the most complex, and its function depends on specialized contacts among neurons called synapses. The assembly and organization of synapses must be exquisitely regulated for a normal brain function and network activity. There has been a tremendous effort in recent decades to understand the molecular and cellular mechanisms participating in the formation of new synapses and their organization, maintenance, and regulation. At the vertebrate presynapses, proteins such as Piccolo, Bassoon, RIM, RIM-BPs, CAST/ELKS, liprin-α, and Munc13 are constant residents and participate in multiple and dynamic interactions with other regulatory proteins, which define network activity and normal brain function. Here, we review the function of these active zone (AZ) proteins and diverse factors involved in AZ assembly and maintenance, with an emphasis on axonal trafficking of precursor vesicles, protein homo- and hetero-oligomeric interactions as a mechanism of AZ trapping and stabilization, and the role of F-actin in presynaptic assembly and its modulation by Wnt signaling.

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

PubMed

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

2016-12-15

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

Characterizing genes with distinct methylation patterns in the context of protein-protein interaction network: application to human brain tissues.

PubMed

Li, Yongsheng; Xu, Juan; Chen, Hong; Zhao, Zheng; Li, Shengli; Bai, Jing; Wu, Aiwei; Jiang, Chunjie; Wang, Yuan; Su, Bin; Li, Xia

2013-01-01

DNA methylation is an essential epigenetic mechanism involved in transcriptional control. However, how genes with different methylation patterns are assembled in the protein-protein interaction network (PPIN) remains a mystery. In the present study, we systematically dissected the characterization of genes with different methylation patterns in the PPIN. A negative association was detected between the methylation levels in the brain tissues and topological centralities. By focusing on two classes of genes with considerably different methylation levels in the brain tissues, namely the low methylated genes (LMGs) and high methylated genes (HMGs), we found that their organizing principles in the PPIN are distinct. The LMGs tend to be the center of the PPIN, and attacking them causes a more deleterious effect on the network integrity. Furthermore, the LMGs express their functions in a modular pattern and substantial differences in functions are observed between the two types of genes. The LMGs are enriched in the basic biological functions, such as binding activity and regulation of transcription. More importantly, cancer genes, especially recessive cancer genes, essential genes, and aging-related genes were all found more often in the LMGs. Additionally, our analysis presented that the intra-classes communications are enhanced, but inter-classes communications are repressed. Finally, a functional complementation was revealed between methylation and miRNA regulation in the human genome. We have elucidated the assembling principles of genes with different methylation levels in the context of the PPIN, providing key insights into the complex epigenetic regulation mechanisms.

Characterizing Genes with Distinct Methylation Patterns in the Context of Protein-Protein Interaction Network: Application to Human Brain Tissues

PubMed Central

Zhao, Zheng; Li, Shengli; Bai, Jing; Wu, Aiwei; Jiang, Chunjie; Wang, Yuan; Su, Bin; Li, Xia

2013-01-01

Background DNA methylation is an essential epigenetic mechanism involved in transcriptional control. However, how genes with different methylation patterns are assembled in the protein-protein interaction network (PPIN) remains a mystery. Results In the present study, we systematically dissected the characterization of genes with different methylation patterns in the PPIN. A negative association was detected between the methylation levels in the brain tissues and topological centralities. By focusing on two classes of genes with considerably different methylation levels in the brain tissues, namely the low methylated genes (LMGs) and high methylated genes (HMGs), we found that their organizing principles in the PPIN are distinct. The LMGs tend to be the center of the PPIN, and attacking them causes a more deleterious effect on the network integrity. Furthermore, the LMGs express their functions in a modular pattern and substantial differences in functions are observed between the two types of genes. The LMGs are enriched in the basic biological functions, such as binding activity and regulation of transcription. More importantly, cancer genes, especially recessive cancer genes, essential genes, and aging-related genes were all found more often in the LMGs. Additionally, our analysis presented that the intra-classes communications are enhanced, but inter-classes communications are repressed. Finally, a functional complementation was revealed between methylation and miRNA regulation in the human genome. Conclusions We have elucidated the assembling principles of genes with different methylation levels in the context of the PPIN, providing key insights into the complex epigenetic regulation mechanisms. PMID:23776563

Identification of cancer-related miRNA-lncRNA biomarkers using a basic miRNA-lncRNA network.

PubMed

Zhang, Guangle; Pian, Cong; Chen, Zhi; Zhang, Jin; Xu, Mingmin; Zhang, Liangyun; Chen, Yuanyuan

2018-01-01

LncRNAs are regulatory noncoding RNAs that play crucial roles in many biological processes. The dysregulation of lncRNA is thought to be involved in many complex diseases; lncRNAs are often the targets of miRNAs in the indirect regulation of gene expression. Numerous studies have indicated that miRNA-lncRNA interactions are closely related to the occurrence and development of cancers. Thus, it is important to develop an effective method for the identification of cancer-related miRNA-lncRNA interactions. In this study, we compiled 155653 experimentally validated and predicted miRNA-lncRNA associations, which we defined as basic interactions. We next constructed an individual-specific miRNA-lncRNA network (ISMLN) for each cancer sample and a basic miRNA-lncRNA network (BMLN) for each type of cancer by examining the expression profiles of miRNAs and lncRNAs in the TCGA (The Cancer Genome Atlas) database. We then selected potential miRNA-lncRNA biomarkers based on the BLMN. Using this method, we identified cancer-related miRNA-lncRNA biomarkers and modules specific to a certain cancer. This method of profiling will contribute to the diagnosis and treatment of cancers at the level of gene regulatory networks.

Correlated miR-mRNA expression signatures of mouse hematopoietic stem and progenitor cell subsets predict "Stemness" and "Myeloid" interaction networks.

PubMed

Heiser, Diane; Tan, Yee Sun; Kaplan, Ian; Godsey, Brian; Morisot, Sebastien; Cheng, Wen-Chih; Small, Donald; Civin, Curt I

2014-01-01

Several individual miRNAs (miRs) have been implicated as potent regulators of important processes during normal and malignant hematopoiesis. In addition, many miRs have been shown to fine-tune intricate molecular networks, in concert with other regulatory elements. In order to study hematopoietic networks as a whole, we first created a map of global miR expression during early murine hematopoiesis. Next, we determined the copy number per cell for each miR in each of the examined stem and progenitor cell types. As data is emerging indicating that miRs function robustly mainly when they are expressed above a certain threshold (∼100 copies per cell), our database provides a resource for determining which miRs are expressed at a potentially functional level in each cell type. Finally, we combine our miR expression map with matched mRNA expression data and external prediction algorithms, using a Bayesian modeling approach to create a global landscape of predicted miR-mRNA interactions within each of these hematopoietic stem and progenitor cell subsets. This approach implicates several interaction networks comprising a "stemness" signature in the most primitive hematopoietic stem cell (HSC) populations, as well as "myeloid" patterns associated with two branches of myeloid development.

Recycling Endosomes and Viral Infection.

PubMed

Vale-Costa, Sílvia; Amorim, Maria João

2016-03-08

Many viruses exploit specific arms of the endomembrane system. The unique composition of each arm prompts the development of remarkably specific interactions between viruses and sub-organelles. This review focuses on the viral-host interactions occurring on the endocytic recycling compartment (ERC), and mediated by its regulatory Ras-related in brain (Rab) GTPase Rab11. This protein regulates trafficking from the ERC and the trans-Golgi network to the plasma membrane. Such transport comprises intricate networks of proteins/lipids operating sequentially from the membrane of origin up to the cell surface. Rab11 is also emerging as a critical factor in an increasing number of infections by major animal viruses, including pathogens that provoke human disease. Understanding the interplay between the ERC and viruses is a milestone in human health. Rab11 has been associated with several steps of the viral lifecycles by unclear processes that use sophisticated diversified host machinery. For this reason, we first explore the state-of-the-art on processes regulating membrane composition and trafficking. Subsequently, this review outlines viral interactions with the ERC, highlighting current knowledge on viral-host binding partners. Finally, using examples from the few mechanistic studies available we emphasize how ERC functions are adjusted during infection to remodel cytoskeleton dynamics, innate immunity and membrane composition.

Dissecting the chromatin interactome of microRNA genes.

PubMed

Chen, Dijun; Fu, Liang-Yu; Zhang, Zhao; Li, Guoliang; Zhang, Hang; Jiang, Li; Harrison, Andrew P; Shanahan, Hugh P; Klukas, Christian; Zhang, Hong-Yu; Ruan, Yijun; Chen, Ling-Ling; Chen, Ming

2014-03-01

Our knowledge of the role of higher-order chromatin structures in transcription of microRNA genes (MIRs) is evolving rapidly. Here we investigate the effect of 3D architecture of chromatin on the transcriptional regulation of MIRs. We demonstrate that MIRs have transcriptional features that are similar to protein-coding genes. RNA polymerase II-associated ChIA-PET data reveal that many groups of MIRs and protein-coding genes are organized into functionally compartmentalized chromatin communities and undergo coordinated expression when their genomic loci are spatially colocated. We observe that MIRs display widespread communication in those transcriptionally active communities. Moreover, miRNA-target interactions are significantly enriched among communities with functional homogeneity while depleted from the same community from which they originated, suggesting MIRs coordinating function-related pathways at posttranscriptional level. Further investigation demonstrates the existence of spatial MIR-MIR chromatin interacting networks. We show that groups of spatially coordinated MIRs are frequently from the same family and involved in the same disease category. The spatial interaction network possesses both common and cell-specific subnetwork modules that result from the spatial organization of chromatin within different cell types. Together, our study unveils an entirely unexplored layer of MIR regulation throughout the human genome that links the spatial coordination of MIRs to their co-expression and function.

A novel functional domain of Cdc15 kinase is required for its interaction with Tem1 GTPase in Saccharomyces cerevisiae.

PubMed Central

Asakawa, K; Yoshida, S; Otake, F; Toh-e, A

2001-01-01

Exit from mitosis requires the inactivation of cyclin-dependent kinase (CDK) activity. In the budding yeast Saccharomyces cerevisiae, a number of gene products have been identified as components of the signal transduction network regulating inactivation of CDK (called the MEN, for the mitotic exit network). Cdc15, one of such components of the MEN, is an essential protein kinase. By the two-hybrid screening, we identified Cdc15 as a binding protein of Tem1 GTPase, another essential regulator of the MEN. Coprecipitation experiments revealed that Tem1 binds to Cdc15 in vivo. By deletion analysis, we found that the Tem1-binding domain resides near the conserved kinase domain of Cdc15. The cdc15-LF mutation, which was introduced into the Tem1-binding domain, reduced the interaction with Cdc15 and Tem1 and caused temperature-sensitive growth.The kinase activity of Cdc15 was not so much affected by the cdc15-LF mutation. However, Cdc15-LF failed to localize to the SPB at the restrictive temperature. Our data show that the interaction with Tem1 is important for the function of Cdc15 and that Cdc15 and Tem1 function in a complex to direct the exit from mitosis. PMID:11290702

Recycling Endosomes and Viral Infection

PubMed Central

Vale-Costa, Sílvia; Amorim, Maria João

2016-01-01

Many viruses exploit specific arms of the endomembrane system. The unique composition of each arm prompts the development of remarkably specific interactions between viruses and sub-organelles. This review focuses on the viral–host interactions occurring on the endocytic recycling compartment (ERC), and mediated by its regulatory Ras-related in brain (Rab) GTPase Rab11. This protein regulates trafficking from the ERC and the trans-Golgi network to the plasma membrane. Such transport comprises intricate networks of proteins/lipids operating sequentially from the membrane of origin up to the cell surface. Rab11 is also emerging as a critical factor in an increasing number of infections by major animal viruses, including pathogens that provoke human disease. Understanding the interplay between the ERC and viruses is a milestone in human health. Rab11 has been associated with several steps of the viral lifecycles by unclear processes that use sophisticated diversified host machinery. For this reason, we first explore the state-of-the-art on processes regulating membrane composition and trafficking. Subsequently, this review outlines viral interactions with the ERC, highlighting current knowledge on viral-host binding partners. Finally, using examples from the few mechanistic studies available we emphasize how ERC functions are adjusted during infection to remodel cytoskeleton dynamics, innate immunity and membrane composition. PMID:27005655

System in biology leading to cell pathology: stable protein-protein interactions after covalent modifications by small molecules or in transgenic cells.

PubMed

Malina, Halina Z

2011-01-19

The physiological processes in the cell are regulated by reversible, electrostatic protein-protein interactions. Apoptosis is such a regulated process, which is critically important in tissue homeostasis and development and leads to complete disintegration of the cell. Pathological apoptosis, a process similar to apoptosis, is associated with aging and infection. The current study shows that pathological apoptosis is a process caused by the covalent interactions between the signaling proteins, and a characteristic of this pathological network is the covalent binding of calmodulin to regulatory sequences. Small molecules able to bind covalently to the amino group of lysine, histidine, arginine, or glutamine modify the regulatory sequences of the proteins. The present study analyzed the interaction of calmodulin with the BH3 sequence of Bax, and the calmodulin-binding sequence of myristoylated alanine-rich C-kinase substrate in the presence of xanthurenic acid in primary retinal epithelium cell cultures and murine epithelial fibroblast cell lines transformed with SV40 (wild type [WT], Bid knockout [Bid-/-], and Bax-/-/Bak-/- double knockout [DKO]). Cell death was observed to be associated with the covalent binding of calmodulin, in parallel, to the regulatory sequences of proteins. Xanthurenic acid is known to activate caspase-3 in primary cell cultures, and the results showed that this activation is also observed in WT and Bid-/- cells, but not in DKO cells. However, DKO cells were not protected against death, but high rates of cell death occurred by detachment. The results showed that small molecules modify the basic amino acids in the regulatory sequences of proteins leading to covalent interactions between the modified sequences (e.g., calmodulin to calmodulin-binding sites). The formation of these polymers (aggregates) leads to an unregulated and, consequently, pathological protein network. The results suggest a mechanism for the involvement of small molecules in disease development. In the knockout cells, incorrect interactions between proteins were observed without the protein modification by small molecules, indicating the abnormality of the protein network in the transgenic system. The irreversible protein-protein interactions lead to protein aggregation and cell degeneration, which are observed in all aging-associated diseases.

System in biology leading to cell pathology: stable protein-protein interactions after covalent modifications by small molecules or in transgenic cells

PubMed Central

2011-01-01

Background The physiological processes in the cell are regulated by reversible, electrostatic protein-protein interactions. Apoptosis is such a regulated process, which is critically important in tissue homeostasis and development and leads to complete disintegration of the cell. Pathological apoptosis, a process similar to apoptosis, is associated with aging and infection. The current study shows that pathological apoptosis is a process caused by the covalent interactions between the signaling proteins, and a characteristic of this pathological network is the covalent binding of calmodulin to regulatory sequences. Results Small molecules able to bind covalently to the amino group of lysine, histidine, arginine, or glutamine modify the regulatory sequences of the proteins. The present study analyzed the interaction of calmodulin with the BH3 sequence of Bax, and the calmodulin-binding sequence of myristoylated alanine-rich C-kinase substrate in the presence of xanthurenic acid in primary retinal epithelium cell cultures and murine epithelial fibroblast cell lines transformed with SV40 (wild type [WT], Bid knockout [Bid-/-], and Bax-/-/Bak-/- double knockout [DKO]). Cell death was observed to be associated with the covalent binding of calmodulin, in parallel, to the regulatory sequences of proteins. Xanthurenic acid is known to activate caspase-3 in primary cell cultures, and the results showed that this activation is also observed in WT and Bid-/- cells, but not in DKO cells. However, DKO cells were not protected against death, but high rates of cell death occurred by detachment. Conclusions The results showed that small molecules modify the basic amino acids in the regulatory sequences of proteins leading to covalent interactions between the modified sequences (e.g., calmodulin to calmodulin-binding sites). The formation of these polymers (aggregates) leads to an unregulated and, consequently, pathological protein network. The results suggest a mechanism for the involvement of small molecules in disease development. In the knockout cells, incorrect interactions between proteins were observed without the protein modification by small molecules, indicating the abnormality of the protein network in the transgenic system. The irreversible protein-protein interactions lead to protein aggregation and cell degeneration, which are observed in all aging-associated diseases. PMID:21247434

A Protein Preparation Method for the High-throughput Identification of Proteins Interacting with a Nuclear Cofactor Using LC-MS/MS Analysis.

PubMed

Tsuchiya, Megumi; Karim, M Rezaul; Matsumoto, Taro; Ogawa, Hidesato; Taniguchi, Hiroaki

2017-01-24

Transcriptional coregulators are vital to the efficient transcriptional regulation of nuclear chromatin structure. Coregulators play a variety of roles in regulating transcription. These include the direct interaction with transcription factors, the covalent modification of histones and other proteins, and the occasional chromatin conformation alteration. Accordingly, establishing relatively quick methods for identifying proteins that interact within this network is crucial to enhancing our understanding of the underlying regulatory mechanisms. LC-MS/MS-mediated protein binding partner identification is a validated technique used to analyze protein-protein interactions. By immunoprecipitating a previously-identified member of a protein complex with an antibody (occasionally with an antibody for a tagged protein), it is possible to identify its unknown protein interactions via mass spectrometry analysis. Here, we present a method of protein preparation for the LC-MS/MS-mediated high-throughput identification of protein interactions involving nuclear cofactors and their binding partners. This method allows for a better understanding of the transcriptional regulatory mechanisms of the targeted nuclear factors.

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

PubMed

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

2017-12-01

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

Mena/VASP and αII-Spectrin complexes regulate cytoplasmic actin networks in cardiomyocytes and protect from conduction abnormalities and dilated cardiomyopathy

PubMed Central

2013-01-01

Background In the heart, cytoplasmic actin networks are thought to have important roles in mechanical support, myofibrillogenesis, and ion channel function. However, subcellular localization of cytoplasmic actin isoforms and proteins involved in the modulation of the cytoplasmic actin networks are elusive. Mena and VASP are important regulators of actin dynamics. Due to the lethal phenotype of mice with combined deficiency in Mena and VASP, however, distinct cardiac roles of the proteins remain speculative. In the present study, we analyzed the physiological functions of Mena and VASP in the heart and also investigated the role of the proteins in the organization of cytoplasmic actin networks. Results We generated a mouse model, which simultaneously lacks Mena and VASP in the heart. Mena/VASP double-deficiency induced dilated cardiomyopathy and conduction abnormalities. In wild-type mice, Mena and VASP specifically interacted with a distinct αII-Spectrin splice variant (SH3i), which is in cardiomyocytes exclusively localized at Z- and intercalated discs. At Z- and intercalated discs, Mena and β-actin localized to the edges of the sarcomeres, where the thin filaments are anchored. In Mena/VASP double-deficient mice, β-actin networks were disrupted and the integrity of Z- and intercalated discs was markedly impaired. Conclusions Together, our data suggest that Mena, VASP, and αII-Spectrin assemble cardiac multi-protein complexes, which regulate cytoplasmic actin networks. Conversely, Mena/VASP deficiency results in disrupted β-actin assembly, Z- and intercalated disc malformation, and induces dilated cardiomyopathy and conduction abnormalities. PMID:23937664

Mena/VASP and αII-Spectrin complexes regulate cytoplasmic actin networks in cardiomyocytes and protect from conduction abnormalities and dilated cardiomyopathy.

PubMed

Benz, Peter M; Merkel, Carla J; Offner, Kristin; Abeßer, Marco; Ullrich, Melanie; Fischer, Tobias; Bayer, Barbara; Wagner, Helga; Gambaryan, Stepan; Ursitti, Jeanine A; Adham, Ibrahim M; Linke, Wolfgang A; Feller, Stephan M; Fleming, Ingrid; Renné, Thomas; Frantz, Stefan; Unger, Andreas; Schuh, Kai

2013-08-12

In the heart, cytoplasmic actin networks are thought to have important roles in mechanical support, myofibrillogenesis, and ion channel function. However, subcellular localization of cytoplasmic actin isoforms and proteins involved in the modulation of the cytoplasmic actin networks are elusive. Mena and VASP are important regulators of actin dynamics. Due to the lethal phenotype of mice with combined deficiency in Mena and VASP, however, distinct cardiac roles of the proteins remain speculative. In the present study, we analyzed the physiological functions of Mena and VASP in the heart and also investigated the role of the proteins in the organization of cytoplasmic actin networks. We generated a mouse model, which simultaneously lacks Mena and VASP in the heart. Mena/VASP double-deficiency induced dilated cardiomyopathy and conduction abnormalities. In wild-type mice, Mena and VASP specifically interacted with a distinct αII-Spectrin splice variant (SH3i), which is in cardiomyocytes exclusively localized at Z- and intercalated discs. At Z- and intercalated discs, Mena and β-actin localized to the edges of the sarcomeres, where the thin filaments are anchored. In Mena/VASP double-deficient mice, β-actin networks were disrupted and the integrity of Z- and intercalated discs was markedly impaired. Together, our data suggest that Mena, VASP, and αII-Spectrin assemble cardiac multi-protein complexes, which regulate cytoplasmic actin networks. Conversely, Mena/VASP deficiency results in disrupted β-actin assembly, Z- and intercalated disc malformation, and induces dilated cardiomyopathy and conduction abnormalities.

Combining affinity proteomics and network context to identify new phosphatase substrates and adapters in growth pathways

PubMed Central

Sacco, Francesca; Boldt, Karsten; Calderone, Alberto; Panni, Simona; Paoluzi, Serena; Castagnoli, Luisa; Ueffing, Marius; Cesareni, Gianni

2014-01-01

Protein phosphorylation homoeostasis is tightly controlled and pathological conditions are caused by subtle alterations of the cell phosphorylation profile. Altered levels of kinase activities have already been associated to specific diseases. Less is known about the impact of phosphatases, the enzymes that down-regulate phosphorylation by removing the phosphate groups. This is partly due to our poor understanding of the phosphatase-substrate network. Much of phosphatase substrate specificity is not based on intrinsic enzyme specificity with the catalytic pocket recognizing the sequence/structure context of the phosphorylated residue. In addition many phosphatase catalytic subunits do not form a stable complex with their substrates. This makes the inference and validation of phosphatase substrates a non-trivial task. Here, we present a novel approach that builds on the observation that much of phosphatase substrate selection is based on the network of physical interactions linking the phosphatase to the substrate. We first used affinity proteomics coupled to quantitative mass spectrometry to saturate the interactome of eight phosphatases whose down regulations was shown to affect the activation of the RAS-PI3K pathway. By integrating information from functional siRNA with protein interaction information, we develop a strategy that aims at inferring phosphatase physiological substrates. Graph analysis is used to identify protein scaffolds that may link the catalytic subunits to their substrates. By this approach we rediscover several previously described phosphatase substrate interactions and characterize two new protein scaffolds that promote the dephosphorylation of PTPN11 and ERK by DUSP18 and DUSP26, respectively. PMID:24847354

Shifted intrinsic connectivity of central executive and salience network in borderline personality disorder

PubMed Central

Doll, Anselm; Sorg, Christian; Manoliu, Andrei; Wöller, Andreas; Meng, Chun; Förstl, Hans; Zimmer, Claus; Wohlschläger, Afra M.; Riedl, Valentin

2013-01-01

Borderline personality disorder (BPD) is characterized by “stable instability” of emotions and behavior and their regulation. This emotional and behavioral instability corresponds with a neurocognitive triple network model of psychopathology, which suggests that aberrant emotional saliency and cognitive control is associated with aberrant interaction across three intrinsic connectivity networks [i.e., the salience network (SN), default mode network (DMN), and central executive network (CEN)]. The objective of the current study was to investigate whether and how such triple network intrinsic functional connectivity (iFC) is changed in patients with BPD. We acquired resting-state functional magnetic resonance imaging (rs-fMRI) data from 14 patients with BPD and 16 healthy controls. High-model order independent component analysis was used to extract spatiotemporal patterns of ongoing, coherent blood-oxygen-level-dependent signal fluctuations from rs-fMRI data. Main outcome measures were iFC within networks (intra-iFC) and between networks (i.e., network time course correlation inter-iFC). Aberrant intra-iFC was found in patients’ DMN, SN, and CEN, consistent with previous findings. While patients’ inter-iFC of the CEN was decreased, inter-iFC of the SN was increased. In particular, a balance index reflecting the relationship of CEN- and SN-inter-iFC across networks was strongly shifted from CEN to SN connectivity in patients. Results provide first preliminary evidence for aberrant triple network iFC in BPD. Our data suggest a shift of inter-network iFC from networks involved in cognitive control to those of emotion-related activity in BPD, potentially reflecting the persistent instability of emotion regulation in patients. PMID:24198777

Systematic transcriptome-wide analysis of mRNA-miRNA interactions reveals the involvement of miR-142-5p and its target (FOXO3) in skeletal muscle growth in chickens.

PubMed

Li, Zhenhui; Abdalla, Bahareldin Ali; Zheng, Ming; He, Xiaomei; Cai, Bolin; Han, Peigong; Ouyang, Hongjia; Chen, Biao; Nie, Qinghua; Zhang, Xiquan

2018-02-01

The goal of this study was to perform a systematic transcriptome-wide analysis of mRNA-miRNA interactions and to identify candidates involved in the interplay between miRNAs and mRNAs that regulate chicken muscle growth. We used our previously published mRNA (GSE72424) and miRNA (GSE62971) deep sequencing data from two-tailed samples [i.e., the highest (h) and lowest (l) body weights] of Recessive White Rock (WRR) and Xinghua (XH) chickens to conduct integrative analyses of the miRNA-mRNA interactions involved in chicken skeletal muscle growth. A total of 162, 15, 173, and 27 miRNA-mRNA pairs with negatively correlated expression patterns were identified in miRNA-mRNA networks constructed on the basis of the WRR h vs. XH h , WRR h vs. WRR l , WRR l vs. XH l , and XH h vs. XH l comparisons, respectively. Ingenuity Pathway Analysis revealed that gene networks identified for the WRR h vs. XH h contrast were associated with developmental disorders. Importantly, the WRR h vs. XH h contrast miRNA-mRNA network was enriched in IGF-1 signaling pathway genes, including FOXO3. A dual-luciferase reporter assay showed that FOXO3 was a target of miR-142-5p. Furthermore, miR-142-5p overexpression significantly decreased FOXO3 mRNA levels and promoted the expression of growth-related genes. These data demonstrated that miR-142-5p targets FOXO3 and promotes growth-related gene expression and regulates skeletal muscle growth in chicken. Comprehensive analysis facilitated the identification of miRNAs and target genes that might contribute to the regulation of skeletal muscle development. Our results provide new clues for understanding the molecular basis of chicken growth.

Network Analyses Reveal Pervasive Functional Regulation Between Proteases in the Human Protease Web

PubMed Central

Fortelny, Nikolaus; Cox, Jennifer H.; Kappelhoff, Reinhild; Starr, Amanda E.; Lange, Philipp F.; Pavlidis, Paul; Overall, Christopher M.

2014-01-01

Proteolytic processing is an irreversible posttranslational modification affecting a large portion of the proteome. Protease-cleaved mediators frequently exhibit altered activity, and biological pathways are often regulated by proteolytic processing. Many of these mechanisms have not been appreciated as being protease-dependent, and the potential in unraveling a complex new dimension of biological control is increasingly recognized. Proteases are currently believed to act individually or in isolated cascades. However, conclusive but scattered biochemical evidence indicates broader regulation of proteases by protease and inhibitor interactions. Therefore, to systematically study such interactions, we assembled curated protease cleavage and inhibition data into a global, computational representation, termed the protease web. This revealed that proteases pervasively influence the activity of other proteases directly or by cleaving intermediate proteases or protease inhibitors. The protease web spans four classes of proteases and inhibitors and so links both recently and classically described protease groups and cascades, which can no longer be viewed as operating in isolation in vivo. We demonstrated that this observation, termed reachability, is robust to alterations in the data and will only increase in the future as additional data are added. We further show how subnetworks of the web are operational in 23 different tissues reflecting different phenotypes. We applied our network to develop novel insights into biologically relevant protease interactions using cell-specific proteases of the polymorphonuclear leukocyte as a system. Predictions from the protease web on the activity of matrix metalloproteinase 8 (MMP8) and neutrophil elastase being linked by an inactivating cleavage of serpinA1 by MMP8 were validated and explain perplexing Mmp8 −/− versus wild-type polymorphonuclear chemokine cleavages in vivo. Our findings supply systematically derived and validated evidence for the existence of the protease web, a network that affects the activity of most proteases and thereby influences the functional state of the proteome and cell activity. PMID:24865846

Mathematical model of a gene regulatory network reconciles effects of genetic perturbations on hematopoietic stem cell emergence.

PubMed

Narula, Jatin; Williams, C J; Tiwari, Abhinav; Marks-Bluth, Jonathon; Pimanda, John E; Igoshin, Oleg A

2013-07-15

Interlinked gene regulatory networks (GRNs) are vital for the spatial and temporal control of gene expression during development. The hematopoietic transcription factors (TFs) Scl, Gata2 and Fli1 form one such densely connected GRN which acts as a master regulator of embryonic hematopoiesis. This triad has been shown to direct the specification of the hemogenic endothelium and emergence of hematopoietic stem cells (HSCs) in response to Notch1 and Bmp4-Smad signaling. Here we employ previously published data to construct a mathematical model of this GRN network and use this model to systematically investigate the network dynamical properties. Our model uses a statistical-thermodynamic framework to describe the combinatorial regulation of gene expression and reconciles, mechanistically, several previously published but unexplained results from different genetic perturbation experiments. In particular, our results demonstrate how the interactions of Runx1, an essential hematopoietic TF, with components of the Bmp4 signaling pathway allow it to affect triad activation and acts as a key regulator of HSC emergence. We also explain why heterozygous deletion of this essential TF, Runx1, speeds up the network dynamics leading to accelerated HSC emergence. Taken together our results demonstrate that the triad, a master-level controller of definitive hematopoiesis, is an irreversible bistable switch whose dynamical properties are modulated by Runx1 and components of the Bmp4 signaling pathway. Copyright © 2013 Elsevier Inc. All rights reserved.

Transcriptome comparison and gene coexpression network analysis provide a systems view of citrus response to ‘Candidatus Liberibacter asiaticus’ infection

PubMed Central

2013-01-01

Background Huanglongbing (HLB) is arguably the most destructive disease for the citrus industry. HLB is caused by infection of the bacterium, Candidatus Liberibacter spp. Several citrus GeneChip studies have revealed thousands of genes that are up- or down-regulated by infection with Ca. Liberibacter asiaticus. However, whether and how these host genes act to protect against HLB remains poorly understood. Results As a first step towards a mechanistic view of citrus in response to the HLB bacterial infection, we performed a comparative transcriptome analysis and found that a total of 21 Probesets are commonly up-regulated by the HLB bacterial infection. In addition, a number of genes are likely regulated specifically at early, late or very late stages of the infection. Furthermore, using Pearson correlation coefficient-based gene coexpression analysis, we constructed a citrus HLB response network consisting of 3,507 Probesets and 56,287 interactions. Genes involved in carbohydrate and nitrogen metabolic processes, transport, defense, signaling and hormone response were overrepresented in the HLB response network and the subnetworks for these processes were constructed. Analysis of the defense and hormone response subnetworks indicates that hormone response is interconnected with defense response. In addition, mapping the commonly up-regulated HLB responsive genes into the HLB response network resulted in a core subnetwork where transport plays a key role in the citrus response to the HLB bacterial infection. Moreover, analysis of a phloem protein subnetwork indicates a role for this protein and zinc transporters or zinc-binding proteins in the citrus HLB defense response. Conclusion Through integrating transcriptome comparison and gene coexpression network analysis, we have provided for the first time a systems view of citrus in response to the Ca. Liberibacter spp. infection causing HLB. PMID:23324561

The Caenorhabditis elegans vulva: A post-embryonic gene regulatory network controlling organogenesis

PubMed Central

Ririe, Ted O.; Fernandes, Jolene S.; Sternberg, Paul W.

2008-01-01

The Caenorhabditis elegans vulva is an elegant model for dissecting a gene regulatory network (GRN) that directs postembryonic organogenesis. The mature vulva comprises seven cell types (vulA, vulB1, vulB2, vulC, vulD, vulE, and vulF), each with its own unique pattern of spatial and temporal gene expression. The mechanisms that specify these cell types in a precise spatial pattern are not well understood. Using reverse genetic screens, we identified novel components of the vulval GRN, including nhr-113 in vulA. Several transcription factors (lin-11, lin-29, cog-1, egl-38, and nhr-67) interact with each other and act in concert to regulate target gene expression in the diverse vulval cell types. For example, egl-38 (Pax2/5/8) stabilizes the vulF fate by positively regulating vulF characteristics and by inhibiting characteristics associated with the neighboring vulE cells. nhr-67 and egl-38 regulate cog-1, helping restrict its expression to vulE. Computational approaches have been successfully used to identify functional cis-regulatory motifs in the zmp-1 (zinc metalloproteinase) promoter. These results provide an overview of the regulatory network architecture for each vulval cell type. PMID:19104047

Single-Molecule Studies of Actin Assembly and Disassembly Factors

PubMed Central

Smith, Benjamin A.; Gelles, Jeff; Goode, Bruce L.

2014-01-01

The actin cytoskeleton is very dynamic and highly regulated by multiple associated proteins in vivo. Understanding how this system of proteins functions in the processes of actin network assembly and disassembly requires methods to dissect the mechanisms of activity of individual factors and of multiple factors acting in concert. The advent of single-filament and single-molecule fluorescence imaging methods has provided a powerful new approach to discovering actin-regulatory activities and obtaining direct, quantitative insights into the pathways of molecular interactions that regulate actin network architecture and dynamics. Here we describe techniques for acquisition and analysis of single-molecule data, applied to the novel challenges of studying the filament assembly and disassembly activities of actin-associated proteins in vitro. We discuss the advantages of single-molecule analysis in directly visualizing the order of molecular events, measuring the kinetic rates of filament binding and dissociation, and studying the coordination among multiple factors. The methods described here complement traditional biochemical approaches in elucidating actin-regulatory mechanisms in reconstituted filamentous networks. PMID:24630103

Social media: physicians-to-physicians education and communication.

PubMed

Fehring, Keith A; De Martino, Ivan; McLawhorn, Alexander S; Sculco, Peter K

2017-06-01

Physician to physician communication is essential for the transfer of ideas, surgical experience, and education. Social networks and online video educational contents have grown exponentially in recent years changing the interaction among physicians. Social media platforms can improve physician-to-physician communication mostly through video education and social networking. There are several online video platforms for orthopedic surgery with educational content on diagnosis, treatment, outcomes, and surgical technique. Social networking instead is mostly centered on sharing of data, discussion of confidential topics, and job seeking. Quality of educational contents and data confidentiality represent the major drawbacks of these platforms. Orthopedic surgeons must be aware that the quality of the videos should be better controlled and regulated to avoid inaccurate information that may have a significant impact especially on trainees that are more prone to use this type of resources. Sharing of data and discussion of confidential topics should be extremely secure according the HIPAA regulations in order to protect patients' confidentiality.

The Signaling Networks of the Herpesvirus Entry Mediator (TNFRSF14) in Immune Regulation

PubMed Central

Steinberg, Marcos; Cheung, Timothy C.; Ware, Carl F.

2012-01-01

Summary The tumor necrosis factor (TNF) receptor superfamily member herpesvirus entry mediator (HVEM) (TNFRSF14) regulates T-cell immune responses by activating both inflammatory and inhibitory signaling pathways. HVEM acts as both a receptor for the canonical TNF-related ligands, LIGHT [lymphotoxin-like, exhibits inducible expression, and competes with herpes simplex virus glycoprotein D for HVEM, a receptor expressed on T lymphocytes] and lymphotoxin-α, and as a ligand for the immunoglobulin superfamily proteins BTLA (B and T lymphocyte attenuator) and CD160, a feature distinguishing HVEM from other immune regulatory molecules. The ability of HVEM to interact with multiple ligands in distinct configurations creates a functionally diverse set of intrinsic and bidirectional signaling pathways that control both inflammatory and inhibitory responses. The HVEM system is integrated into the larger LTβR and TNFR network through extensive shared ligand and receptor usage. Experimental mouse models and human diseases indicate that dysregulation of HVEM network may contribute to autoimmune pathogenesis, making it an attractive target for drug intervention. PMID:22017438

Dense fibrillar collagen is a potent inducer of invadopodia via a specific signaling network

PubMed Central

Swatkoski, Stephen; Matsumoto, Kazue; Campbell, Catherine B.; Petrie, Ryan J.; Dimitriadis, Emilios K.; Li, Xin; Mueller, Susette C.; Bugge, Thomas H.; Gucek, Marjan

2015-01-01

Cell interactions with the extracellular matrix (ECM) can regulate multiple cellular activities and the matrix itself in dynamic, bidirectional processes. One such process is local proteolytic modification of the ECM. Invadopodia of tumor cells are actin-rich proteolytic protrusions that locally degrade matrix molecules and mediate invasion. We report that a novel high-density fibrillar collagen (HDFC) matrix is a potent inducer of invadopodia, both in carcinoma cell lines and in primary human fibroblasts. In carcinoma cells, HDFC matrix induced formation of invadopodia via a specific integrin signaling pathway that did not require growth factors or even altered gene and protein expression. In contrast, phosphoproteomics identified major changes in a complex phosphosignaling network with kindlin2 serine phosphorylation as a key regulatory element. This kindlin2-dependent signal transduction network was required for efficient induction of invadopodia on dense fibrillar collagen and for local degradation of collagen. This novel phosphosignaling mechanism regulates cell surface invadopodia via kindlin2 for local proteolytic remodeling of the ECM. PMID:25646088

Dual Coordination of Post Translational Modifications in Human Protein Networks

PubMed Central

Woodsmith, Jonathan; Kamburov, Atanas; Stelzl, Ulrich

2013-01-01

Post-translational modifications (PTMs) regulate protein activity, stability and interaction profiles and are critical for cellular functioning. Further regulation is gained through PTM interplay whereby modifications modulate the occurrence of other PTMs or act in combination. Integration of global acetylation, ubiquitination and tyrosine or serine/threonine phosphorylation datasets with protein interaction data identified hundreds of protein complexes that selectively accumulate each PTM, indicating coordinated targeting of specific molecular functions. A second layer of PTM coordination exists in these complexes, mediated by PTM integration (PTMi) spots. PTMi spots represent very dense modification patterns in disordered protein regions and showed an equally high mutation rate as functional protein domains in cancer, inferring equivocal importance for cellular functioning. Systematic PTMi spot identification highlighted more than 300 candidate proteins for combinatorial PTM regulation. This study reveals two global PTM coordination mechanisms and emphasizes dataset integration as requisite in proteomic PTM studies to better predict modification impact on cellular signaling. PMID:23505349

A combined gene expression and functional study reveals the crosstalk between N-Myc and differentiation-inducing microRNAs in neuroblastoma cells

PubMed Central

Zhao, Zhenze; Ma, Xiuye; Shelton, Spencer D.; Sung, Derek C.; Li, Monica; Hernandez, Daniel; Zhang, Maggie; Losiewicz, Michael D.; Chen, Yidong; Pertsemlidis, Alexander; Yu, Xiaojie; Liu, Yuanhang; Du, Liqin

2016-01-01

MYCN amplification is the most common genetic alteration in neuroblastoma and plays a critical role in neuroblastoma tumorigenesis. MYCN regulates neuroblastoma cell differentiation, which is one of the mechanisms underlying its oncogenic function. We recently identified a group of differentiation-inducing microRNAs. Given the demonstrated inter-regulation between MYCN and microRNAs, we speculated that MYCN and the differentiation-inducing microRNAs might form an interaction network to control the differentiation of neuroblastoma cells. In this study, we found that eight of the thirteen differentiation-inducing microRNAs, miR-506-3p, miR-124-3p, miR-449a, miR-34a-5p, miR-449b-5p, miR-103a-3p, miR-2110 and miR-34b-5p, inhibit N-Myc expression by either directly targeting the MYCN 3′UTR or through indirect regulations. Further investigation showed that both MYCN-dependent and MYCN-independent pathways play roles in mediating the differentiation-inducing function of miR-506-3p and miR-449a, two microRNAs that dramatically down-regulate MYCN expression. On the other hand, we found that N-Myc inhibits the expression of multiple differentiation-inducing microRNAs, suggesting that these miRNAs play a role in mediating the function of MYCN. In examining the published dataset collected from clinical neuroblastoma specimens, we found that expressions of two miRNAs, miR-137 and miR-2110, were significantly anti-correlated with MYCN mRNA levels, suggesting their interactions with MYCN play a clinically-relevant role in maintaining the MYCN and miRNA expression levels in neuroblastoma. Our findings altogether suggest that MYCN and differentiation-inducing miRNAs form an interaction network that play an important role in neuroblastoma tumorigenesis through regulating cell differentiation. PMID:27764804

A combined gene expression and functional study reveals the crosstalk between N-Myc and differentiation-inducing microRNAs in neuroblastoma cells.

PubMed

Zhao, Zhenze; Ma, Xiuye; Shelton, Spencer D; Sung, Derek C; Li, Monica; Hernandez, Daniel; Zhang, Maggie; Losiewicz, Michael D; Chen, Yidong; Pertsemlidis, Alexander; Yu, Xiaojie; Liu, Yuanhang; Du, Liqin

2016-11-29

MYCN amplification is the most common genetic alteration in neuroblastoma and plays a critical role in neuroblastoma tumorigenesis. MYCN regulates neuroblastoma cell differentiation, which is one of the mechanisms underlying its oncogenic function. We recently identified a group of differentiation-inducing microRNAs. Given the demonstrated inter-regulation between MYCN and microRNAs, we speculated that MYCN and the differentiation-inducing microRNAs might form an interaction network to control the differentiation of neuroblastoma cells. In this study, we found that eight of the thirteen differentiation-inducing microRNAs, miR-506-3p, miR-124-3p, miR-449a, miR-34a-5p, miR-449b-5p, miR-103a-3p, miR-2110 and miR-34b-5p, inhibit N-Myc expression by either directly targeting the MYCN 3'UTR or through indirect regulations. Further investigation showed that both MYCN-dependent and MYCN-independent pathways play roles in mediating the differentiation-inducing function of miR-506-3p and miR-449a, two microRNAs that dramatically down-regulate MYCN expression. On the other hand, we found that N-Myc inhibits the expression of multiple differentiation-inducing microRNAs, suggesting that these miRNAs play a role in mediating the function of MYCN. In examining the published dataset collected from clinical neuroblastoma specimens, we found that expressions of two miRNAs, miR-137 and miR-2110, were significantly anti-correlated with MYCN mRNA levels, suggesting their interactions with MYCN play a clinically-relevant role in maintaining the MYCN and miRNA expression levels in neuroblastoma. Our findings altogether suggest that MYCN and differentiation-inducing miRNAs form an interaction network that play an important role in neuroblastoma tumorigenesis through regulating cell differentiation.

LSU network hubs integrate abiotic and biotic stress responses via interaction with the superoxide dismutase FSD2

PubMed Central

Garcia-Molina, Antoni; Altmann, Melina; Alkofer, Angela; Epple, Petra M.; Dangl, Jeffery L.

2017-01-01

Abstract In natural environments, plants often experience different stresses simultaneously, and adverse abiotic conditions can weaken the plant immune system. Interactome mapping revealed that the LOW SULPHUR UPREGULATED (LSU) proteins are hubs in an Arabidopsis protein interaction network that are targeted by virulence effectors from evolutionarily diverse pathogens. Here we show that LSU proteins are up-regulated in several abiotic and biotic stress conditions, such as nutrient depletion or salt stress, by both transcriptional and post-translational mechanisms. Interference with LSU expression prevents chloroplastic reactive oxygen species (ROS) production and proper stomatal closure during sulphur stress. We demonstrate that LSU1 interacts with the chloroplastic superoxide dismutase FSD2 and stimulates its enzymatic activity in vivo and in vitro. Pseudomonas syringae virulence effectors interfere with this interaction and preclude re-localization of LSU1 to chloroplasts. We demonstrate that reduced LSU levels cause a moderately enhanced disease susceptibility in plants exposed to abiotic stresses such as nutrient deficiency, high salinity, or heavy metal toxicity, whereas LSU1 overexpression confers significant disease resistance in several of these conditions. Our data suggest that the network hub LSU1 plays an important role in co-ordinating plant immune responses across a spectrum of abiotic stress conditions. PMID:28207043

Genomic analysis of regulatory network dynamics reveals large topological changes

NASA Astrophysics Data System (ADS)

Luscombe, Nicholas M.; Madan Babu, M.; Yu, Haiyuan; Snyder, Michael; Teichmann, Sarah A.; Gerstein, Mark

2004-09-01

Network analysis has been applied widely, providing a unifying language to describe disparate systems ranging from social interactions to power grids. It has recently been used in molecular biology, but so far the resulting networks have only been analysed statically. Here we present the dynamics of a biological network on a genomic scale, by integrating transcriptional regulatory information and gene-expression data for multiple conditions in Saccharomyces cerevisiae. We develop an approach for the statistical analysis of network dynamics, called SANDY, combining well-known global topological measures, local motifs and newly derived statistics. We uncover large changes in underlying network architecture that are unexpected given current viewpoints and random simulations. In response to diverse stimuli, transcription factors alter their interactions to varying degrees, thereby rewiring the network. A few transcription factors serve as permanent hubs, but most act transiently only during certain conditions. By studying sub-network structures, we show that environmental responses facilitate fast signal propagation (for example, with short regulatory cascades), whereas the cell cycle and sporulation direct temporal progression through multiple stages (for example, with highly inter-connected transcription factors). Indeed, to drive the latter processes forward, phase-specific transcription factors inter-regulate serially, and ubiquitously active transcription factors layer above them in a two-tiered hierarchy. We anticipate that many of the concepts presented here-particularly the large-scale topological changes and hub transience-will apply to other biological networks, including complex sub-systems in higher eukaryotes.

Systematic Genetic Screen for Transcriptional Regulators of the Candida albicans White-Opaque Switch

PubMed Central

Lohse, Matthew B.; Ene, Iuliana V.; Craik, Veronica B.; Hernday, Aaron D.; Mancera, Eugenio; Morschhäuser, Joachim; Bennett, Richard J.; Johnson, Alexander D.

2016-01-01

The human fungal pathogen Candida albicans can reversibly switch between two cell types named “white” and “opaque,” each of which is stable through many cell divisions. These two cell types differ in their ability to mate, their metabolic preferences and their interactions with the mammalian innate immune system. A highly interconnected network of eight transcriptional regulators has been shown to control switching between these two cell types. To identify additional regulators of the switch, we systematically and quantitatively measured white–opaque switching rates of 196 strains, each deleted for a specific transcriptional regulator. We identified 19 new regulators with at least a 10-fold effect on switching rates and an additional 14 new regulators with more subtle effects. To investigate how these regulators affect switching rates, we examined several criteria, including the binding of the eight known regulators of switching to the control region of each new regulatory gene, differential expression of the newly found genes between cell types, and the growth rate of each mutant strain. This study highlights the complexity of the transcriptional network that regulates the white–opaque switch and the extent to which switching is linked to a variety of metabolic processes, including respiration and carbon utilization. In addition to revealing specific insights, the information reported here provides a foundation to understand the highly complex coupling of white–opaque switching to cellular physiology. PMID:27280690

Optimality principles in the regulation of metabolic networks.

PubMed

Berkhout, Jan; Bruggeman, Frank J; Teusink, Bas

2012-08-29

One of the challenging tasks in systems biology is to understand how molecular networks give rise to emergent functionality and whether universal design principles apply to molecular networks. To achieve this, the biophysical, evolutionary and physiological constraints that act on those networks need to be identified in addition to the characterisation of the molecular components and interactions. Then, the cellular "task" of the network-its function-should be identified. A network contributes to organismal fitness through its function. The premise is that the same functions are often implemented in different organisms by the same type of network; hence, the concept of design principles. In biology, due to the strong forces of selective pressure and natural selection, network functions can often be understood as the outcome of fitness optimisation. The hypothesis of fitness optimisation to understand the design of a network has proven to be a powerful strategy. Here, we outline the use of several optimisation principles applied to biological networks, with an emphasis on metabolic regulatory networks. We discuss the different objective functions and constraints that are considered and the kind of understanding that they provide.

Identification of HDA15-PIF1 as a key repression module directing the transcriptional network of seed germination in the dark.

PubMed

Gu, Dachuan; Chen, Chia-Yang; Zhao, Minglei; Zhao, Linmao; Duan, Xuewu; Duan, Jun; Wu, Keqiang; Liu, Xuncheng

2017-07-07

Light is a major external factor in regulating seed germination. Photoreceptor phytochrome B (PHYB) plays a predominant role in promoting seed germination in the initial phase after imbibition, partially by repressing phytochrome-interacting factor1 (PIF1). However, the mechanism underlying the PHYB-PIF1-mediated transcription regulation remains largely unclear. Here, we identified that histone deacetylase15 (HDA15) is a negative component of PHYB-dependent seed germination. Overexpression of HDA15 in Arabidopsis inhibits PHYB-dependent seed germination, whereas loss of function of HDA15 increases PHYB-dependent seed germination. Genetic evidence indicated that HDA15 acts downstream of PHYB and represses seed germination dependent on PIF1. Furthermore, HDA15 interacts with PIF1 both in vitro and in vivo. Genome-wide transcriptome analysis revealed that HDA15 and PIF1 co-regulate the transcription of the light-responsive genes involved in multiple hormonal signaling pathways and cellular processes in germinating seeds in the dark. In addition, PIF1 recruits HDA15 to the promoter regions of target genes and represses their expression by decreasing the histone H3 acetylation levels in the dark. Taken together, our analysis uncovered the role of histone deacetylation in the light-regulated seed germination process and identified that HDA15-PIF1 acts as a key repression module directing the transcription network of seed germination. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Identification of HDA15-PIF1 as a key repression module directing the transcriptional network of seed germination in the dark

PubMed Central

Gu, Dachuan; Chen, Chia-Yang; Zhao, Minglei; Zhao, Linmao; Duan, Xuewu

2017-01-01

Abstract Light is a major external factor in regulating seed germination. Photoreceptor phytochrome B (PHYB) plays a predominant role in promoting seed germination in the initial phase after imbibition, partially by repressing phytochrome-interacting factor1 (PIF1). However, the mechanism underlying the PHYB-PIF1-mediated transcription regulation remains largely unclear. Here, we identified that histone deacetylase15 (HDA15) is a negative component of PHYB-dependent seed germination. Overexpression of HDA15 in Arabidopsis inhibits PHYB-dependent seed germination, whereas loss of function of HDA15 increases PHYB-dependent seed germination. Genetic evidence indicated that HDA15 acts downstream of PHYB and represses seed germination dependent on PIF1. Furthermore, HDA15 interacts with PIF1 both in vitro and in vivo. Genome-wide transcriptome analysis revealed that HDA15 and PIF1 co-regulate the transcription of the light-responsive genes involved in multiple hormonal signaling pathways and cellular processes in germinating seeds in the dark. In addition, PIF1 recruits HDA15 to the promoter regions of target genes and represses their expression by decreasing the histone H3 acetylation levels in the dark. Taken together, our analysis uncovered the role of histone deacetylation in the light-regulated seed germination process and identified that HDA15-PIF1 acts as a key repression module directing the transcription network of seed germination. PMID:28444370

iTRAQ-based Quantitative Proteomics Study in Patients with Refractory Mycoplasma pneumoniae Pneumonia.

PubMed

Yu, Jia-Lu; Song, Qi-Fang; Xie, Zhi-Wei; Jiang, Wen-Hui; Chen, Jia-Hui; Fan, Hui-Feng; Xie, Ya-Ping; Lu, Gen

2017-09-25

Mycoplasma pneumoniae (MP) is a leading cause of community-acquired pneumonia in children and young adults. Although MP pneumonia is usually benign and self-limited, in some cases it can develop into life-threating refractory MP pneumonia (RMPP). However, the pathogenesis of RMPP is poorly understood. The identification and characterization of proteins related to RMPP could provide a proof of principle to facilitate appropriate diagnostic and therapeutic strategies for treating paients with MP. In this study, we used a quantitative proteomic technique (iTRAQ) to analyze MP-related proteins in serum samples from 5 patients with RMPP, 5 patients with non-refractory MP pneumonia (NRMPP), and 5 healthy children. Functional classification, sub-cellular localization, and protein interaction network analysis were carried out based on protein annotation through evolutionary relationship (PANTHER) and Cytoscape analysis. A total of 260 differentially expressed proteins were identified in the RMPP and NRMPP groups. Compared to the control group, the NRMPP and RMPP groups showed 134 (70 up-regulated and 64 down-regulated) and 126 (63 up-regulated and 63 down-regulated) differentially expressed proteins, respectively. The complex functional classification and protein interaction network of the identified proteins reflected the complex pathogenesis of RMPP. Our study provides the first comprehensive proteome map of RMPP-related proteins from MP pneumonia. These profiles may be useful as part of a diagnostic panel, and the identified proteins provide new insights into the pathological mechanisms underlying RMPP.

Autocatalytic, bistable, oscillatory networks of biologically relevant organic reactions.

PubMed

Semenov, Sergey N; Kraft, Lewis J; Ainla, Alar; Zhao, Mengxia; Baghbanzadeh, Mostafa; Campbell, Victoria E; Kang, Kyungtae; Fox, Jerome M; Whitesides, George M

2016-09-29

Networks of organic chemical reactions are important in life and probably played a central part in its origin. Network dynamics regulate cell division, circadian rhythms, nerve impulses and chemotaxis, and guide the development of organisms. Although out-of-equilibrium networks of chemical reactions have the potential to display emergent network dynamics such as spontaneous pattern formation, bistability and periodic oscillations, the principles that enable networks of organic reactions to develop complex behaviours are incompletely understood. Here we describe a network of biologically relevant organic reactions (amide formation, thiolate-thioester exchange, thiolate-disulfide interchange and conjugate addition) that displays bistability and oscillations in the concentrations of organic thiols and amides. Oscillations arise from the interaction between three subcomponents of the network: an autocatalytic cycle that generates thiols and amides from thioesters and dialkyl disulfides; a trigger that controls autocatalytic growth; and inhibitory processes that remove activating thiol species that are produced during the autocatalytic cycle. In contrast to previous studies that have demonstrated oscillations and bistability using highly evolved biomolecules (enzymes and DNA) or inorganic molecules of questionable biochemical relevance (for example, those used in Belousov-Zhabotinskii-type reactions), the organic molecules we use are relevant to metabolism and similar to those that might have existed on the early Earth. By using small organic molecules to build a network of organic reactions with autocatalytic, bistable and oscillatory behaviour, we identify principles that explain the ways in which dynamic networks relevant to life could have developed. Modifications of this network will clarify the influence of molecular structure on the dynamics of reaction networks, and may enable the design of biomimetic networks and of synthetic self-regulating and evolving chemical systems.

Autocatalytic, bistable, oscillatory networks of biologically relevant organic reactions

NASA Astrophysics Data System (ADS)

Semenov, Sergey N.; Kraft, Lewis J.; Ainla, Alar; Zhao, Mengxia; Baghbanzadeh, Mostafa; Campbell, Victoria E.; Kang, Kyungtae; Fox, Jerome M.; Whitesides, George M.

2016-09-01

Networks of organic chemical reactions are important in life and probably played a central part in its origin. Network dynamics regulate cell division, circadian rhythms, nerve impulses and chemotaxis, and guide the development of organisms. Although out-of-equilibrium networks of chemical reactions have the potential to display emergent network dynamics such as spontaneous pattern formation, bistability and periodic oscillations, the principles that enable networks of organic reactions to develop complex behaviours are incompletely understood. Here we describe a network of biologically relevant organic reactions (amide formation, thiolate-thioester exchange, thiolate-disulfide interchange and conjugate addition) that displays bistability and oscillations in the concentrations of organic thiols and amides. Oscillations arise from the interaction between three subcomponents of the network: an autocatalytic cycle that generates thiols and amides from thioesters and dialkyl disulfides; a trigger that controls autocatalytic growth; and inhibitory processes that remove activating thiol species that are produced during the autocatalytic cycle. In contrast to previous studies that have demonstrated oscillations and bistability using highly evolved biomolecules (enzymes and DNA) or inorganic molecules of questionable biochemical relevance (for example, those used in Belousov-Zhabotinskii-type reactions), the organic molecules we use are relevant to metabolism and similar to those that might have existed on the early Earth. By using small organic molecules to build a network of organic reactions with autocatalytic, bistable and oscillatory behaviour, we identify principles that explain the ways in which dynamic networks relevant to life could have developed. Modifications of this network will clarify the influence of molecular structure on the dynamics of reaction networks, and may enable the design of biomimetic networks and of synthetic self-regulating and evolving chemical systems.

CoryneRegNet 4.0 – A reference database for corynebacterial gene regulatory networks

PubMed Central

Baumbach, Jan

2007-01-01

Background Detailed information on DNA-binding transcription factors (the key players in the regulation of gene expression) and on transcriptional regulatory interactions of microorganisms deduced from literature-derived knowledge, computer predictions and global DNA microarray hybridization experiments, has opened the way for the genome-wide analysis of transcriptional regulatory networks. The large-scale reconstruction of these networks allows the in silico analysis of cell behavior in response to changing environmental conditions. We previously published CoryneRegNet, an ontology-based data warehouse of corynebacterial transcription factors and regulatory networks. Initially, it was designed to provide methods for the analysis and visualization of the gene regulatory network of Corynebacterium glutamicum. Results Now we introduce CoryneRegNet release 4.0, which integrates data on the gene regulatory networks of 4 corynebacteria, 2 mycobacteria and the model organism Escherichia coli K12. As the previous versions, CoryneRegNet provides a web-based user interface to access the database content, to allow various queries, and to support the reconstruction, analysis and visualization of regulatory networks at different hierarchical levels. In this article, we present the further improved database content of CoryneRegNet along with novel analysis features. The network visualization feature GraphVis now allows the inter-species comparisons of reconstructed gene regulatory networks and the projection of gene expression levels onto that networks. Therefore, we added stimulon data directly into the database, but also provide Web Service access to the DNA microarray analysis platform EMMA. Additionally, CoryneRegNet now provides a SOAP based Web Service server, which can easily be consumed by other bioinformatics software systems. Stimulons (imported from the database, or uploaded by the user) can be analyzed in the context of known transcriptional regulatory networks to predict putative contradictions or further gene regulatory interactions. Furthermore, it integrates protein clusters by means of heuristically solving the weighted graph cluster editing problem. In addition, it provides Web Service based access to up to date gene annotation data from GenDB. Conclusion The release 4.0 of CoryneRegNet is a comprehensive system for the integrated analysis of procaryotic gene regulatory networks. It is a versatile systems biology platform to support the efficient and large-scale analysis of transcriptional regulation of gene expression in microorganisms. It is publicly available at . PMID:17986320

Regulation of corneal stroma extracellular matrix assembly.

PubMed

Chen, Shoujun; Mienaltowski, Michael J; Birk, David E

2015-04-01

The transparent cornea is the major refractive element of the eye. A finely controlled assembly of the stromal extracellular matrix is critical to corneal function, as well as in establishing the appropriate mechanical stability required to maintain corneal shape and curvature. In the stroma, homogeneous, small diameter collagen fibrils, regularly packed with a highly ordered hierarchical organization, are essential for function. This review focuses on corneal stroma assembly and the regulation of collagen fibrillogenesis. Corneal collagen fibrillogenesis involves multiple molecules interacting in sequential steps, as well as interactions between keratocytes and stroma matrix components. The stroma has the highest collagen V:I ratio in the body. Collagen V regulates the nucleation of protofibril assembly, thus controlling the number of fibrils and assembly of smaller diameter fibrils in the stroma. The corneal stroma is also enriched in small leucine-rich proteoglycans (SLRPs) that cooperate in a temporal and spatial manner to regulate linear and lateral collagen fibril growth. In addition, the fibril-associated collagens (FACITs) such as collagen XII and collagen XIV have roles in the regulation of fibril packing and inter-lamellar interactions. A communicating keratocyte network contributes to the overall and long-range regulation of stromal extracellular matrix assembly, by creating micro-domains where the sequential steps in stromal matrix assembly are controlled. Keratocytes control the synthesis of extracellular matrix components, which interact with the keratocytes dynamically to coordinate the regulatory steps into a cohesive process. Mutations or deficiencies in stromal regulatory molecules result in altered interactions and deficiencies in both transparency and refraction, leading to corneal stroma pathobiology such as stromal dystrophies, cornea plana and keratoconus. Copyright © 2014 Elsevier Ltd. All rights reserved.

Specificity and non-specificity in RNA–protein interactions

PubMed Central

Jankowsky, Eckhard; Harris, Michael E.

2016-01-01

Gene expression is regulated by complex networks of interactions between RNAs and proteins. Proteins that interact with RNA have been traditionally viewed as either specific or non-specific; specific proteins interact preferentially with defined RNA sequence or structure motifs, whereas non-specific proteins interact with RNA sites devoid of such characteristics. Recent studies indicate that the binary “specific vs. non-specific” classification is insufficient to describe the full spectrum of RNA–protein interactions. Here, we review new methods that enable quantitative measurements of protein binding to large numbers of RNA variants, and the concepts aimed as describing resulting binding spectra: affinity distributions, comprehensive binding models and free energy landscapes. We discuss how these new methodologies and associated concepts enable work towards inclusive, quantitative models for specific and non-specific RNA–protein interactions. PMID:26285679

Natural changes in light interact with circadian regulation at promoters to control gene expression in cyanobacteria

PubMed Central

2017-01-01

The circadian clock interacts with other regulatory pathways to tune physiology to predictable daily changes and unexpected environmental fluctuations. However, the complexity of circadian clocks in higher organisms has prevented a clear understanding of how natural environmental conditions affect circadian clocks and their physiological outputs. Here, we dissect the interaction between circadian regulation and responses to fluctuating light in the cyanobacterium Synechococcus elongatus. We demonstrate that natural changes in light intensity substantially affect the expression of hundreds of circadian-clock-controlled genes, many of which are involved in key steps of metabolism. These changes in expression arise from circadian and light-responsive control of RNA polymerase recruitment to promoters by a network of transcription factors including RpaA and RpaB. Using phenomenological modeling constrained by our data, we reveal simple principles that underlie the small number of stereotyped responses of dusk circadian genes to changes in light. PMID:29239721

Exploring the interactions of the RAS family in the human protein network and their potential implications in RAS-directed therapies

PubMed Central

Bueno, Anibal; Morilla, Ian; Diez, Diego; Moya-Garcia, Aurelio A.; Lozano, José; Ranea, Juan A.G.

2016-01-01

RAS proteins are the founding members of the RAS superfamily of GTPases. They are involved in key signaling pathways regulating essential cellular functions such as cell growth and differentiation. As a result, their deregulation by inactivating mutations often results in aberrant cell proliferation and cancer. With the exception of the relatively well-known KRAS, HRAS and NRAS proteins, little is known about how the interactions of the other RAS human paralogs affect cancer evolution and response to treatment. In this study we performed a comprehensive analysis of the relationship between the phylogeny of RAS proteins and their location in the protein interaction network. This analysis was integrated with the structural analysis of conserved positions in available 3D structures of RAS complexes. Our results show that many RAS proteins with divergent sequences are found close together in the human interactome. We found specific conserved amino acid positions in this group that map to the binding sites of RAS with many of their signaling effectors, suggesting that these pairs could share interacting partners. These results underscore the potential relevance of cross-talking in the RAS signaling network, which should be taken into account when considering the inhibitory activity of drugs targeting specific RAS oncoproteins. This study broadens our understanding of the human RAS signaling network and stresses the importance of considering its potential cross-talk in future therapies. PMID:27713118

RegNetwork: an integrated database of transcriptional and post-transcriptional regulatory networks in human and mouse

PubMed Central

Liu, Zhi-Ping; Wu, Canglin; Miao, Hongyu; Wu, Hulin

2015-01-01

Transcriptional and post-transcriptional regulation of gene expression is of fundamental importance to numerous biological processes. Nowadays, an increasing amount of gene regulatory relationships have been documented in various databases and literature. However, to more efficiently exploit such knowledge for biomedical research and applications, it is necessary to construct a genome-wide regulatory network database to integrate the information on gene regulatory relationships that are widely scattered in many different places. Therefore, in this work, we build a knowledge-based database, named ‘RegNetwork’, of gene regulatory networks for human and mouse by collecting and integrating the documented regulatory interactions among transcription factors (TFs), microRNAs (miRNAs) and target genes from 25 selected databases. Moreover, we also inferred and incorporated potential regulatory relationships based on transcription factor binding site (TFBS) motifs into RegNetwork. As a result, RegNetwork contains a comprehensive set of experimentally observed or predicted transcriptional and post-transcriptional regulatory relationships, and the database framework is flexibly designed for potential extensions to include gene regulatory networks for other organisms in the future. Based on RegNetwork, we characterized the statistical and topological properties of genome-wide regulatory networks for human and mouse, we also extracted and interpreted simple yet important network motifs that involve the interplays between TF-miRNA and their targets. In summary, RegNetwork provides an integrated resource on the prior information for gene regulatory relationships, and it enables us to further investigate context-specific transcriptional and post-transcriptional regulatory interactions based on domain-specific experimental data. Database URL: http://www.regnetworkweb.org PMID:26424082

Integrating non-coding RNAs in JAK-STAT regulatory networks

PubMed Central

Witte, Steven; Muljo, Stefan A

2014-01-01

Being a well-characterized pathway, JAK-STAT signaling serves as a valuable paradigm for studying the architecture of gene regulatory networks. The discovery of untranslated or non-coding RNAs, namely microRNAs and long non-coding RNAs, provides an opportunity to elucidate their roles in such networks. In principle, these regulatory RNAs can act as downstream effectors of the JAK-STAT pathway and/or affect signaling by regulating the expression of JAK-STAT components. Examples of interactions between signaling pathways and non-coding RNAs have already emerged in basic cell biology and human diseases such as cancer, and can potentially guide the identification of novel biomarkers or drug targets for medicine. PMID:24778925

Intrinsic limits to gene regulation by global crosstalk

NASA Astrophysics Data System (ADS)

Friedlander, Tamar; Prizak, Roshan; Guet, Calin; Barton, Nicholas H.; Tkacik, Gasper

Gene activity is mediated by the specificity of binding interactions between special proteins, called transcription factors, and short regulatory sequences on the DNA, where different protein species preferentially bind different DNA targets. Limited interaction specificity may lead to crosstalk: a regulatory state in which a gene is either incorrectly activated due to spurious interactions or remains erroneously inactive. Since each protein can potentially interact with numerous DNA targets, crosstalk is inherently a global problem, yet has previously not been studied as such. We construct a theoretical framework to analyze the effects of global crosstalk on gene regulation, using statistical mechanics. We find that crosstalk in regulatory interactions puts fundamental limits on the reliability of gene regulation that are not easily mitigated by tuning proteins concentrations or by complex regulatory schemes proposed in the literature. Our results suggest that crosstalk imposes a previously unexplored global constraint on the functioning and evolution of regulatory networks, which is qualitatively distinct from the known constraints that act at the level of individual gene regulatory elements. The research leading to these results has received funding from the People Programme (Marie Curie Actions) of the European Union's Seventh Framework Programme (FP7/2007-2013) under REA Grant agreement Nr. 291734 (T.F.) and ERC Grant Nr. 250152 (N.B.).

Functional Categorization of Transcriptome in the Species Symphysodon aequifasciatus Pellegrin 1904 (Perciformes: Cichlidae) Exposed to Benzo[a]pyrene and Phenanthrene

PubMed Central

Lemgruber, Renato de Souza Pinto; Marshall, Nislanha Ana dos Anjos; Ghelfi, Andrea; Fagundes, Daniel Barros; Val, Adalberto Luis

2013-01-01

This study aims to evaluate the transcriptome alterations, through cDNA libraries, associated with the combined effects of two PAHs, benzo[a]pyrene (0.5 µg/L) and phenanthrene (50 µg/L), present in crude oil, on specimens of Symphysodon aequifasciatus (discus fish) after 48 h of exposure. The cDNA libraries were constructed according to the SOLiD™ SAGE™ protocol for sequencing in the SOLiD v.3 Plus sequencer. The results were analyzed by bioinformatics and differentially expressed genes were categorized using the gene ontology program. The functional categories (terms) found in the gene ontology and the gene network generated using STRING software were used to predict the adverse effects of benzo[a]pyrene and phenanthrene in the liver. In the present study, 27,127 genes (compared to Danio rerio database) were identified. Considering only those genes with a p-value less than or equal to 0.05 and greater than or equal to two-fold change in expression across libraries, we found 804 genes, 438 down-regulated (54%) and 366 up-regulated (46%), in the experimental group compared to the control. Out of this total, 327 genes were successfully categorized, 174 down-regulated and 153 up-regulated, using gene ontology. Using String, the gene network was composed by 199 nodes, 124 of them resulting in 274 interactions. The results showed that even an acute exposure of 48 h caused metabolic change in response to environmental contaminants, resulting in changes of cell integrity, in oxidation-reduction processes, in the immune response and disturbances of intracellular signaling of discus fish. Also the gene network has showed no central interplay cluster, exhibiting instead interconnected clusters interactions and connected sub-networks. These findings highlight that even an acute sublethal exposure of PAHs can cause metabolism changes that may affect survival of discus. Our findings using SOLiD coupled with SAGE-method resulted in a powerful and reliable means for gene expression analysis in discus, a non-model Amazonian fish. PMID:24312524

Oxytocin receptors modulate a social salience neural network in male prairie voles.

PubMed

Johnson, Zachary V; Walum, Hasse; Xiao, Yao; Riefkohl, Paula C; Young, Larry J

2017-01-01

Social behavior is regulated by conserved neural networks across vertebrates. Variation in the organization of neuropeptide systems across these networks is thought to contribute to individual and species diversity in network function during social contexts. For example, oxytocin (OT) is an ancient neuropeptide that binds to OT receptors (OTRs) in the brain and modulates social and reproductive behavior across vertebrate species, including humans. Central OTRs exhibit extraordinarily diverse expression patterns that are associated with individual and species differences in social behavior. In voles, OTR density in the nucleus accumbens (NAc)-a region important for social and reward learning-is associated with individual and species variation in social attachment behavior. Here we test whether OTRs in the NAc modulate a social salience network (SSN)-a network of interconnected brain nuclei thought to encode valence and incentive salience of sociosensory cues-during a social context in the socially monogamous male prairie vole. Using a selective OTR antagonist, we test whether activation of OTRs in the NAc during sociosexual interaction and mating modulates expression of the immediate early gene product Fos across nuclei of the SSN. We show that blockade of endogenous OTR signaling in the NAc during sociosexual interaction and mating does not strongly modulate levels of Fos expression in individual nodes of the network, but strongly modulates patterns of correlated Fos expression between the NAc and other SSN nuclei. Published by Elsevier Inc.

Coding and non-coding gene regulatory networks underlie the immune response in liver cirrhosis.

PubMed

Gao, Bo; Zhang, Xueming; Huang, Yongming; Yang, Zhengpeng; Zhang, Yuguo; Zhang, Weihui; Gao, Zu-Hua; Xue, Dongbo

2017-01-01

Liver cirrhosis is recognized as being the consequence of immune-mediated hepatocyte damage and repair processes. However, the regulation of these immune responses underlying liver cirrhosis has not been elucidated. In this study, we used GEO datasets and bioinformatics methods to established coding and non-coding gene regulatory networks including transcription factor-/lncRNA-microRNA-mRNA, and competing endogenous RNA interaction networks. Our results identified 2224 mRNAs, 70 lncRNAs and 46 microRNAs were differentially expressed in liver cirrhosis. The transcription factor -/lncRNA- microRNA-mRNA network we uncovered that results in immune-mediated liver cirrhosis is comprised of 5 core microRNAs (e.g., miR-203; miR-219-5p), 3 transcription factors (i.e., FOXP3, ETS1 and FOS) and 7 lncRNAs (e.g., ENTS00000671336, ENST00000575137). The competing endogenous RNA interaction network we identified includes a complex immune response regulatory subnetwork that controls the entire liver cirrhosis network. Additionally, we found 10 overlapping GO terms shared by both liver cirrhosis and hepatocellular carcinoma including "immune response" as well. Interestingly, the overlapping differentially expressed genes in liver cirrhosis and hepatocellular carcinoma were enriched in immune response-related functional terms. In summary, a complex gene regulatory network underlying immune response processes may play an important role in the development and progression of liver cirrhosis, and its development into hepatocellular carcinoma.

NetDecoder: a network biology platform that decodes context-specific biological networks and gene activities.

PubMed

da Rocha, Edroaldo Lummertz; Ung, Choong Yong; McGehee, Cordelia D; Correia, Cristina; Li, Hu

2016-06-02

The sequential chain of interactions altering the binary state of a biomolecule represents the 'information flow' within a cellular network that determines phenotypic properties. Given the lack of computational tools to dissect context-dependent networks and gene activities, we developed NetDecoder, a network biology platform that models context-dependent information flows using pairwise phenotypic comparative analyses of protein-protein interactions. Using breast cancer, dyslipidemia and Alzheimer's disease as case studies, we demonstrate NetDecoder dissects subnetworks to identify key players significantly impacting cell behaviour specific to a given disease context. We further show genes residing in disease-specific subnetworks are enriched in disease-related signalling pathways and information flow profiles, which drive the resulting disease phenotypes. We also devise a novel scoring scheme to quantify key genes-network routers, which influence many genes, key targets, which are influenced by many genes, and high impact genes, which experience a significant change in regulation. We show the robustness of our results against parameter changes. Our network biology platform includes freely available source code (http://www.NetDecoder.org) for researchers to explore genome-wide context-dependent information flow profiles and key genes, given a set of genes of particular interest and transcriptome data. More importantly, NetDecoder will enable researchers to uncover context-dependent drug targets. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

An experimentally validated network of nine haematopoietic transcription factors reveals mechanisms of cell state stability

PubMed Central

Schütte, Judith; Wang, Huange; Antoniou, Stella; Jarratt, Andrew; Wilson, Nicola K; Riepsaame, Joey; Calero-Nieto, Fernando J; Moignard, Victoria; Basilico, Silvia; Kinston, Sarah J; Hannah, Rebecca L; Chan, Mun Chiang; Nürnberg, Sylvia T; Ouwehand, Willem H; Bonzanni, Nicola; de Bruijn, Marella FTR; Göttgens, Berthold

2016-01-01

Transcription factor (TF) networks determine cell-type identity by establishing and maintaining lineage-specific expression profiles, yet reconstruction of mammalian regulatory network models has been hampered by a lack of comprehensive functional validation of regulatory interactions. Here, we report comprehensive ChIP-Seq, transgenic and reporter gene experimental data that have allowed us to construct an experimentally validated regulatory network model for haematopoietic stem/progenitor cells (HSPCs). Model simulation coupled with subsequent experimental validation using single cell expression profiling revealed potential mechanisms for cell state stabilisation, and also how a leukaemogenic TF fusion protein perturbs key HSPC regulators. The approach presented here should help to improve our understanding of both normal physiological and disease processes. DOI: http://dx.doi.org/10.7554/eLife.11469.001 PMID:26901438

Pathway perturbations in signaling networks: Linking genotype to phenotype.

PubMed

Li, Yongsheng; McGrail, Daniel J; Latysheva, Natasha; Yi, Song; Babu, M Madan; Sahni, Nidhi

2018-05-10

Genes and gene products interact with each other to form signal transduction networks in the cell. The interactome networks are under intricate regulation in physiological conditions, but could go awry upon genome instability caused by genetic mutations. In the past decade with next-generation sequencing technologies, an increasing number of genomic mutations have been identified in a variety of disease patients and healthy individuals. As functional and systematic studies on these mutations leap forward, they begin to reveal insights into cellular homeostasis and disease mechanisms. In this review, we discuss recent advances in the field of network biology and signaling pathway perturbations upon genomic changes, and highlight the success of various omics datasets in unraveling genotype-to-phenotype relationships. Copyright © 2018 Elsevier Ltd. All rights reserved.

Systems analysis of multiple regulator perturbations allows discovery of virulence factors in Salmonella

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

Yoon, Hyunjin; Ansong, Charles; McDermott, Jason E.

Background: Systemic bacterial infections are highly regulated and complex processes that are orchestrated by numerous virulence factors. Genes that are coordinately controlled by the set of regulators required for systemic infection are potentially required for pathogenicity. Results: In this study we present a systems biology approach in which sample-matched multi-omic measurements of fourteen virulence-essential regulator mutants were coupled with computational network analysis to efficiently identify Salmonella virulence factors. Immunoblot experiments verified network-predicted virulence factors and a subset was determined to be secreted into the host cytoplasm, suggesting that they are virulence factors directly interacting with host cellular components. Two ofmore » these, SrfN and PagK2, were required for full mouse virulence and were shown to be translocated independent of either of the type III secretion systems in Salmonella or the type III injectisome-related flagellar mechanism. Conclusions: Integrating multi-omic datasets from Salmonella mutants lacking virulence regulators not only identified novel virulence factors but also defined a new class of translocated effectors involved in pathogenesis. The success of this strategy at discovery of known and novel virulence factors suggests that the approach may have applicability for other bacterial pathogens.« less

Evolution of synthetic signaling scaffolds by recombination of modular protein domains.

PubMed

Lai, Andicus; Sato, Paloma M; Peisajovich, Sergio G

2015-06-19

Signaling scaffolds are proteins that interact via modular domains with multiple partners, regulating signaling networks in space and time and providing an ideal platform from which to alter signaling functions. However, to better exploit scaffolds for signaling engineering, it is necessary to understand the full extent of their modularity. We used a directed evolution approach to identify, from a large library of randomly shuffled protein interaction domains, variants capable of rescuing the signaling defect of a yeast strain in which Ste5, the scaffold in the mating pathway, had been deleted. After a single round of selection, we identified multiple synthetic scaffold variants with diverse domain architectures, able to mediate mating pathway activation in a pheromone-dependent manner. The facility with which this signaling network accommodates changes in scaffold architecture suggests that the mating signaling complex does not possess a single, precisely defined geometry into which the scaffold has to fit. These relaxed geometric constraints may facilitate the evolution of signaling networks, as well as their engineering for applications in synthetic biology.

Untangling complex networks: Risk minimization in financial markets through accessible spin glass ground states

NASA Astrophysics Data System (ADS)

Lisewski, Andreas Martin; Lichtarge, Olivier

2010-08-01

Recurrent international financial crises inflict significant damage to societies and stress the need for mechanisms or strategies to control risk and tamper market uncertainties. Unfortunately, the complex network of market interactions often confounds rational approaches to optimize financial risks. Here we show that investors can overcome this complexity and globally minimize risk in portfolio models for any given expected return, provided the margin requirement remains below a critical, empirically measurable value. In practice, for markets with centrally regulated margin requirements, a rational stabilization strategy would be keeping margins small enough. This result follows from ground states of the random field spin glass Ising model that can be calculated exactly through convex optimization when relative spin coupling is limited by the norm of the network’s Laplacian matrix. In that regime, this novel approach is robust to noise in empirical data and may be also broadly relevant to complex networks with frustrated interactions that are studied throughout scientific fields.

A Conserved Deubiquitinating Enzyme Uses Intrinsically Disordered Regions to Scaffold Multiple Protein Interaction Sites*

PubMed Central

Reed, Benjamin J.; Locke, Melissa N.; Gardner, Richard G.

2015-01-01

In the canonical view of protein function, it is generally accepted that the three-dimensional structure of a protein determines its function. However, the past decade has seen a dramatic growth in the identification of proteins with extensive intrinsically disordered regions (IDRs), which are conformationally plastic and do not appear to adopt single three-dimensional structures. One current paradigm for IDR function is that disorder enables IDRs to adopt multiple conformations, expanding the ability of a protein to interact with a wide variety of disparate proteins. The capacity for many interactions is an important feature of proteins that occupy the hubs of protein networks, in particular protein-modifying enzymes that usually have a broad spectrum of substrates. One such protein modification is ubiquitination, where ubiquitin is attached to proteins through ubiquitin ligases (E3s) and removed through deubiquitinating enzymes. Numerous proteomic studies have found that thousands of proteins are dynamically regulated by cycles of ubiquitination and deubiquitination. Thus, how these enzymes target their wide array of substrates is of considerable importance for understanding the function of the cell's diverse ubiquitination networks. Here, we characterize a yeast deubiquitinating enzyme, Ubp10, that possesses IDRs flanking its catalytic protease domain. We show that Ubp10 possesses multiple, distinct binding modules within its IDRs that are necessary and sufficient for directing protein interactions important for Ubp10's known roles in gene silencing and ribosome biogenesis. The human homolog of Ubp10, USP36, also has IDRs flanking its catalytic domain, and these IDRs similarly contain binding modules important for protein interactions. This work highlights the significant protein interaction scaffolding abilities of IDRs in the regulation of dynamic protein ubiquitination. PMID:26149687

Social insect colony as a biological regulatory system: modelling information flow in dominance networks.

PubMed

Nandi, Anjan K; Sumana, Annagiri; Bhattacharya, Kunal

2014-12-06

Social insects provide an excellent platform to investigate flow of information in regulatory systems since their successful social organization is essentially achieved by effective information transfer through complex connectivity patterns among the colony members. Network representation of such behavioural interactions offers a powerful tool for structural as well as dynamical analysis of the underlying regulatory systems. In this paper, we focus on the dominance interaction networks in the tropical social wasp Ropalidia marginata-a species where behavioural observations indicate that such interactions are principally responsible for the transfer of information between individuals about their colony needs, resulting in a regulation of their own activities. Our research reveals that the dominance networks of R. marginata are structurally similar to a class of naturally evolved information processing networks, a fact confirmed also by the predominance of a specific substructure-the 'feed-forward loop'-a key functional component in many other information transfer networks. The dynamical analysis through Boolean modelling confirms that the networks are sufficiently stable under small fluctuations and yet capable of more efficient information transfer compared to their randomized counterparts. Our results suggest the involvement of a common structural design principle in different biological regulatory systems and a possible similarity with respect to the effect of selection on the organization levels of such systems. The findings are also consistent with the hypothesis that dominance behaviour has been shaped by natural selection to co-opt the information transfer process in such social insect species, in addition to its primal function of mediation of reproductive competition in the colony. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

Optimality Principles in the Regulation of Metabolic Networks

PubMed Central

Berkhout, Jan; Bruggeman, Frank J.; Teusink, Bas

2012-01-01

One of the challenging tasks in systems biology is to understand how molecular networks give rise to emergent functionality and whether universal design principles apply to molecular networks. To achieve this, the biophysical, evolutionary and physiological constraints that act on those networks need to be identified in addition to the characterisation of the molecular components and interactions. Then, the cellular “task” of the network—its function—should be identified. A network contributes to organismal fitness through its function. The premise is that the same functions are often implemented in different organisms by the same type of network; hence, the concept of design principles. In biology, due to the strong forces of selective pressure and natural selection, network functions can often be understood as the outcome of fitness optimisation. The hypothesis of fitness optimisation to understand the design of a network has proven to be a powerful strategy. Here, we outline the use of several optimisation principles applied to biological networks, with an emphasis on metabolic regulatory networks. We discuss the different objective functions and constraints that are considered and the kind of understanding that they provide. PMID:24957646

Structure-Based Network Analysis of Activation Mechanisms in the ErbB Family of Receptor Tyrosine Kinases: The Regulatory Spine Residues Are Global Mediators of Structural Stability and Allosteric Interactions

PubMed Central

James, Kevin A.; Verkhivker, Gennady M.

2014-01-01

The ErbB protein tyrosine kinases are among the most important cell signaling families and mutation-induced modulation of their activity is associated with diverse functions in biological networks and human disease. We have combined molecular dynamics simulations of the ErbB kinases with the protein structure network modeling to characterize the reorganization of the residue interaction networks during conformational equilibrium changes in the normal and oncogenic forms. Structural stability and network analyses have identified local communities integrated around high centrality sites that correspond to the regulatory spine residues. This analysis has provided a quantitative insight to the mechanism of mutation-induced “superacceptor” activity in oncogenic EGFR dimers. We have found that kinase activation may be determined by allosteric interactions between modules of structurally stable residues that synchronize the dynamics in the nucleotide binding site and the αC-helix with the collective motions of the integrating αF-helix and the substrate binding site. The results of this study have pointed to a central role of the conserved His-Arg-Asp (HRD) motif in the catalytic loop and the Asp-Phe-Gly (DFG) motif as key mediators of structural stability and allosteric communications in the ErbB kinases. We have determined that residues that are indispensable for kinase regulation and catalysis often corresponded to the high centrality nodes within the protein structure network and could be distinguished by their unique network signatures. The optimal communication pathways are also controlled by these nodes and may ensure efficient allosteric signaling in the functional kinase state. Structure-based network analysis has quantified subtle effects of ATP binding on conformational dynamics and stability of the EGFR structures. Consistent with the NMR studies, we have found that nucleotide-induced modulation of the residue interaction networks is not limited to the ATP site, and may enhance allosteric cooperativity with the substrate binding region by increasing communication capabilities of mediating residues. PMID:25427151

Integrative analyses of leprosy susceptibility genes indicate a common autoimmune profile.

PubMed

Zhang, Deng-Feng; Wang, Dong; Li, Yu-Ye; Yao, Yong-Gang

2016-04-01

Leprosy is an ancient chronic infection in the skin and peripheral nerves caused by Mycobacterium leprae. The development of leprosy depends on genetic background and the immune status of the host. However, there is no systematic view focusing on the biological pathways, interaction networks and overall expression pattern of leprosy-related immune and genetic factors. To identify the hub genes in the center of leprosy genetic network and to provide an insight into immune and genetic factors contributing to leprosy. We retrieved all reported leprosy-related genes and performed integrative analyses covering gene expression profiling, pathway analysis, protein-protein interaction network, and evolutionary analyses. A list of 123 differentially expressed leprosy related genes, which were enriched in activation and regulation of immune response, was obtained in our analyses. Cross-disorder analysis showed that the list of leprosy susceptibility genes was largely shared by typical autoimmune diseases such as lupus erythematosus and arthritis, suggesting that similar pathways might be affected in leprosy and autoimmune diseases. Protein-protein interaction (PPI) and positive selection analyses revealed a co-evolution network of leprosy risk genes. Our analyses showed that leprosy associated genes constituted a co-evolution network and might undergo positive selection driven by M. leprae. We suggested that leprosy may be a kind of autoimmune disease and the development of leprosy is a matter of defect or over-activation of body immunity. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Gene regulatory networks in lactation: identification of global principles using bioinformatics.

PubMed

Lemay, Danielle G; Neville, Margaret C; Rudolph, Michael C; Pollard, Katherine S; German, J Bruce

2007-11-27

The molecular events underlying mammary development during pregnancy, lactation, and involution are incompletely understood. Mammary gland microarray data, cellular localization data, protein-protein interactions, and literature-mined genes were integrated and analyzed using statistics, principal component analysis, gene ontology analysis, pathway analysis, and network analysis to identify global biological principles that govern molecular events during pregnancy, lactation, and involution. Several key principles were derived: (1) nearly a third of the transcriptome fluctuates to build, run, and disassemble the lactation apparatus; (2) genes encoding the secretory machinery are transcribed prior to lactation; (3) the diversity of the endogenous portion of the milk proteome is derived from fewer than 100 transcripts; (4) while some genes are differentially transcribed near the onset of lactation, the lactation switch is primarily post-transcriptionally mediated; (5) the secretion of materials during lactation occurs not by up-regulation of novel genomic functions, but by widespread transcriptional suppression of functions such as protein degradation and cell-environment communication; (6) the involution switch is primarily transcriptionally mediated; and (7) during early involution, the transcriptional state is partially reverted to the pre-lactation state. A new hypothesis for secretory diminution is suggested - milk production gradually declines because the secretory machinery is not transcriptionally replenished. A comprehensive network of protein interactions during lactation is assembled and new regulatory gene targets are identified. Less than one fifth of the transcriptionally regulated nodes in this lactation network have been previously explored in the context of lactation. Implications for future research in mammary and cancer biology are discussed.

Towards systems biology of the gravity response of higher plants -multiscale analysis of Arabidopsis thaliana root growth

NASA Astrophysics Data System (ADS)

Palme, Klaus; Aubry, D.; Bensch, M.; Schmidt, T.; Ronneberger, O.; Neu, C.; Li, X.; Wang, H.; Santos, F.; Wang, B.; Paponov, I.; Ditengou, F. A.; Teale, W. T.; Volkmann, D.; Baluska, F.; Nonis, A.; Trevisan, S.; Ruperti, B.; Dovzhenko, A.

Gravity plays a fundamental role in plant growth and development. Up to now, little is known about the molecular organisation of the signal transduction cascades and networks which co-ordinate gravity perception and response. By using an integrated systems biological approach, a systems analysis of gravity perception and the subsequent tightly-regulated growth response is planned in the model plant Arabidopsis thaliana. This approach will address questions such as: (i) what are the components of gravity signal transduction pathways? (ii) what are the dynamics of these components? (iii) what is their spatio-temporal regulation in different tis-sues? Using Arabidopsis thaliana as a model-we use root growth to obtain insights in the gravity response. New techniques enable identification of the individual genes affected by grav-ity and further integration of transcriptomics and proteomics data into interaction networks and cell communication events that operate during gravitropic curvature. Using systematic multiscale analysis we have identified regulatory networks consisting of transcription factors, the protein degradation machinery, vesicle trafficking and cellular signalling during the gravire-sponse. We developed approach allowing to incorporate key features of the root system across all relevant spatial and temporal scales to describe gene-expression patterns and correlate them with individual gene and protein functions. Combination of high-resolution microscopy and novel computational tools resulted in development of the root 3D model in which quantitative descriptions of cellular network properties and of multicellular interactions important in root growth and gravitropism can be integrated for the first time.

A Data Driven Model for Predicting RNA-Protein Interactions based on Gradient Boosting Machine.

PubMed

Jain, Dharm Skandh; Gupte, Sanket Rajan; Aduri, Raviprasad

2018-06-22

RNA protein interactions (RPI) play a pivotal role in the regulation of various biological processes. Experimental validation of RPI has been time-consuming, paving the way for computational prediction methods. The major limiting factor of these methods has been the accuracy and confidence of the predictions, and our in-house experiments show that they fail to accurately predict RPI involving short RNA sequences such as TERRA RNA. Here, we present a data-driven model for RPI prediction using a gradient boosting classifier. Amino acids and nucleotides are classified based on the high-resolution structural data of RNA protein complexes. The minimum structural unit consisting of five residues is used as the descriptor. Comparative analysis of existing methods shows the consistently higher performance of our method irrespective of the length of RNA present in the RPI. The method has been successfully applied to map RPI networks involving both long noncoding RNA as well as TERRA RNA. The method is also shown to successfully predict RNA and protein hubs present in RPI networks of four different organisms. The robustness of this method will provide a way for predicting RPI networks of yet unknown interactions for both long noncoding RNA and microRNA.

Identification of key regulators of pancreatic cancer progression through multidimensional systems-level analysis.

PubMed

Rajamani, Deepa; Bhasin, Manoj K

2016-05-03

Pancreatic cancer is an aggressive cancer with dismal prognosis, urgently necessitating better biomarkers to improve therapeutic options and early diagnosis. Traditional approaches of biomarker detection that consider only one aspect of the biological continuum like gene expression alone are limited in their scope and lack robustness in identifying the key regulators of the disease. We have adopted a multidimensional approach involving the cross-talk between the omics spaces to identify key regulators of disease progression. Multidimensional domain-specific disease signatures were obtained using rank-based meta-analysis of individual omics profiles (mRNA, miRNA, DNA methylation) related to pancreatic ductal adenocarcinoma (PDAC). These domain-specific PDAC signatures were integrated to identify genes that were affected across multiple dimensions of omics space in PDAC (genes under multiple regulatory controls, GMCs). To further pin down the regulators of PDAC pathophysiology, a systems-level network was generated from knowledge-based interaction information applied to the above identified GMCs. Key regulators were identified from the GMC network based on network statistics and their functional importance was validated using gene set enrichment analysis and survival analysis. Rank-based meta-analysis identified 5391 genes, 109 miRNAs and 2081 methylation-sites significantly differentially expressed in PDAC (false discovery rate ≤ 0.05). Bimodal integration of meta-analysis signatures revealed 1150 and 715 genes regulated by miRNAs and methylation, respectively. Further analysis identified 189 altered genes that are commonly regulated by miRNA and methylation, hence considered GMCs. Systems-level analysis of the scale-free GMCs network identified eight potential key regulator hubs, namely E2F3, HMGA2, RASA1, IRS1, NUAK1, ACTN1, SKI and DLL1, associated with important pathways driving cancer progression. Survival analysis on individual key regulators revealed that higher expression of IRS1 and DLL1 and lower expression of HMGA2, ACTN1 and SKI were associated with better survival probabilities. It is evident from the results that our hierarchical systems-level multidimensional analysis approach has been successful in isolating the converging regulatory modules and associated key regulatory molecules that are potential biomarkers for pancreatic cancer progression.

The identification of key genes and pathways in hepatocellular carcinoma by bioinformatics analysis of high-throughput data.

PubMed

Zhang, Chaoyang; Peng, Li; Zhang, Yaqin; Liu, Zhaoyang; Li, Wenling; Chen, Shilian; Li, Guancheng

2017-06-01

Liver cancer is a serious threat to public health and has fairly complicated pathogenesis. Therefore, the identification of key genes and pathways is of much importance for clarifying molecular mechanism of hepatocellular carcinoma (HCC) initiation and progression. HCC-associated gene expression dataset was downloaded from Gene Expression Omnibus database. Statistical software R was used for significance analysis of differentially expressed genes (DEGs) between liver cancer samples and normal samples. Gene Ontology (GO) term enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, based on R software, were applied for the identification of pathways in which DEGs significantly enriched. Cytoscape software was for the construction of protein-protein interaction (PPI) network and module analysis to find the hub genes and key pathways. Finally, weighted correlation network analysis (WGCNA) was conducted to further screen critical gene modules with similar expression pattern and explore their biological significance. Significance analysis identified 1230 DEGs with fold change >2, including 632 significantly down-regulated DEGs and 598 significantly up-regulated DEGs. GO term enrichment analysis suggested that up-regulated DEG significantly enriched in immune response, cell adhesion, cell migration, type I interferon signaling pathway, and cell proliferation, and the down-regulated DEG mainly enriched in response to endoplasmic reticulum stress and endoplasmic reticulum unfolded protein response. KEGG pathway analysis found DEGs significantly enriched in five pathways including complement and coagulation cascades, focal adhesion, ECM-receptor interaction, antigen processing and presentation, and protein processing in endoplasmic reticulum. The top 10 hub genes in HCC were separately GMPS, ACACA, ALB, TGFB1, KRAS, ERBB2, BCL2, EGFR, STAT3, and CD8A, which resulted from PPI network. The top 3 gene interaction modules in PPI network enriched in immune response, organ development, and response to other organism, respectively. WGCNA revealed that the confirmed eight gene modules significantly enriched in monooxygenase and oxidoreductase activity, response to endoplasmic reticulum stress, type I interferon signaling pathway, processing, presentation and binding of peptide antigen, cellular response to cadmium and zinc ion, cell locomotion and differentiation, ribonucleoprotein complex and RNA processing, and immune system process, respectively. In conclusion, we identified some key genes and pathways closely related with HCC initiation and progression by a series of bioinformatics analysis on DEGs. These screened genes and pathways provided for a more detailed molecular mechanism underlying HCC occurrence and progression, holding promise for acting as biomarkers and potential therapeutic targets.

Network and biosignature analysis for the integration of transcriptomic and metabolomic data to characterize leaf senescence process in sunflower.

PubMed

Moschen, Sebastián; Higgins, Janet; Di Rienzo, Julio A; Heinz, Ruth A; Paniego, Norma; Fernandez, Paula

2016-06-06

In recent years, high throughput technologies have led to an increase of datasets from omics disciplines allowing the understanding of the complex regulatory networks associated with biological processes. Leaf senescence is a complex mechanism controlled by multiple genetic and environmental variables, which has a strong impact on crop yield. Transcription factors (TFs) are key proteins in the regulation of gene expression, regulating different signaling pathways; their function is crucial for triggering and/or regulating different aspects of the leaf senescence process. The study of TF interactions and their integration with metabolic profiles under different developmental conditions, especially for a non-model organism such as sunflower, will open new insights into the details of gene regulation of leaf senescence. Weighted Gene Correlation Network Analysis (WGCNA) and BioSignature Discoverer (BioSD, Gnosis Data Analysis, Heraklion, Greece) were used to integrate transcriptomic and metabolomic data. WGCNA allowed the detection of 10 metabolites and 13 TFs whereas BioSD allowed the detection of 1 metabolite and 6 TFs as potential biomarkers. The comparative analysis demonstrated that three transcription factors were detected through both methodologies, highlighting them as potentially robust biomarkers associated with leaf senescence in sunflower. The complementary use of network and BioSignature Discoverer analysis of transcriptomic and metabolomic data provided a useful tool for identifying candidate genes and metabolites which may have a role during the triggering and development of the leaf senescence process. The WGCNA tool allowed us to design and test a hypothetical network in order to infer relationships across selected transcription factor and metabolite candidate biomarkers involved in leaf senescence, whereas BioSignature Discoverer selected transcripts and metabolites which discriminate between different ages of sunflower plants. The methodology presented here would help to elucidate and predict novel networks and potential biomarkers of leaf senescence in sunflower.

How reliable is the linear noise approximation of gene regulatory networks?

PubMed Central

2013-01-01

Background The linear noise approximation (LNA) is commonly used to predict how noise is regulated and exploited at the cellular level. These predictions are exact for reaction networks composed exclusively of first order reactions or for networks involving bimolecular reactions and large numbers of molecules. It is however well known that gene regulation involves bimolecular interactions with molecule numbers as small as a single copy of a particular gene. It is therefore questionable how reliable are the LNA predictions for these systems. Results We implement in the software package intrinsic Noise Analyzer (iNA), a system size expansion based method which calculates the mean concentrations and the variances of the fluctuations to an order of accuracy higher than the LNA. We then use iNA to explore the parametric dependence of the Fano factors and of the coefficients of variation of the mRNA and protein fluctuations in models of genetic networks involving nonlinear protein degradation, post-transcriptional, post-translational and negative feedback regulation. We find that the LNA can significantly underestimate the amplitude and period of noise-induced oscillations in genetic oscillators. We also identify cases where the LNA predicts that noise levels can be optimized by tuning a bimolecular rate constant whereas our method shows that no such regulation is possible. All our results are confirmed by stochastic simulations. Conclusion The software iNA allows the investigation of parameter regimes where the LNA fares well and where it does not. We have shown that the parametric dependence of the coefficients of variation and Fano factors for common gene regulatory networks is better described by including terms of higher order than LNA in the system size expansion. This analysis is considerably faster than stochastic simulations due to the extensive ensemble averaging needed to obtain statistically meaningful results. Hence iNA is well suited for performing computationally efficient and quantitative studies of intrinsic noise in gene regulatory networks. PMID:24266939

[Mechanism of Tongsaimai tablet for atherosclerosis based on network pharmacology].

PubMed

Li, Na; Zhang, Xin-Zhuang; Wang, Yan-Ru; Cao, Liang; Ding, Gang; Wang, Zhen-Zhong; Xiao, Wei; Xu, Xiao-Jie

2016-05-01

Network pharmacology method was adopted in this study to explore the active compounds and mechanism of Tongsaimai tablets for atherosclerosis. In molecular docking and molecular-target protein network analysis, 97 molecules in Tongsaimai tablets showed good interaction with the atherosclerosis-related target protein (docking score ≥ 7), and 37 molecules of them could act on more than 2 targets (≥ 2) with higher betweenness, suggesting that these 37 molecules might be the main active compounds group in Tongsaimai tablets for atherosclerosis treatment. Furthermore, the predicted active compounds contained more flavonoids and saponins, reminding more attention should be paid on flavonoids and saponins in study of effective compounds and quality standards of Tongsaimai tablets. Targets network analysis showed that, the active compounds of Tongsaimai tablets could regulate inflammation, stabilize plaque, protect vascular endothelial cell, regulate blood lipid and inhibit blood coagulation through acting on the main 22 target proteins, such as Toll-like receptors (TLR1, TLR2), matrix metalloproteinase (MMP1, MMP2, MMP3, MMP9), angiotensin converting enzyme (ACE), leukotriene A4 hydrolase (LTA4-H), 5-lipoxidase (5-LOX), peroxisome proliferators-activated receptors (PPARα, PPARγ). These active compounds can participate in regulating different pathologic stages of atherosclerosis and thus treat atherosclerosis finally. This study revealed the main active compounds and possible mechanism of Tongsaimai tablets for treatment of atherosclerosis and meanwhile, verified the characteristics of multi-components, multi-targets and integral regulation for Tongsaimai tablets, providing theoretical references for the following systematic laboratory experiments on effective compounds and action mechanism of Tongsaimai Tablet. Copyright© by the Chinese Pharmaceutical Association.

Co-acting gene networks predict TRAIL responsiveness of tumour cells with high accuracy.

PubMed

O'Reilly, Paul; Ortutay, Csaba; Gernon, Grainne; O'Connell, Enda; Seoighe, Cathal; Boyce, Susan; Serrano, Luis; Szegezdi, Eva

2014-12-19

Identification of differentially expressed genes from transcriptomic studies is one of the most common mechanisms to identify tumor biomarkers. This approach however is not well suited to identify interaction between genes whose protein products potentially influence each other, which limits its power to identify molecular wiring of tumour cells dictating response to a drug. Due to the fact that signal transduction pathways are not linear and highly interlinked, the biological response they drive may be better described by the relative amount of their components and their functional relationships than by their individual, absolute expression. Gene expression microarray data for 109 tumor cell lines with known sensitivity to the death ligand cytokine tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) was used to identify genes with potential functional relationships determining responsiveness to TRAIL-induced apoptosis. The machine learning technique Random Forest in the statistical environment "R" with backward elimination was used to identify the key predictors of TRAIL sensitivity and differentially expressed genes were identified using the software GeneSpring. Gene co-regulation and statistical interaction was assessed with q-order partial correlation analysis and non-rejection rate. Biological (functional) interactions amongst the co-acting genes were studied with Ingenuity network analysis. Prediction accuracy was assessed by calculating the area under the receiver operator curve using an independent dataset. We show that the gene panel identified could predict TRAIL-sensitivity with a very high degree of sensitivity and specificity (AUC=0·84). The genes in the panel are co-regulated and at least 40% of them functionally interact in signal transduction pathways that regulate cell death and cell survival, cellular differentiation and morphogenesis. Importantly, only 12% of the TRAIL-predictor genes were differentially expressed highlighting the importance of functional interactions in predicting the biological response. The advantage of co-acting gene clusters is that this analysis does not depend on differential expression and is able to incorporate direct- and indirect gene interactions as well as tissue- and cell-specific characteristics. This approach (1) identified a descriptor of TRAIL sensitivity which performs significantly better as a predictor of TRAIL sensitivity than any previously reported gene signatures, (2) identified potential novel regulators of TRAIL-responsiveness and (3) provided a systematic view highlighting fundamental differences between the molecular wiring of sensitive and resistant cell types.

Allosteric pathway identification through network analysis: from molecular dynamics simulations to interactive 2D and 3D graphs.

PubMed

Allain, Ariane; Chauvot de Beauchêne, Isaure; Langenfeld, Florent; Guarracino, Yann; Laine, Elodie; Tchertanov, Luba

2014-01-01

Allostery is a universal phenomenon that couples the information induced by a local perturbation (effector) in a protein to spatially distant regulated sites. Such an event can be described in terms of a large scale transmission of information (communication) through a dynamic coupling between structurally rigid (minimally frustrated) and plastic (locally frustrated) clusters of residues. To elaborate a rational description of allosteric coupling, we propose an original approach - MOdular NETwork Analysis (MONETA) - based on the analysis of inter-residue dynamical correlations to localize the propagation of both structural and dynamical effects of a perturbation throughout a protein structure. MONETA uses inter-residue cross-correlations and commute times computed from molecular dynamics simulations and a topological description of a protein to build a modular network representation composed of clusters of residues (dynamic segments) linked together by chains of residues (communication pathways). MONETA provides a brand new direct and simple visualization of protein allosteric communication. A GEPHI module implemented in the MONETA package allows the generation of 2D graphs of the communication network. An interactive PyMOL plugin permits drawing of the communication pathways between chosen protein fragments or residues on a 3D representation. MONETA is a powerful tool for on-the-fly display of communication networks in proteins. We applied MONETA for the analysis of communication pathways (i) between the main regulatory fragments of receptors tyrosine kinases (RTKs), KIT and CSF-1R, in the native and mutated states and (ii) in proteins STAT5 (STAT5a and STAT5b) in the phosphorylated and the unphosphorylated forms. The description of the physical support for allosteric coupling by MONETA allowed a comparison of the mechanisms of (a) constitutive activation induced by equivalent mutations in two RTKs and (b) allosteric regulation in the activated and non-activated STAT5 proteins. Our theoretical prediction based on results obtained with MONETA was validated for KIT by in vitro experiments. MONETA is a versatile analytical and visualization tool entirely devoted to the understanding of the functioning/malfunctioning of allosteric regulation in proteins - a crucial basis to guide the discovery of next-generation allosteric drugs.

Transcriptional network systems in cartilage development and disease.

PubMed

Nishimura, Riko; Hata, Kenji; Nakamura, Eriko; Murakami, Tomohiko; Takahata, Yoshifumi

2018-04-01

Transcription factors play important roles in the regulation of cartilage development by controlling the expression of chondrogenic genes. Genetic studies have revealed that Sox9/Sox5/Sox6, Runx2/Runx3 and Osterix in particular are essential for the sequential steps of cartilage development. Importantly, these transcription factors form network systems that are also required for appropriate cartilage development. Molecular cloning approaches have largely contributed to the identification of several transcriptional partners for Sox9 and Runx2 during cartilage development. Although the importance of a negative-feedback loop between Indian hedgehog (Ihh) and parathyroid hormone-related protein (PTHrP) in chondrocyte hypertrophy has been well established, recent studies indicate that several transcription factors interact with the Ihh-PTHrP loop and demonstrated that Ihh has multiple functions in the regulation of cartilage development. The most common cartilage disorder, osteoarthritis, has been reported to result from the pathological action of several transcription factors, including Runx2, C/EBPβ and HIF-2α. On the other hand, NFAT family members appear to play roles in the protection of cartilage from osteoarthritis. It is also becoming important to understand the homeostasis and regulation of articular chondrocytes, because they have different cellular and molecular features from chondrocytes of the growth plate. This review summarizes the regulation and roles of transcriptional network systems in cartilage development and their pathological roles in osteoarthritis.

A network of conserved formins, regulated by the guanine exchange factor EXC-5 and the GTPase CDC-42, modulates tubulogenesis in vivo.

PubMed

Shaye, Daniel D; Greenwald, Iva

2016-11-15

The C. elegans excretory cell (EC) is a powerful model for tubulogenesis, a conserved process that requires precise cytoskeletal regulation. EXC-6, an ortholog of the disease-associated formin INF2, coordinates cell outgrowth and lumen formation during EC tubulogenesis by regulating F-actin at the tip of the growing canal and the dynamics of basolateral microtubules. EXC-6 functions in parallel with EXC-5/FGD, a predicted activator of the Rho GTPase Cdc42. Here, we identify the parallel pathway: EXC-5 functions through CDC-42 to regulate two other formins: INFT-2, another INF2 ortholog, and CYK-1, the sole ortholog of the mammalian diaphanous (mDia) family of formins. We show that INFT-2 promotes F-actin accumulation in the EC, and that CYK-1 inhibits INFT-2 to regulate F-actin levels and EXC-6-promoted outgrowth. As INF2 and mDia physically interact and cross-regulate in cultured cells, our work indicates that a conserved EXC-5-CDC-42 pathway modulates this regulatory interaction and that it is functionally important in vivo during tubulogenesis. © 2016. Published by The Company of Biologists Ltd.

Post-transcriptional inducible gene regulation by natural antisense RNA.

PubMed

Nishizawa, Mikio; Ikeya, Yukinobu; Okumura, Tadayoshi; Kimura, Tominori

2015-01-01

Accumulating data indicate the existence of natural antisense transcripts (asRNAs), frequently transcribed from eukaryotic genes and do not encode proteins in many cases. However, their importance has been overlooked due to their heterogeneity, low expression level, and unknown function. Genes induced in responses to various stimuli are transcriptionally regulated by the activation of a gene promoter and post-transcriptionally regulated by controlling mRNA stability and translatability. A low-copy-number asRNA may post-transcriptionally regulate gene expression with cis-controlling elements on the mRNA. The asRNA itself may act as regulatory RNA in concert with trans-acting factors, including various RNA-binding proteins that bind to cis-controlling elements, microRNAs, and drugs. A novel mechanism that regulates mRNA stability includes the interaction of asRNA with mRNA by hybridization to loops in secondary structures. Furthermore, recent studies have shown that the functional network of mRNAs, asRNAs, and microRNAs finely tunes the levels of mRNA expression. The post-transcriptional mechanisms via these RNA-RNA interactions may play pivotal roles to regulate inducible gene expression and present the possibility of the involvement of asRNAs in various diseases.

Anatomy of the bacitracin resistance network in Bacillus subtilis.

PubMed

Radeck, Jara; Gebhard, Susanne; Orchard, Peter Shevlin; Kirchner, Marion; Bauer, Stephanie; Mascher, Thorsten; Fritz, Georg

2016-05-01

Protection against antimicrobial peptides (AMPs) often involves the parallel production of multiple, well-characterized resistance determinants. So far, little is known about how these resistance modules interact and how they jointly protect the cell. Here, we studied the interdependence between different layers of the envelope stress response of Bacillus subtilis when challenged with the lipid II cycle-inhibiting AMP bacitracin. The underlying regulatory network orchestrates the production of the ABC transporter BceAB, the UPP phosphatase BcrC and the phage-shock proteins LiaIH. Our systems-level analysis reveals a clear hierarchy, allowing us to discriminate between primary (BceAB) and secondary (BcrC and LiaIH) layers of bacitracin resistance. Deleting the primary layer provokes an enhanced induction of the secondary layer to partially compensate for this loss. This study reveals a direct role of LiaIH in bacitracin resistance, provides novel insights into the feedback regulation of the Lia system, and demonstrates a pivotal role of BcrC in maintaining cell wall homeostasis. The compensatory regulation within the bacitracin network can also explain how gene expression noise propagates between resistance layers. We suggest that this active redundancy in the bacitracin resistance network of B. subtilis is a general principle to be found in many bacterial antibiotic resistance networks. © 2016 John Wiley & Sons Ltd.

Histone chaperones: an escort network regulating histone traffic.

PubMed

De Koning, Leanne; Corpet, Armelle; Haber, James E; Almouzni, Geneviève

2007-11-01

In eukaryotes, DNA is organized into chromatin in a dynamic manner that enables it to be accessed for processes such as transcription and repair. Histones, the chief protein component of chromatin, must be assembled, replaced or exchanged to preserve or change this organization according to cellular needs. Histone chaperones are key actors during histone metabolism. Here we classify known histone chaperones and discuss how they build a network to escort histone proteins. Molecular interactions with histones and their potential specificity or redundancy are also discussed in light of chaperone structural properties. The multiplicity of histone chaperone partners, including histone modifiers, nucleosome remodelers and cell-cycle regulators, is relevant to their coordination with key cellular processes. Given the current interest in chromatin as a source of epigenetic marks, we address the potential contributions of histone chaperones to epigenetic memory and genome stability.

Graph Theory-Based Analysis of the Lymph Node Fibroblastic Reticular Cell Network.

PubMed

Novkovic, Mario; Onder, Lucas; Bocharov, Gennady; Ludewig, Burkhard

2017-01-01

Secondary lymphoid organs have developed segregated niches that are able to initiate and maintain effective immune responses. Such global organization requires tight control of diverse cellular components, specifically those that regulate lymphocyte trafficking. Fibroblastic reticular cells (FRCs) form a densely interconnected network in lymph nodes and provide key factors necessary for T cell migration and retention, and foster subsequent interactions between T cells and dendritic cells. Development of integrative systems biology approaches has made it possible to elucidate this multilevel complexity of the immune system. Here, we present a graph theory-based analysis of the FRC network in murine lymph nodes, where generation of the network topology is performed using high-resolution confocal microscopy and 3D reconstruction. This approach facilitates the analysis of physical cell-to-cell connectivity, and estimation of topological robustness and global behavior of the network when it is subjected to perturbation in silico.

Auxin-BR Interaction Regulates Plant Growth and Development

PubMed Central

Tian, Huiyu; Lv, Bingsheng; Ding, Tingting; Bai, Mingyi; Ding, Zhaojun

2018-01-01

Plants develop a high flexibility to alter growth, development, and metabolism to adapt to the ever-changing environments. Multiple signaling pathways are involved in these processes and the molecular pathways to transduce various developmental signals are not linear but are interconnected by a complex network and even feedback mutually to achieve the final outcome. This review will focus on two important plant hormones, auxin and brassinosteroid (BR), based on the most recent progresses about these two hormone regulated plant growth and development in Arabidopsis, and highlight the cross-talks between these two phytohormones. PMID:29403511

Tinman/Nkx2-5 acts via miR-1 and upstream of Cdc42 to regulate heart function across species

PubMed Central

Wythe, Joshua D.; Liu, Jiandong; Cartry, Jerome; Vogler, Georg; Mohapatra, Bhagyalaxmi; Otway, Robyn T.; Huang, Yu; King, Isabelle N.; Maillet, Marjorie; Zheng, Yi; Crawley, Timothy; Taghli-Lamallem, Ouarda; Semsarian, Christopher; Dunwoodie, Sally; Winlaw, David; Harvey, Richard P.; Fatkin, Diane; Towbin, Jeffrey A.; Molkentin, Jeffery D.; Srivastava, Deepak; Ocorr, Karen; Bruneau, Benoit G.

2011-01-01

Unraveling the gene regulatory networks that govern development and function of the mammalian heart is critical for the rational design of therapeutic interventions in human heart disease. Using the Drosophila heart as a platform for identifying novel gene interactions leading to heart disease, we found that the Rho-GTPase Cdc42 cooperates with the cardiac transcription factor Tinman/Nkx2-5. Compound Cdc42, tinman heterozygous mutant flies exhibited impaired cardiac output and altered myofibrillar architecture, and adult heart–specific interference with Cdc42 function is sufficient to cause these same defects. We also identified K+ channels, encoded by dSUR and slowpoke, as potential effectors of the Cdc42–Tinman interaction. To determine whether a Cdc42–Nkx2-5 interaction is conserved in the mammalian heart, we examined compound heterozygous mutant mice and found conduction system and cardiac output defects. In exploring the mechanism of Nkx2-5 interaction with Cdc42, we demonstrated that mouse Cdc42 was a target of, and negatively regulated by miR-1, which itself was negatively regulated by Nkx2-5 in the mouse heart and by Tinman in the fly heart. We conclude that Cdc42 plays a conserved role in regulating heart function and is an indirect target of Tinman/Nkx2-5 via miR-1. PMID:21690310

Behavior control in the sensorimotor loop with short-term synaptic dynamics induced by self-regulating neurons.

PubMed

Toutounji, Hazem; Pasemann, Frank

2014-01-01

The behavior and skills of living systems depend on the distributed control provided by specialized and highly recurrent neural networks. Learning and memory in these systems is mediated by a set of adaptation mechanisms, known collectively as neuronal plasticity. Translating principles of recurrent neural control and plasticity to artificial agents has seen major strides, but is usually hampered by the complex interactions between the agent's body and its environment. One of the important standing issues is for the agent to support multiple stable states of behavior, so that its behavioral repertoire matches the requirements imposed by these interactions. The agent also must have the capacity to switch between these states in time scales that are comparable to those by which sensory stimulation varies. Achieving this requires a mechanism of short-term memory that allows the neurocontroller to keep track of the recent history of its input, which finds its biological counterpart in short-term synaptic plasticity. This issue is approached here by deriving synaptic dynamics in recurrent neural networks. Neurons are introduced as self-regulating units with a rich repertoire of dynamics. They exhibit homeostatic properties for certain parameter domains, which result in a set of stable states and the required short-term memory. They can also operate as oscillators, which allow them to surpass the level of activity imposed by their homeostatic operation conditions. Neural systems endowed with the derived synaptic dynamics can be utilized for the neural behavior control of autonomous mobile agents. The resulting behavior depends also on the underlying network structure, which is either engineered or developed by evolutionary techniques. The effectiveness of these self-regulating units is demonstrated by controlling locomotion of a hexapod with 18 degrees of freedom, and obstacle-avoidance of a wheel-driven robot.

MicroRNAs as Key Effectors in the p53 Network.

PubMed

Goeman, Frauke; Strano, Sabrina; Blandino, Giovanni

2017-01-01

The guardian of the genome p53 is embedded in a fine-spun network of MicroRNAs. p53 is able to activate or repress directly the transcription of MicroRNAs that are participating in the tumor-suppressive mission of p53. On the other hand, the expression of p53 is under tight control of MicroRNAs that are either targeting directly p53 or factors that are modifying its protein level or activity. Although the most important function of p53 is suggested to be transcriptional regulation, there are several nontranscriptional functions described. One of those regards the modulation of MicroRNA biogenesis. Wild-type p53 is increasing the maturation of selected MicroRNAs from the primary transcript to the precursor MiRNA by interacting with the Microprocessor complex. Furthermore, p53 is modulating the mRNA accessibility for certain MicroRNAs by association with the RISC complex and transcriptional regulation of RNA-binding proteins. In this way p53 is able to remodel the MiRNA-mRNA interaction network. As wild-type p53 is employing MicroRNAs to suppress cancer development, gain-of-function mutant p53 proteins use MicroRNAs to confer oncogenic properties like chemoresistance and the ability to drive metastasis. Like its wild-type counterpart mutant p53 is able to regulate MicroRNAs transcriptionally and posttranscriptionally. Mutant p53 affects the MiRNA processing at two cleavage steps through interfering with the Microprocessor complex and by downregulating Dicer and KSRP, a modulator of MiRNA biogenesis. Thus, MicroRNAs are essential components in the p53 pathway, contributing substantially to combat or enhance tumor development depending on the wild-type or mutant p53 context. © 2017 Elsevier Inc. All rights reserved.

The central role of AMP-kinase and energy homeostasis impairment in Alzheimer's disease: a multifactor network analysis.

PubMed

Caberlotto, Laura; Lauria, Mario; Nguyen, Thanh-Phuong; Scotti, Marco

2013-01-01

Alzheimer's disease is the most common cause of dementia worldwide, affecting the elderly population. It is characterized by the hallmark pathology of amyloid-β deposition, neurofibrillary tangle formation, and extensive neuronal degeneration in the brain. Wealth of data related to Alzheimer's disease has been generated to date, nevertheless, the molecular mechanism underlying the etiology and pathophysiology of the disease is still unknown. Here we described a method for the combined analysis of multiple types of genome-wide data aimed at revealing convergent evidence interest that would not be captured by a standard molecular approach. Lists of Alzheimer-related genes (seed genes) were obtained from different sets of data on gene expression, SNPs, and molecular targets of drugs. Network analysis was applied for identifying the regions of the human protein-protein interaction network showing a significant enrichment in seed genes, and ultimately, in genes associated to Alzheimer's disease, due to the cumulative effect of different combinations of the starting data sets. The functional properties of these enriched modules were characterized, effectively considering the role of both Alzheimer-related seed genes and genes that closely interact with them. This approach allowed us to present evidence in favor of one of the competing theories about AD underlying processes, specifically evidence supporting a predominant role of metabolism-associated biological process terms, including autophagy, insulin and fatty acid metabolic processes in Alzheimer, with a focus on AMP-activated protein kinase. This central regulator of cellular energy homeostasis regulates a series of brain functions altered in Alzheimer's disease and could link genetic perturbation with neuronal transmission and energy regulation, representing a potential candidate to be targeted by therapy.

Behavior control in the sensorimotor loop with short-term synaptic dynamics induced by self-regulating neurons

PubMed Central

Toutounji, Hazem; Pasemann, Frank

2014-01-01

The behavior and skills of living systems depend on the distributed control provided by specialized and highly recurrent neural networks. Learning and memory in these systems is mediated by a set of adaptation mechanisms, known collectively as neuronal plasticity. Translating principles of recurrent neural control and plasticity to artificial agents has seen major strides, but is usually hampered by the complex interactions between the agent's body and its environment. One of the important standing issues is for the agent to support multiple stable states of behavior, so that its behavioral repertoire matches the requirements imposed by these interactions. The agent also must have the capacity to switch between these states in time scales that are comparable to those by which sensory stimulation varies. Achieving this requires a mechanism of short-term memory that allows the neurocontroller to keep track of the recent history of its input, which finds its biological counterpart in short-term synaptic plasticity. This issue is approached here by deriving synaptic dynamics in recurrent neural networks. Neurons are introduced as self-regulating units with a rich repertoire of dynamics. They exhibit homeostatic properties for certain parameter domains, which result in a set of stable states and the required short-term memory. They can also operate as oscillators, which allow them to surpass the level of activity imposed by their homeostatic operation conditions. Neural systems endowed with the derived synaptic dynamics can be utilized for the neural behavior control of autonomous mobile agents. The resulting behavior depends also on the underlying network structure, which is either engineered or developed by evolutionary techniques. The effectiveness of these self-regulating units is demonstrated by controlling locomotion of a hexapod with 18 degrees of freedom, and obstacle-avoidance of a wheel-driven robot. PMID:24904403

A candidate multimodal functional genetic network for thermal adaptation

PubMed Central

Pathak, Rachana; Prajapati, Indira; Bankston, Shannon; Thompson, Aprylle; Usher, Jaytriece; Isokpehi, Raphael D.

2014-01-01

Vertebrate ectotherms such as reptiles provide ideal organisms for the study of adaptation to environmental thermal change. Comparative genomic and exomic studies can recover markers that diverge between warm and cold adapted lineages, but the genes that are functionally related to thermal adaptation may be difficult to identify. We here used a bioinformatics genome-mining approach to predict and identify functions for suitable candidate markers for thermal adaptation in the chicken. We first established a framework of candidate functions for such markers, and then compiled the literature on genes known to adapt to the thermal environment in different lineages of vertebrates. We then identified them in the genomes of human, chicken, and the lizard Anolis carolinensis, and established a functional genetic interaction network in the chicken. Surprisingly, markers initially identified from diverse lineages of vertebrates such as human and fish were all in close functional relationship with each other and more associated than expected by chance. This indicates that the general genetic functional network for thermoregulation and/or thermal adaptation to the environment might be regulated via similar evolutionarily conserved pathways in different vertebrate lineages. We were able to identify seven functions that were statistically overrepresented in this network, corresponding to four of our originally predicted functions plus three unpredicted functions. We describe this network as multimodal: central regulator genes with the function of relaying thermal signal (1), affect genes with different cellular functions, namely (2) lipoprotein metabolism, (3) membrane channels, (4) stress response, (5) response to oxidative stress, (6) muscle contraction and relaxation, and (7) vasodilation, vasoconstriction and regulation of blood pressure. This network constitutes a novel resource for the study of thermal adaptation in the closely related nonavian reptiles and other vertebrate ectotherms. PMID:25289178

The Modular Organization of Protein Interactions in Escherichia coli

PubMed Central

Peregrín-Alvarez, José M.; Xiong, Xuejian; Su, Chong; Parkinson, John

2009-01-01

Escherichia coli serves as an excellent model for the study of fundamental cellular processes such as metabolism, signalling and gene expression. Understanding the function and organization of proteins within these processes is an important step towards a ‘systems’ view of E. coli. Integrating experimental and computational interaction data, we present a reliable network of 3,989 functional interactions between 1,941 E. coli proteins (∼45% of its proteome). These were combined with a recently generated set of 3,888 high-quality physical interactions between 918 proteins and clustered to reveal 316 discrete modules. In addition to known protein complexes (e.g., RNA and DNA polymerases), we identified modules that represent biochemical pathways (e.g., nitrate regulation and cell wall biosynthesis) as well as batteries of functionally and evolutionarily related processes. To aid the interpretation of modular relationships, several case examples are presented, including both well characterized and novel biochemical systems. Together these data provide a global view of the modular organization of the E. coli proteome and yield unique insights into structural and evolutionary relationships in bacterial networks. PMID:19798435

Diversification of transcription factor-DNA interactions and the evolution of gene regulatory networks.

PubMed

Rogers, Julia M; Bulyk, Martha L

2018-04-25

Sequence-specific transcription factors (TFs) bind short DNA sequences in the genome to regulate the expression of target genes. In the last decade, numerous technical advances have enabled the determination of the DNA-binding specificities of many of these factors. Large-scale screens of many TFs enabled the creation of databases of TF DNA-binding specificities, typically represented as position weight matrices (PWMs). Although great progress has been made in determining and predicting binding specificities systematically, there are still many surprises to be found when studying a particular TF's interactions with DNA in detail. Paralogous TFs' binding specificities can differ in subtle ways, in a manner that is not immediately apparent from looking at their PWMs. These differences affect gene regulatory outputs and enable TFs to rewire transcriptional networks over evolutionary time. This review discusses recent observations made in the study of TF-DNA interactions that highlight the importance of continued in-depth analysis of TF-DNA interactions and their inherent complexity. This article is categorized under: Biological Mechanisms > Regulatory Biology. © 2018 Wiley Periodicals, Inc.

A Sparse Reconstruction Approach for Identifying Gene Regulatory Networks Using Steady-State Experiment Data

PubMed Central

Zhang, Wanhong; Zhou, Tong

2015-01-01

Motivation Identifying gene regulatory networks (GRNs) which consist of a large number of interacting units has become a problem of paramount importance in systems biology. Situations exist extensively in which causal interacting relationships among these units are required to be reconstructed from measured expression data and other a priori information. Though numerous classical methods have been developed to unravel the interactions of GRNs, these methods either have higher computing complexities or have lower estimation accuracies. Note that great similarities exist between identification of genes that directly regulate a specific gene and a sparse vector reconstruction, which often relates to the determination of the number, location and magnitude of nonzero entries of an unknown vector by solving an underdetermined system of linear equations y = Φx. Based on these similarities, we propose a novel framework of sparse reconstruction to identify the structure of a GRN, so as to increase accuracy of causal regulation estimations, as well as to reduce their computational complexity. Results In this paper, a sparse reconstruction framework is proposed on basis of steady-state experiment data to identify GRN structure. Different from traditional methods, this approach is adopted which is well suitable for a large-scale underdetermined problem in inferring a sparse vector. We investigate how to combine the noisy steady-state experiment data and a sparse reconstruction algorithm to identify causal relationships. Efficiency of this method is tested by an artificial linear network, a mitogen-activated protein kinase (MAPK) pathway network and the in silico networks of the DREAM challenges. The performance of the suggested approach is compared with two state-of-the-art algorithms, the widely adopted total least-squares (TLS) method and those available results on the DREAM project. Actual results show that, with a lower computational cost, the proposed method can significantly enhance estimation accuracy and greatly reduce false positive and negative errors. Furthermore, numerical calculations demonstrate that the proposed algorithm may have faster convergence speed and smaller fluctuation than other methods when either estimate error or estimate bias is considered. PMID:26207991

Self-Regulation, Cooperative Learning, and Academic Self-Efficacy: Interactions to Prevent School Failure

PubMed Central

Fernandez-Rio, Javier; Cecchini, Jose A.; Méndez-Gimenez, Antonio; Mendez-Alonso, David; Prieto, Jose A.

2017-01-01

Learning to learn and learning to cooperate are two important goals for individuals. Moreover, self regulation has been identified as fundamental to prevent school failure. The goal of the present study was to assess the interactions between self-regulated learning, cooperative learning and academic self-efficacy in secondary education students experiencing cooperative learning as the main pedagogical approach for at least one school year. 2.513 secondary education students (1.308 males, 1.205 females), 12–17 years old (M = 13.85, SD = 1.29), enrolled in 17 different schools belonging to the National Network of Schools on Cooperative Learning in Spain agreed to participate. They all had experienced this pedagogical approach a minimum of one school year. Participants were asked to complete the cooperative learning questionnaire, the strategies to control the study questionnaire and the global academic self-efficacy questionnaire. Participants were grouped based on their perceptions on cooperative learning and self-regulated learning in their classes. A combination of hierarchical and κ-means cluster analyses was used. Results revealed a four-cluster solution: cluster one included students with low levels of cooperative learning, self-regulated learning and academic self-efficacy, cluster two included students with high levels of cooperative learning, self-regulated learning and academic self-efficacy, cluster three included students with high levels of cooperative learning, low levels of self-regulated learning and intermediate-low levels of academic self-efficacy, and, finally, cluster four included students with high levels of self-regulated learning, low levels of cooperative learning, and intermediate-high levels of academic self-efficacy. Self-regulated learning was found more influential than cooperative learning on students’ academic self-efficacy. In cooperative learning contexts students interact through different types of regulations: self, co, and shared. Educators should be aware of these interactions, symmetrical or asymmetrical, because they determine the quality and quantity of the students’ participation and achievements, and they are key elements to prevent school failure. PMID:28154544

Self-Regulation, Cooperative Learning, and Academic Self-Efficacy: Interactions to Prevent School Failure.

PubMed

Fernandez-Rio, Javier; Cecchini, Jose A; Méndez-Gimenez, Antonio; Mendez-Alonso, David; Prieto, Jose A

2017-01-01

Learning to learn and learning to cooperate are two important goals for individuals. Moreover, self regulation has been identified as fundamental to prevent school failure. The goal of the present study was to assess the interactions between self-regulated learning, cooperative learning and academic self-efficacy in secondary education students experiencing cooperative learning as the main pedagogical approach for at least one school year. 2.513 secondary education students (1.308 males, 1.205 females), 12-17 years old ( M = 13.85, SD = 1.29), enrolled in 17 different schools belonging to the National Network of Schools on Cooperative Learning in Spain agreed to participate. They all had experienced this pedagogical approach a minimum of one school year. Participants were asked to complete the cooperative learning questionnaire, the strategies to control the study questionnaire and the global academic self-efficacy questionnaire. Participants were grouped based on their perceptions on cooperative learning and self-regulated learning in their classes. A combination of hierarchical and κ -means cluster analyses was used. Results revealed a four-cluster solution: cluster one included students with low levels of cooperative learning, self-regulated learning and academic self-efficacy, cluster two included students with high levels of cooperative learning, self-regulated learning and academic self-efficacy, cluster three included students with high levels of cooperative learning, low levels of self-regulated learning and intermediate-low levels of academic self-efficacy, and, finally, cluster four included students with high levels of self-regulated learning, low levels of cooperative learning, and intermediate-high levels of academic self-efficacy. Self-regulated learning was found more influential than cooperative learning on students' academic self-efficacy. In cooperative learning contexts students interact through different types of regulations: self, co, and shared. Educators should be aware of these interactions, symmetrical or asymmetrical, because they determine the quality and quantity of the students' participation and achievements, and they are key elements to prevent school failure.

Role of miR-452-5p in the tumorigenesis of prostate cancer: A study based on the Cancer Genome Atl(TCGA), Gene Expression Omnibus (GEO), and bioinformatics analysis.

PubMed

Gao, Li; Zhang, Li-Jie; Li, Sheng-Hua; Wei, Li-Li; Luo, Bin; He, Rong-Quan; Xia, Shuang

2018-03-06

MiR-452-5p has been reported to be down-regulated in prostate cancer, affecting the development of this type of cancer. However, the molecular mechanism of miR-452-5p in prostate cancer remains unclear. Therefore, we investigated the network of target genes of miR-452-5p in prostate cancer using bioinformatics analyses. We first analyzed the expression profiles and prognostic value of miR-452-5p in prostate cancer tissues from a public database. Gene Ontology (GO), the Kyoto Encyclopedia of Genes and Genomes (KEGG), PANTHER pathway analyses, and a disease ontology (DG) analysis were performed to find the molecular functions of the target genes from GSE datasets and miRWalk. Finally, we validated hub genes from the protein-protein interaction (PPI) networks of the target genes in the Human Protein Atlas (HPA) database and Gene Expression Profiling Interactive Analysis (GEPIA). Narrowing down the optimal target genes was conducted by seeking the common parts of up-regulated genes from GEPIA, down-regulated genes from GSE datasets, and predicted genes in miRWalk. Based on mining of GEO and ArrayExpress microarray chips and miRNA-Seq data in the TCGA database, which includes 1007 prostate cancer samples and 387 non-cancer samples, miR-452-5p is shown to be down-regulated in prostate cancer. GO, KEGG, and PANTHER pathway analyses suggested that the target genes might participate in important biological processes, such as transforming growth factor beta signaling and the positive regulation of brown fat cell differentiation and mesenchymal cell differentiation, as well as the Ras signaling pathway and pathways regulating the pluripotency of stem cells and arrhythmogenic right ventricular cardiomyopathy (ARVC). Nine genes-GABBR, PNISR, NTSR1, DOCK1, EREG, SFRP1, PTGS2, LEF1, and BMP2-were defined as hub genes in the PPI network. Three genes-FAM174B, SLC30A4, and SLIT1-were jointly shared by GEPIA, the GSE datasets, and miRWalk. Down-regulated miR-452-5p might play an essential role in the tumorigenesis of prostate cancer. Copyright © 2018. Published by Elsevier GmbH.

Exploring pathway interactions in insulin resistant mouse liver

PubMed Central

2011-01-01

Background Complex phenotypes such as insulin resistance involve different biological pathways that may interact and influence each other. Interpretation of related experimental data would be facilitated by identifying relevant pathway interactions in the context of the dataset. Results We developed an analysis approach to study interactions between pathways by integrating gene and protein interaction networks, biological pathway information and high-throughput data. This approach was applied to a transcriptomics dataset to investigate pathway interactions in insulin resistant mouse liver in response to a glucose challenge. We identified regulated pathway interactions at different time points following the glucose challenge and also studied the underlying protein interactions to find possible mechanisms and key proteins involved in pathway cross-talk. A large number of pathway interactions were found for the comparison between the two diet groups at t = 0. The initial response to the glucose challenge (t = 0.6) was typed by an acute stress response and pathway interactions showed large overlap between the two diet groups, while the pathway interaction networks for the late response were more dissimilar. Conclusions Studying pathway interactions provides a new perspective on the data that complements established pathway analysis methods such as enrichment analysis. This study provided new insights in how interactions between pathways may be affected by insulin resistance. In addition, the analysis approach described here can be generally applied to different types of high-throughput data and will therefore be useful for analysis of other complex datasets as well. PMID:21843341

Coarse-Grain Bandwidth Estimation Scheme for Large-Scale Network

NASA Technical Reports Server (NTRS)

Cheung, Kar-Ming; Jennings, Esther H.; Sergui, John S.

2013-01-01

A large-scale network that supports a large number of users can have an aggregate data rate of hundreds of Mbps at any time. High-fidelity simulation of a large-scale network might be too complicated and memory-intensive for typical commercial-off-the-shelf (COTS) tools. Unlike a large commercial wide-area-network (WAN) that shares diverse network resources among diverse users and has a complex topology that requires routing mechanism and flow control, the ground communication links of a space network operate under the assumption of a guaranteed dedicated bandwidth allocation between specific sparse endpoints in a star-like topology. This work solved the network design problem of estimating the bandwidths of a ground network architecture option that offer different service classes to meet the latency requirements of different user data types. In this work, a top-down analysis and simulation approach was created to size the bandwidths of a store-and-forward network for a given network topology, a mission traffic scenario, and a set of data types with different latency requirements. These techniques were used to estimate the WAN bandwidths of the ground links for different architecture options of the proposed Integrated Space Communication and Navigation (SCaN) Network. A new analytical approach, called the "leveling scheme," was developed to model the store-and-forward mechanism of the network data flow. The term "leveling" refers to the spreading of data across a longer time horizon without violating the corresponding latency requirement of the data type. Two versions of the leveling scheme were developed: 1. A straightforward version that simply spreads the data of each data type across the time horizon and doesn't take into account the interactions among data types within a pass, or between data types across overlapping passes at a network node, and is inherently sub-optimal. 2. Two-state Markov leveling scheme that takes into account the second order behavior of the store-and-forward mechanism, and the interactions among data types within a pass. The novelty of this approach lies in the modeling of the store-and-forward mechanism of each network node. The term store-and-forward refers to the data traffic regulation technique in which data is sent to an intermediate network node where they are temporarily stored and sent at a later time to the destination node or to another intermediate node. Store-and-forward can be applied to both space-based networks that have intermittent connectivity, and ground-based networks with deterministic connectivity. For groundbased networks, the store-and-forward mechanism is used to regulate the network data flow and link resource utilization such that the user data types can be delivered to their destination nodes without violating their respective latency requirements.

Genome-nuclear lamina interactions and gene regulation.

PubMed

Kind, Jop; van Steensel, Bas

2010-06-01

The nuclear lamina, a filamentous protein network that coats the inner nuclear membrane, has long been thought to interact with specific genomic loci and regulate their expression. Molecular mapping studies have now identified large genomic domains that are in contact with the lamina. Genes in these domains are typically repressed, and artificial tethering experiments indicate that the lamina can actively contribute to this repression. Furthermore, the lamina indirectly controls gene expression in the nuclear interior by sequestration of certain transcription factors. A variety of DNA-binding and chromatin proteins may anchor specific loci to the lamina, while histone-modifying enzymes partly mediate the local repressive effect of the lamina. Experimental tools are now available to begin to unravel the underlying molecular mechanisms. Copyright 2010 Elsevier Ltd. All rights reserved.

Chromatin and Epigenetics at the Forefront: Finding Clues among Peaks

PubMed Central

Shi, Yang

2016-01-01

The Keystone Symposium on Chromatin and Epigenetics, organized by Luciano Di Croce (Center for Genomic Regulation, Spain) and Yang Shi (Harvard Medical School, USA), took place 20 to 24 March 2016 at Whistler (British Columbia, Canada). The symposium brought together some of the most outstanding scientists studying how chromatin structure and epigenetic mechanisms regulate gene function in both development and disease. Junior scientists had the opportunity to interact with experienced researchers by presenting their work and discussing ideas and novel hypotheses. In order to foster interaction and networking, the scientific agenda was balanced with an extended social agenda. This meeting review describes several of the most provocative and exciting talks from the symposium, revealing how fast this research field is evolving and the profound impact it will have on human health. PMID:27402863

GW182 controls Drosophila circadian behavior and PDF-Receptor signaling

PubMed Central

Zhang, Yong; Emery, Patrick

2013-01-01

The neuropeptide PDF is crucial for Drosophila circadian behavior: it keeps circadian neurons synchronized. Here, we identify GW182 as a key regulator of PDF signaling. Indeed, GW182 downregulation results in phenotypes similar to those of Pdf and Pdf-receptor (Pdfr) mutants. gw182 genetically interacts with Pdfr and cAMP signaling, which is essential for PDFR function. GW182 mediates miRNA-dependent gene silencing through its interaction with AGO1. Consistently, GW182's AGO1 interaction domain is required for GW182's circadian function. Moreover, our results indicate that GW182 modulates PDFR signaling by silencing the expression of the cAMP phosphodiesterase DUNCE. Importantly, this repression is under photic control, and GW182 activity level - which is limiting in circadian neurons - influences the responses of the circadian neural network to light. We propose that GW182's gene silencing activity functions as a rheostat for PDFR signaling, and thus profoundly impacts the circadian neural network and its response to environmental inputs. PMID:23583112

Interactions between inflammatory signals and the progesterone receptor in regulating gene expression in pregnant human uterine myocytes

PubMed Central

Lee, Yun; Sooranna, Suren R; Terzidou, Vasso; Christian, Mark; Brosens, Jan; Huhtinen, Kaisa; Poutanen, Matti; Barton, Geraint; Johnson, Mark R; Bennett, Phillip R

2012-01-01

The absence of a fall in circulating progesterone levels has led to the concept that human labour is associated with ‘functional progesterone withdrawal’ caused through changes in the expression or function of progesterone receptor (PR). At the time of labour, the human uterus is heavily infiltrated with inflammatory cells, which release cytokines to create a ‘myometrial inflammation’ via NF-κB activation. The negative interaction between NF-κB and PR, may represent a mechanism to account for ‘functional progesterone withdrawal’ at term. Conversely, PR may act to inhibit NF-κB function and so play a role in inhibition of myometrial inflammation during pregnancy. To model this inter-relationship, we have used small interfering (si) RNA-mediated knock-down of PR in human pregnant myocytes and whole genome microarray analysis to identify genes regulated through PR. We then activated myometrial inflammation using IL-1β stimulation to determine the role of PR in myometrial inflammation regulation. Through PR-knock-down, we found that PR regulates gene networks involved in myometrial quiescence and extracellular matrix integrity. Activation of myometrial inflammation was found to antagonize PR-induced gene expression, of genes normally upregulated via PR. We found that PR does not play a role in repression of pro-inflammatory gene networks induced by IL-1β and that only MMP10 was significantly regulated in opposite directions by IL-1β and PR. We conclude that progesterone acting through PR does not generally inhibit myometrial inflammation. Activation of myometrial inflammation does cause ‘functional progesterone withdrawal’ but only in the context of genes normally upregulated via PR. PMID:22435466

Walking the interactome to identify human miRNA-disease associations through the functional link between miRNA targets and disease genes

PubMed Central

2013-01-01

Background MicroRNAs (miRNAs) are important post-transcriptional regulators that have been demonstrated to play an important role in human diseases. Elucidating the associations between miRNAs and diseases at the systematic level will deepen our understanding of the molecular mechanisms of diseases. However, miRNA-disease associations identified by previous computational methods are far from completeness and more effort is needed. Results We developed a computational framework to identify miRNA-disease associations by performing random walk analysis, and focused on the functional link between miRNA targets and disease genes in protein-protein interaction (PPI) networks. Furthermore, a bipartite miRNA-disease network was constructed, from which several miRNA-disease co-regulated modules were identified by hierarchical clustering analysis. Our approach achieved satisfactory performance in identifying known cancer-related miRNAs for nine human cancers with an area under the ROC curve (AUC) ranging from 71.3% to 91.3%. By systematically analyzing the global properties of the miRNA-disease network, we found that only a small number of miRNAs regulated genes involved in various diseases, genes associated with neurological diseases were preferentially regulated by miRNAs and some immunological diseases were associated with several specific miRNAs. We also observed that most diseases in the same co-regulated module tended to belong to the same disease category, indicating that these diseases might share similar miRNA regulatory mechanisms. Conclusions In this study, we present a computational framework to identify miRNA-disease associations, and further construct a bipartite miRNA-disease network for systematically analyzing the global properties of miRNA regulation of disease genes. Our findings provide a broad perspective on the relationships between miRNAs and diseases and could potentially aid future research efforts concerning miRNA involvement in disease pathogenesis. PMID:24103777

Discovery of time-delayed gene regulatory networks based on temporal gene expression profiling

PubMed Central

Li, Xia; Rao, Shaoqi; Jiang, Wei; Li, Chuanxing; Xiao, Yun; Guo, Zheng; Zhang, Qingpu; Wang, Lihong; Du, Lei; Li, Jing; Li, Li; Zhang, Tianwen; Wang, Qing K

2006-01-01

Background It is one of the ultimate goals for modern biological research to fully elucidate the intricate interplays and the regulations of the molecular determinants that propel and characterize the progression of versatile life phenomena, to name a few, cell cycling, developmental biology, aging, and the progressive and recurrent pathogenesis of complex diseases. The vast amount of large-scale and genome-wide time-resolved data is becoming increasing available, which provides the golden opportunity to unravel the challenging reverse-engineering problem of time-delayed gene regulatory networks. Results In particular, this methodological paper aims to reconstruct regulatory networks from temporal gene expression data by using delayed correlations between genes, i.e., pairwise overlaps of expression levels shifted in time relative each other. We have thus developed a novel model-free computational toolbox termed TdGRN (Time-delayed Gene Regulatory Network) to address the underlying regulations of genes that can span any unit(s) of time intervals. This bioinformatics toolbox has provided a unified approach to uncovering time trends of gene regulations through decision analysis of the newly designed time-delayed gene expression matrix. We have applied the proposed method to yeast cell cycling and human HeLa cell cycling and have discovered most of the underlying time-delayed regulations that are supported by multiple lines of experimental evidence and that are remarkably consistent with the current knowledge on phase characteristics for the cell cyclings. Conclusion We established a usable and powerful model-free approach to dissecting high-order dynamic trends of gene-gene interactions. We have carefully validated the proposed algorithm by applying it to two publicly available cell cycling datasets. In addition to uncovering the time trends of gene regulations for cell cycling, this unified approach can also be used to study the complex gene regulations related to the development, aging and progressive pathogenesis of a complex disease where potential dependences between different experiment units might occurs. PMID:16420705

The Interaction Network Ontology-supported modeling and mining of complex interactions represented with multiple keywords in biomedical literature.

PubMed

Özgür, Arzucan; Hur, Junguk; He, Yongqun

2016-01-01

The Interaction Network Ontology (INO) logically represents biological interactions, pathways, and networks. INO has been demonstrated to be valuable in providing a set of structured ontological terms and associated keywords to support literature mining of gene-gene interactions from biomedical literature. However, previous work using INO focused on single keyword matching, while many interactions are represented with two or more interaction keywords used in combination. This paper reports our extension of INO to include combinatory patterns of two or more literature mining keywords co-existing in one sentence to represent specific INO interaction classes. Such keyword combinations and related INO interaction type information could be automatically obtained via SPARQL queries, formatted in Excel format, and used in an INO-supported SciMiner, an in-house literature mining program. We studied the gene interaction sentences from the commonly used benchmark Learning Logic in Language (LLL) dataset and one internally generated vaccine-related dataset to identify and analyze interaction types containing multiple keywords. Patterns obtained from the dependency parse trees of the sentences were used to identify the interaction keywords that are related to each other and collectively represent an interaction type. The INO ontology currently has 575 terms including 202 terms under the interaction branch. The relations between the INO interaction types and associated keywords are represented using the INO annotation relations: 'has literature mining keywords' and 'has keyword dependency pattern'. The keyword dependency patterns were generated via running the Stanford Parser to obtain dependency relation types. Out of the 107 interactions in the LLL dataset represented with two-keyword interaction types, 86 were identified by using the direct dependency relations. The LLL dataset contained 34 gene regulation interaction types, each of which associated with multiple keywords. A hierarchical display of these 34 interaction types and their ancestor terms in INO resulted in the identification of specific gene-gene interaction patterns from the LLL dataset. The phenomenon of having multi-keyword interaction types was also frequently observed in the vaccine dataset. By modeling and representing multiple textual keywords for interaction types, the extended INO enabled the identification of complex biological gene-gene interactions represented with multiple keywords.

An integrated approach to characterize transcription factor and microRNA regulatory networks involved in Schwann cell response to peripheral nerve injury

PubMed Central

2013-01-01

Background The regenerative response of Schwann cells after peripheral nerve injury is a critical process directly related to the pathophysiology of a number of neurodegenerative diseases. This SC injury response is dependent on an intricate gene regulatory program coordinated by a number of transcription factors and microRNAs, but the interactions among them remain largely unknown. Uncovering the transcriptional and post-transcriptional regulatory networks governing the Schwann cell injury response is a key step towards a better understanding of Schwann cell biology and may help develop novel therapies for related diseases. Performing such comprehensive network analysis requires systematic bioinformatics methods to integrate multiple genomic datasets. Results In this study we present a computational pipeline to infer transcription factor and microRNA regulatory networks. Our approach combined mRNA and microRNA expression profiling data, ChIP-Seq data of transcription factors, and computational transcription factor and microRNA target prediction. Using mRNA and microRNA expression data collected in a Schwann cell injury model, we constructed a regulatory network and studied regulatory pathways involved in Schwann cell response to injury. Furthermore, we analyzed network motifs and obtained insights on cooperative regulation of transcription factors and microRNAs in Schwann cell injury recovery. Conclusions This work demonstrates a systematic method for gene regulatory network inference that may be used to gain new information on gene regulation by transcription factors and microRNAs. PMID:23387820

MapReduce Algorithms for Inferring Gene Regulatory Networks from Time-Series Microarray Data Using an Information-Theoretic Approach.

PubMed

Abduallah, Yasser; Turki, Turki; Byron, Kevin; Du, Zongxuan; Cervantes-Cervantes, Miguel; Wang, Jason T L

2017-01-01

Gene regulation is a series of processes that control gene expression and its extent. The connections among genes and their regulatory molecules, usually transcription factors, and a descriptive model of such connections are known as gene regulatory networks (GRNs). Elucidating GRNs is crucial to understand the inner workings of the cell and the complexity of gene interactions. To date, numerous algorithms have been developed to infer gene regulatory networks. However, as the number of identified genes increases and the complexity of their interactions is uncovered, networks and their regulatory mechanisms become cumbersome to test. Furthermore, prodding through experimental results requires an enormous amount of computation, resulting in slow data processing. Therefore, new approaches are needed to expeditiously analyze copious amounts of experimental data resulting from cellular GRNs. To meet this need, cloud computing is promising as reported in the literature. Here, we propose new MapReduce algorithms for inferring gene regulatory networks on a Hadoop cluster in a cloud environment. These algorithms employ an information-theoretic approach to infer GRNs using time-series microarray data. Experimental results show that our MapReduce program is much faster than an existing tool while achieving slightly better prediction accuracy than the existing tool.

Collective learning for the emergence of social norms in networked multiagent systems.

PubMed

Yu, Chao; Zhang, Minjie; Ren, Fenghui

2014-12-01

Social norms such as social rules and conventions play a pivotal role in sustaining system order by regulating and controlling individual behaviors toward a global consensus in large-scale distributed systems. Systematic studies of efficient mechanisms that can facilitate the emergence of social norms enable us to build and design robust distributed systems, such as electronic institutions and norm-governed sensor networks. This paper studies the emergence of social norms via learning from repeated local interactions in networked multiagent systems. A collective learning framework, which imitates the opinion aggregation process in human decision making, is proposed to study the impact of agent local collective behaviors on the emergence of social norms in a number of different situations. In the framework, each agent interacts repeatedly with all of its neighbors. At each step, an agent first takes a best-response action toward each of its neighbors and then combines all of these actions into a final action using ensemble learning methods. Extensive experiments are carried out to evaluate the framework with respect to different network topologies, learning strategies, numbers of actions, influences of nonlearning agents, and so on. Experimental results reveal some significant insights into the manipulation and control of norm emergence in networked multiagent systems achieved through local collective behaviors.

TPPII, MYBBP1A and CDK2 form a protein-protein interaction network.

PubMed

Nahálková, Jarmila; Tomkinson, Birgitta

2014-12-15

Tripeptidyl-peptidase II (TPPII) is an aminopeptidase with suggested regulatory effects on cell cycle, apoptosis and senescence. A protein-protein interaction study revealed that TPPII physically interacts with the tumor suppressor MYBBP1A and the cell cycle regulator protein CDK2. Mutual protein-protein interaction was detected between MYBBP1A and CDK2 as well. In situ Proximity Ligation Assay (PLA) using HEK293 cells overexpressing TPPII forming highly enzymatically active oligomeric complexes showed that the cytoplasmic interaction frequency of TPPII with MYBBP1A increased with the protein expression of TPPII and using serum-free cell growth conditions. A specific reversible inhibitor of TPPII, butabindide, suppressed the cytoplasmic interactions of TPPII and MYBBP1A both in control HEK293 and the cells overexpressing murine TPPII. The interaction of MYBBP1A with CDK2 was confirmed by in situ PLA in two different mammalian cell lines. Functional link between TPPII and MYBBP1A has been verified by gene expression study during anoikis, where overexpression of TPP II decreased mRNA expression level of MYBBP1A at the cell detachment conditions. All three interacting proteins TPPII, MYBBP1A and CDK2 have been previously implicated in the research for development of tumor-suppressing agents. This is the first report presenting mutual protein-protein interaction network of these proteins. Copyright © 2014 Elsevier Inc. All rights reserved.

System-wide Analysis of SUMOylation Dynamics in Response to Replication Stress Reveals Novel Small Ubiquitin-like Modified Target Proteins and Acceptor Lysines Relevant for Genome Stability*

PubMed Central

Xiao, Zhenyu; Chang, Jer-Gung; Hendriks, Ivo A.; Sigurðsson, Jón Otti; Olsen, Jesper V.; Vertegaal, Alfred C.O.

2015-01-01

Genotoxic agents can cause replication fork stalling in dividing cells because of DNA lesions, eventually leading to replication fork collapse when the damage is not repaired. Small Ubiquitin-like Modifiers (SUMOs) are known to counteract replication stress, nevertheless, only a small number of relevant SUMO target proteins are known. To address this, we have purified and identified SUMO-2 target proteins regulated by replication stress in human cells. The developed methodology enabled single step purification of His10-SUMO-2 conjugates under denaturing conditions with high yield and high purity. Following statistical analysis on five biological replicates, a total of 566 SUMO-2 targets were identified. After 2 h of hydroxyurea treatment, 10 proteins were up-regulated for SUMOylation and two proteins were down-regulated for SUMOylation, whereas after 24 h, 35 proteins were up-regulated for SUMOylation, and 13 proteins were down-regulated for SUMOylation. A site-specific approach was used to map over 1000 SUMO-2 acceptor lysines in target proteins. The methodology is generic and is widely applicable in the ubiquitin field. A large subset of these identified proteins function in one network that consists of interacting replication factors, transcriptional regulators, DNA damage response factors including MDC1, ATR-interacting protein ATRIP, the Bloom syndrome protein and the BLM-binding partner RMI1, the crossover junction endonuclease EME1, BRCA1, and CHAF1A. Furthermore, centromeric proteins and signal transducers were dynamically regulated by SUMOylation upon replication stress. Our results uncover a comprehensive network of SUMO target proteins dealing with replication damage and provide a framework for detailed understanding of the role of SUMOylation to counteract replication stress. Ultimately, our study reveals how a post-translational modification is able to orchestrate a large variety of different proteins to integrate different nuclear processes with the aim of dealing with the induced DNA damage. PMID:25755297

Genotet: An Interactive Web-based Visual Exploration Framework to Support Validation of Gene Regulatory Networks.

PubMed

Yu, Bowen; Doraiswamy, Harish; Chen, Xi; Miraldi, Emily; Arrieta-Ortiz, Mario Luis; Hafemeister, Christoph; Madar, Aviv; Bonneau, Richard; Silva, Cláudio T

2014-12-01

Elucidation of transcriptional regulatory networks (TRNs) is a fundamental goal in biology, and one of the most important components of TRNs are transcription factors (TFs), proteins that specifically bind to gene promoter and enhancer regions to alter target gene expression patterns. Advances in genomic technologies as well as advances in computational biology have led to multiple large regulatory network models (directed networks) each with a large corpus of supporting data and gene-annotation. There are multiple possible biological motivations for exploring large regulatory network models, including: validating TF-target gene relationships, figuring out co-regulation patterns, and exploring the coordination of cell processes in response to changes in cell state or environment. Here we focus on queries aimed at validating regulatory network models, and on coordinating visualization of primary data and directed weighted gene regulatory networks. The large size of both the network models and the primary data can make such coordinated queries cumbersome with existing tools and, in particular, inhibits the sharing of results between collaborators. In this work, we develop and demonstrate a web-based framework for coordinating visualization and exploration of expression data (RNA-seq, microarray), network models and gene-binding data (ChIP-seq). Using specialized data structures and multiple coordinated views, we design an efficient querying model to support interactive analysis of the data. Finally, we show the effectiveness of our framework through case studies for the mouse immune system (a dataset focused on a subset of key cellular functions) and a model bacteria (a small genome with high data-completeness).

The Activity of Thalamic Nucleus Reuniens Is Critical for Memory Retrieval, but Not Essential for the Early Phase of "Off-Line" Consolidation

ERIC Educational Resources Information Center

Mei, Hao; Logothetis, Nikos K.; Eschenko, Oxana

2018-01-01

Spatial navigation depends on the hippocampal function, but also requires bidirectional interactions between the hippocampus (HPC) and the prefrontal cortex (PFC). The cross-regional communication is typically regulated by critical nodes of a distributed brain network. The thalamic nucleus reuniens (RE) is reciprocally connected to both HPC and…

Connections and Perceptions: Policy Recommendations to Guide Social Media Interactions for Public Educators

ERIC Educational Resources Information Center

Smith, Stephanie L.

2012-01-01

Social Media networking is the next frontier in educational policy. A plethora of issues has arisen in regard to social media practices on the part of educators in public school systems. There is a lack of regulation for use of social media across the nation, resulting in court challenges brought by individual teachers, teachers' unions,…

The coordinating role of IQGAP1 in the regulation of local, endosome-specific actin networks

PubMed Central

Samson, Edward B.; Tsao, David S.; Zimak, Jan; McLaughlin, R. Tyler; Trenton, Nicholaus J.; Mace, Emily M.; Orange, Jordan S.; Schweikhard, Volker

2017-01-01

ABSTRACT IQGAP1 is a large, multi-domain scaffold that helps orchestrate cell signaling and cytoskeletal mechanics by controlling interactions among a spectrum of receptors, signaling intermediates, and cytoskeletal proteins. While this coordination is known to impact cell morphology, motility, cell adhesion, and vesicular traffic, among other functions, the spatiotemporal properties and regulatory mechanisms of IQGAP1 have not been fully resolved. Herein, we describe a series of super-resolution and live-cell imaging analyses that identified a role for IQGAP1 in the regulation of an actin cytoskeletal shell surrounding a novel membranous compartment that localizes selectively to the basal cortex of polarized epithelial cells (MCF-10A). We also show that IQGAP1 appears to both stabilize the actin coating and constrain its growth. Loss of compartmental IQGAP1 initiates a disassembly mechanism involving rapid and unconstrained actin polymerization around the compartment and dispersal of its vesicle contents. Together, these findings suggest IQGAP1 achieves this control by harnessing both stabilizing and antagonistic interactions with actin. They also demonstrate the utility of these compartments for image-based investigations of the spatial and temporal dynamics of IQGAP1 within endosome-specific actin networks. PMID:28455356

Analysis of a Plant Transcriptional Regulatory Network Using Transient Expression Systems.

PubMed

Díaz-Triviño, Sara; Long, Yuchen; Scheres, Ben; Blilou, Ikram

2017-01-01

In plant biology, transient expression systems have become valuable approaches used routinely to rapidly study protein expression, subcellular localization, protein-protein interactions, and transcriptional activity prior to in vivo studies. When studying transcriptional regulation, luciferase reporter assays offer a sensitive readout for assaying promoter behavior in response to different regulators or environmental contexts and to confirm and assess the functional relevance of predicted binding sites in target promoters. This chapter aims to provide detailed methods for using luciferase reporter system as a rapid, efficient, and versatile assay to analyze transcriptional regulation of target genes by transcriptional regulators. We describe a series of optimized transient expression systems consisting of Arabidopsis thaliana protoplasts, infiltrated Nicotiana benthamiana leaves, and human HeLa cells to study the transcriptional regulations of two well-characterized transcriptional regulators SCARECROW (SCR) and SHORT-ROOT (SHR) on one of their targets, CYCLIN D6 (CYCD6).Here, we illustrate similarities and differences in outcomes when using different systems. The plant-based systems revealed that the SCR-SHR complex enhances CYCD6 transcription, while analysis in HeLa cells showed that the complex is not sufficient to strongly induce CYCD6 transcription, suggesting that additional, plant-specific regulators are required for full activation. These results highlight the importance of the system and suggest that including heterologous systems, such as HeLa cells, can provide a more comprehensive analysis of a complex gene regulatory network.

The Proteomic Profile of Deleted in Breast Cancer 1 (DBC1) Interactions Points to a Multifaceted Regulation of Gene Expression*

PubMed Central

Giguère, Sophie S. B.; Guise, Amanda J.; Jean Beltran, Pierre M.; Joshi, Preeti M.; Greco, Todd M.; Quach, Olivia L.; Kong, Jeffery; Cristea, Ileana M.

2016-01-01

Deleted in breast cancer 1 (DBC1) has emerged as an important regulator of multiple cellular processes, ranging from gene expression to cell cycle progression. DBC1 has been linked to tumorigenesis both as an inhibitor of histone deacetylases, HDAC3 and sirtuin 1, and as a transcriptional cofactor for nuclear hormone receptors. However, despite mounting interest in DBC1, relatively little is known about the range of its interacting partners and the scope of its functions. Here, we carried out a functional proteomics-based investigation of DBC1 interactions in two relevant cell types, T cells and kidney cells. Microscopy, molecular biology, biochemistry, and mass spectrometry studies allowed us to assess DBC1 mRNA and protein levels, localization, phosphorylation status, and protein interaction networks. The comparison of DBC1 interactions in these cell types revealed conserved regulatory roles for DBC1 in gene expression, chromatin organization and modification, and cell cycle progression. Interestingly, we observe previously unrecognized DBC1 interactions with proteins encoded by cancer-associated genes. Among these interactions are five components of the SWI/SNF complex, the most frequently mutated chromatin remodeling complex in human cancers. Additionally, we identified a DBC1 interaction with TBL1XR1, a component of the NCoR complex, which we validated by reciprocal isolation. Strikingly, we discovered that DBC1 associates with proteins that regulate the circadian cycle, including DDX5, DHX9, and SFPQ. We validated this interaction by colocalization and reciprocal isolation. Functional assessment of this association demonstrated that DBC1 protein levels are important for regulating CLOCK and BMAL1 protein oscillations in synchronized T cells. Our results suggest that DBC1 is integral to the maintenance of the circadian molecular clock. Furthermore, the identified interactions provide a valuable resource for the exploration of pathways involved in DBC1-associated tumorigenesis. PMID:26657080

The transcriptional network that controls growth arrest and differentiation in a human myeloid leukemia cell line.

PubMed

Suzuki, Harukazu; Forrest, Alistair R R; van Nimwegen, Erik; Daub, Carsten O; Balwierz, Piotr J; Irvine, Katharine M; Lassmann, Timo; Ravasi, Timothy; Hasegawa, Yuki; de Hoon, Michiel J L; Katayama, Shintaro; Schroder, Kate; Carninci, Piero; Tomaru, Yasuhiro; Kanamori-Katayama, Mutsumi; Kubosaki, Atsutaka; Akalin, Altuna; Ando, Yoshinari; Arner, Erik; Asada, Maki; Asahara, Hiroshi; Bailey, Timothy; Bajic, Vladimir B; Bauer, Denis; Beckhouse, Anthony G; Bertin, Nicolas; Björkegren, Johan; Brombacher, Frank; Bulger, Erika; Chalk, Alistair M; Chiba, Joe; Cloonan, Nicole; Dawe, Adam; Dostie, Josee; Engström, Pär G; Essack, Magbubah; Faulkner, Geoffrey J; Fink, J Lynn; Fredman, David; Fujimori, Ko; Furuno, Masaaki; Gojobori, Takashi; Gough, Julian; Grimmond, Sean M; Gustafsson, Mika; Hashimoto, Megumi; Hashimoto, Takehiro; Hatakeyama, Mariko; Heinzel, Susanne; Hide, Winston; Hofmann, Oliver; Hörnquist, Michael; Huminiecki, Lukasz; Ikeo, Kazuho; Imamoto, Naoko; Inoue, Satoshi; Inoue, Yusuke; Ishihara, Ryoko; Iwayanagi, Takao; Jacobsen, Anders; Kaur, Mandeep; Kawaji, Hideya; Kerr, Markus C; Kimura, Ryuichiro; Kimura, Syuhei; Kimura, Yasumasa; Kitano, Hiroaki; Koga, Hisashi; Kojima, Toshio; Kondo, Shinji; Konno, Takeshi; Krogh, Anders; Kruger, Adele; Kumar, Ajit; Lenhard, Boris; Lennartsson, Andreas; Lindow, Morten; Lizio, Marina; Macpherson, Cameron; Maeda, Norihiro; Maher, Christopher A; Maqungo, Monique; Mar, Jessica; Matigian, Nicholas A; Matsuda, Hideo; Mattick, John S; Meier, Stuart; Miyamoto, Sei; Miyamoto-Sato, Etsuko; Nakabayashi, Kazuhiko; Nakachi, Yutaka; Nakano, Mika; Nygaard, Sanne; Okayama, Toshitsugu; Okazaki, Yasushi; Okuda-Yabukami, Haruka; Orlando, Valerio; Otomo, Jun; Pachkov, Mikhail; Petrovsky, Nikolai; Plessy, Charles; Quackenbush, John; Radovanovic, Aleksandar; Rehli, Michael; Saito, Rintaro; Sandelin, Albin; Schmeier, Sebastian; Schönbach, Christian; Schwartz, Ariel S; Semple, Colin A; Sera, Miho; Severin, Jessica; Shirahige, Katsuhiko; Simons, Cas; St Laurent, George; Suzuki, Masanori; Suzuki, Takahiro; Sweet, Matthew J; Taft, Ryan J; Takeda, Shizu; Takenaka, Yoichi; Tan, Kai; Taylor, Martin S; Teasdale, Rohan D; Tegnér, Jesper; Teichmann, Sarah; Valen, Eivind; Wahlestedt, Claes; Waki, Kazunori; Waterhouse, Andrew; Wells, Christine A; Winther, Ole; Wu, Linda; Yamaguchi, Kazumi; Yanagawa, Hiroshi; Yasuda, Jun; Zavolan, Mihaela; Hume, David A; Arakawa, Takahiro; Fukuda, Shiro; Imamura, Kengo; Kai, Chikatoshi; Kaiho, Ai; Kawashima, Tsugumi; Kawazu, Chika; Kitazume, Yayoi; Kojima, Miki; Miura, Hisashi; Murakami, Kayoko; Murata, Mitsuyoshi; Ninomiya, Noriko; Nishiyori, Hiromi; Noma, Shohei; Ogawa, Chihiro; Sano, Takuma; Simon, Christophe; Tagami, Michihira; Takahashi, Yukari; Kawai, Jun; Hayashizaki, Yoshihide

2009-05-01

Using deep sequencing (deepCAGE), the FANTOM4 study measured the genome-wide dynamics of transcription-start-site usage in the human monocytic cell line THP-1 throughout a time course of growth arrest and differentiation. Modeling the expression dynamics in terms of predicted cis-regulatory sites, we identified the key transcription regulators, their time-dependent activities and target genes. Systematic siRNA knockdown of 52 transcription factors confirmed the roles of individual factors in the regulatory network. Our results indicate that cellular states are constrained by complex networks involving both positive and negative regulatory interactions among substantial numbers of transcription factors and that no single transcription factor is both necessary and sufficient to drive the differentiation process.

Non-coding RNA networks in cancer.

PubMed

Anastasiadou, Eleni; Jacob, Leni S; Slack, Frank J

2018-01-01

Thousands of unique non-coding RNA (ncRNA) sequences exist within cells. Work from the past decade has altered our perception of ncRNAs from 'junk' transcriptional products to functional regulatory molecules that mediate cellular processes including chromatin remodelling, transcription, post-transcriptional modifications and signal transduction. The networks in which ncRNAs engage can influence numerous molecular targets to drive specific cell biological responses and fates. Consequently, ncRNAs act as key regulators of physiological programmes in developmental and disease contexts. Particularly relevant in cancer, ncRNAs have been identified as oncogenic drivers and tumour suppressors in every major cancer type. Thus, a deeper understanding of the complex networks of interactions that ncRNAs coordinate would provide a unique opportunity to design better therapeutic interventions.

Systematic Genetic Screen for Transcriptional Regulators of the Candida albicans White-Opaque Switch.

PubMed

Lohse, Matthew B; Ene, Iuliana V; Craik, Veronica B; Hernday, Aaron D; Mancera, Eugenio; Morschhäuser, Joachim; Bennett, Richard J; Johnson, Alexander D

2016-08-01

The human fungal pathogen Candida albicans can reversibly switch between two cell types named "white" and "opaque," each of which is stable through many cell divisions. These two cell types differ in their ability to mate, their metabolic preferences and their interactions with the mammalian innate immune system. A highly interconnected network of eight transcriptional regulators has been shown to control switching between these two cell types. To identify additional regulators of the switch, we systematically and quantitatively measured white-opaque switching rates of 196 strains, each deleted for a specific transcriptional regulator. We identified 19 new regulators with at least a 10-fold effect on switching rates and an additional 14 new regulators with more subtle effects. To investigate how these regulators affect switching rates, we examined several criteria, including the binding of the eight known regulators of switching to the control region of each new regulatory gene, differential expression of the newly found genes between cell types, and the growth rate of each mutant strain. This study highlights the complexity of the transcriptional network that regulates the white-opaque switch and the extent to which switching is linked to a variety of metabolic processes, including respiration and carbon utilization. In addition to revealing specific insights, the information reported here provides a foundation to understand the highly complex coupling of white-opaque switching to cellular physiology. Copyright © 2016 by the Genetics Society of America.

Neural network of cognitive emotion regulation — An ALE meta-analysis and MACM analysis

PubMed Central

Kohn, N.; Eickhoff, S.B.; Scheller, M.; Laird, A.R.; Fox, P.T.; Habel, U.

2016-01-01

Cognitive regulation of emotions is a fundamental prerequisite for intact social functioning which impacts on both well being and psychopathology. The neural underpinnings of this process have been studied intensively in recent years, without, however, a general consensus. We here quantitatively summarize the published literature on cognitive emotion regulation using activation likelihood estimation in fMRI and PET (23 studies/479 subjects). In addition, we assessed the particular functional contribution of identified regions and their interactions using quantitative functional inference and meta-analytic connectivity modeling, respectively. In doing so, we developed a model for the core brain network involved in emotion regulation of emotional reactivity. According to this, the superior temporal gyrus, angular gyrus and (pre) supplementary motor area should be involved in execution of regulation initiated by frontal areas. The dorsolateral prefrontal cortex may be related to regulation of cognitive processes such as attention, while the ventrolateral prefrontal cortex may not necessarily reflect the regulatory process per se, but signals salience and therefore the need to regulate. We also identified a cluster in the anterior middle cingulate cortex as a region, which is anatomically and functionally in an ideal position to influence behavior and subcortical structures related to affect generation. Hence this area may play a central, integrative role in emotion regulation. By focusing on regions commonly active across multiple studies, this proposed model should provide important a priori information for the assessment of dysregulated emotion regulation in psychiatric disorders. PMID:24220041

Characterization of biomarkers in stroke based on ego-networks and pathways.

PubMed

Li, Haixia; Guo, Qianqian

2017-12-01

To explore potential biomarkers in stroke based on ego-networks and pathways. EgoNet method was applied to search for the underlying biomarkers in stroke using transcription profiling of E-GEOD-58294 and protein-protein interaction (PPI) data. Eight ego-genes were identified from PPI network according to the degree characteristics at the criteria of top 5% ranked z-sore and degree >1. Eight candidate ego-networks with classification accuracy ≥0.9 were selected. After performed randomization test, seven significant ego-networks with adjusted p value < 0.05 were identified. Pathway enrichment analysis was then conducted with these ego-networks to search for the significant pathways. Finally, two significant pathways were identified, and six of seven ego-networks were enriched to "3'-UTR-mediated translational regulation" pathway, indicating that this pathway performs an important role in the development of stroke. Seven ego-networks were constructed using EgoNet and two significant enriched by pathways were identified. These may provide new insights into the potential biomarkers for the development of stroke.

A Non-Targeted Approach Unravels the Volatile Network in Peach Fruit

PubMed Central

Sánchez, Gerardo; Besada, Cristina; Badenes, María Luisa; Monforte, Antonio José; Granell, Antonio

2012-01-01

Volatile compounds represent an important part of the plant metabolome and are of particular agronomic and biological interest due to their contribution to fruit aroma and flavor and therefore to fruit quality. By using a non-targeted approach based on HS-SPME-GC-MS, the volatile-compound complement of peach fruit was described. A total of 110 volatile compounds (including alcohols, ketones, aldehydes, esters, lactones, carboxylic acids, phenolics and terpenoids) were identified and quantified in peach fruit samples from different genetic backgrounds, locations, maturity stages and physiological responses. By using a combination of hierarchical cluster analysis and metabolomic correlation network analysis we found that previously known peach fruit volatiles are clustered according to their chemical nature or known biosynthetic pathways. Moreover, novel volatiles that had not yet been described in peach were identified and assigned to co-regulated groups. In addition, our analyses showed that most of the co-regulated groups showed good intergroup correlations that are therefore consistent with the existence of a higher level of regulation orchestrating volatile production under different conditions and/or developmental stages. In addition, this volatile network of interactions provides the ground information for future biochemical studies as well as a useful route map for breeding or biotechnological purposes. PMID:22761719

Branching of the PIF3 regulatory network in Arabidopsis: roles of PIF3-regulated MIDAs in seedling development in the dark and in response to light.

PubMed

Sentandreu, Maria; Leivar, Pablo; Martín, Guiomar; Monte, Elena

2012-04-01

Plants need to accurately adjust their development after germination in the underground darkness to ensure survival of the seedling, both in the dark and in the light upon reaching the soil surface. Recent studies have established that the photoreceptors phytochromes and the bHLH phytochrome interacting factors PIFs regulate seedling development to adjust it to the prevailing light environment during post-germinative growth. However, complete understanding of the downstream regulatory network implementing these developmental responses is still lacking. In a recent work, published in The Plant Cell, we report a subset of PIF3-regulated genes in dark-grown seedlings that we have named MIDAs (MISREGULATED IN DARK). Analysis of their functional relevance using mutants showed that four of them present phenotypic alterations in the dark, and that each affected a particular facet of seedling development, suggesting organ-specific branching in the signal that PIF3 relays downstream. Furthermore, our results also showed an altered response to light in seedlings with an impaired PIF3/MIDA regulatory network, indicating that these factors might also be essential to initiate and optimize the developmental adjustment of the seedling to the light environment.

LSU network hubs integrate abiotic and biotic stress responses via interaction with the superoxide dismutase FSD2.

PubMed

Garcia-Molina, Antoni; Altmann, Melina; Alkofer, Angela; Epple, Petra M; Dangl, Jeffery L; Falter-Braun, Pascal

2017-02-01

In natural environments, plants often experience different stresses simultaneously, and adverse abiotic conditions can weaken the plant immune system. Interactome mapping revealed that the LOW SULPHUR UPREGULATED (LSU) proteins are hubs in an Arabidopsis protein interaction network that are targeted by virulence effectors from evolutionarily diverse pathogens. Here we show that LSU proteins are up-regulated in several abiotic and biotic stress conditions, such as nutrient depletion or salt stress, by both transcriptional and post-translational mechanisms. Interference with LSU expression prevents chloroplastic reactive oxygen species (ROS) production and proper stomatal closure during sulphur stress. We demonstrate that LSU1 interacts with the chloroplastic superoxide dismutase FSD2 and stimulates its enzymatic activity in vivo and in vitro. Pseudomonas syringae virulence effectors interfere with this interaction and preclude re-localization of LSU1 to chloroplasts. We demonstrate that reduced LSU levels cause a moderately enhanced disease susceptibility in plants exposed to abiotic stresses such as nutrient deficiency, high salinity, or heavy metal toxicity, whereas LSU1 overexpression confers significant disease resistance in several of these conditions. Our data suggest that the network hub LSU1 plays an important role in co-ordinating plant immune responses across a spectrum of abiotic stress conditions. © The Author 2017. Published by Oxford University Press on behalf of the Society for Experimental Biology.

Receptors rather than signals change in expression in four physiological regulatory networks during evolutionary divergence in threespine stickleback.

PubMed

Di Poi, Carole; Bélanger, Dominic; Amyot, Marc; Rogers, Sean; Aubin-Horth, Nadia

2016-07-01

The molecular mechanisms underlying behavioural evolution following colonization of novel environments are largely unknown. Molecules that interact to control equilibrium within an organism form physiological regulatory networks. It is essential to determine whether particular components of physiological regulatory networks evolve or if the network as a whole is affected in populations diverging in behavioural responses, as this may affect the nature, amplitude and number of impacted traits. We studied the regulation of four physiological regulatory networks in freshwater and marine populations of threespine stickleback raised in a common environment, which were previously characterized as showing evolutionary divergence in behaviour and stress reactivity. We measured nineteen components of these networks (ligands and receptors) using mRNA and monoamine levels in the brain, pituitary and interrenal gland, as well as hormone levels. Freshwater fish showed higher expression in the brain of adrenergic (adrb2a), serotonergic (htr2a) and dopaminergic (DRD2) receptors, but lower expression of the htr2b receptor. Freshwater fish also showed higher expression of the mc2r receptor of the glucocorticoid axis in the interrenals. Collectively, our results suggest that the inheritance of the regulation of these networks may be implicated in the evolution of behaviour and stress reactivity in association with population divergence. Our results also suggest that evolutionary change in freshwater threespine stickleback may be more associated with the expression of specific receptors rather than with global changes of all the measured constituents of the physiological regulatory networks. © 2016 John Wiley & Sons Ltd.

Coding and non-coding gene regulatory networks underlie the immune response in liver cirrhosis

PubMed Central

Zhang, Xueming; Huang, Yongming; Yang, Zhengpeng; Zhang, Yuguo; Zhang, Weihui; Gao, Zu-hua; Xue, Dongbo

2017-01-01

Liver cirrhosis is recognized as being the consequence of immune-mediated hepatocyte damage and repair processes. However, the regulation of these immune responses underlying liver cirrhosis has not been elucidated. In this study, we used GEO datasets and bioinformatics methods to established coding and non-coding gene regulatory networks including transcription factor-/lncRNA-microRNA-mRNA, and competing endogenous RNA interaction networks. Our results identified 2224 mRNAs, 70 lncRNAs and 46 microRNAs were differentially expressed in liver cirrhosis. The transcription factor -/lncRNA- microRNA-mRNA network we uncovered that results in immune-mediated liver cirrhosis is comprised of 5 core microRNAs (e.g., miR-203; miR-219-5p), 3 transcription factors (i.e., FOXP3, ETS1 and FOS) and 7 lncRNAs (e.g., ENTS00000671336, ENST00000575137). The competing endogenous RNA interaction network we identified includes a complex immune response regulatory subnetwork that controls the entire liver cirrhosis network. Additionally, we found 10 overlapping GO terms shared by both liver cirrhosis and hepatocellular carcinoma including “immune response” as well. Interestingly, the overlapping differentially expressed genes in liver cirrhosis and hepatocellular carcinoma were enriched in immune response-related functional terms. In summary, a complex gene regulatory network underlying immune response processes may play an important role in the development and progression of liver cirrhosis, and its development into hepatocellular carcinoma. PMID:28355233

Revealing the Effects of the Herbal Pair of Euphorbia kansui and Glycyrrhiza on Hepatocellular Carcinoma Ascites with Integrating Network Target Analysis and Experimental Validation

PubMed Central

Zhang, Yanqiong; Lin, Ya; Zhao, Haiyu; Guo, Qiuyan; Yan, Chen; Lin, Na

2016-01-01

Although the herbal pair of Euphorbia kansui (GS) and Glycyrrhiza (GC) is one of the so-called "eighteen antagonistic medicaments" in Chinese medicinal literature, it is prescribed in a classic Traditional Chinese Medicine (TCM) formula Gansui-Banxia-Tang for cancerous ascites, suggesting that GS and GC may exhibit synergistic or antagonistic effects in different combination designs. Here, we modeled the effects of GS/GC combination with a target interaction network and clarified the associations between the network topologies involving the drug targets and the drug combination effects. Moreover, the "edge-betweenness" values, which is defined as the frequency with which edges are placed on the shortest paths between all pairs of modules in network, were calculated, and the ADRB1-PIK3CG interaction exhibited the greatest edge-betweenness value, suggesting its crucial role in connecting the other edges in the network. Because ADRB1 and PIK3CG were putative targets of GS and GC, respectively, and both had functional interactions with AVPR2 approved as known therapeutic target for ascites, we proposed that the ADRB1-PIK3CG-AVPR2 signal axis might be involved in the effects of the GS-GC combination on ascites. This proposal was further experimentally validated in a H22 hepatocellular carcinoma (HCC) ascites model. Collectively, this systems-level investigation integrated drug target prediction and network analysis to reveal the combination principles of the herbal pair of GS and GC. Experimental validation in an in vivo system provided convincing evidence that different combination designs of GS and GC might result in synergistic or antagonistic effects on HCC ascites that might be partially related to their regulation of the ADRB1-PIK3CG-AVPR2 signal axis. PMID:27143956

Spatial heterogeneity regulates plant-pollinator networks across multiple landscape scales.

PubMed

Moreira, Eduardo Freitas; Boscolo, Danilo; Viana, Blandina Felipe

2015-01-01

Mutualistic plant-pollinator interactions play a key role in biodiversity conservation and ecosystem functioning. In a community, the combination of these interactions can generate emergent properties, e.g., robustness and resilience to disturbances such as fluctuations in populations and extinctions. Given that these systems are hierarchical and complex, environmental changes must have multiple levels of influence. In addition, changes in habitat quality and in the landscape structure are important threats to plants, pollinators and their interactions. However, despite the importance of these phenomena for the understanding of biological systems, as well as for conservation and management strategies, few studies have empirically evaluated these effects at the network level. Therefore, the objective of this study was to investigate the influence of local conditions and landscape structure at multiple scales on the characteristics of plant-pollinator networks. This study was conducted in agri-natural lands in Chapada Diamantina, Bahia, Brazil. Pollinators were collected in 27 sampling units distributed orthogonally along a gradient of proportion of agriculture and landscape diversity. The Akaike information criterion was used to select models that best fit the metrics for network characteristics, comparing four hypotheses represented by a set of a priori candidate models with specific combinations of the proportion of agriculture, the average shape of the landscape elements, the diversity of the landscape and the structure of local vegetation. The results indicate that a reduction of habitat quality and landscape heterogeneity can cause species loss and decrease of networks nestedness. These structural changes can reduce robustness and resilience of plant-pollinator networks what compromises the reproductive success of plants, the maintenance of biodiversity and the pollination service stability. We also discuss the possible explanations for these relationships and the implications for landscape planning in agricultural areas.

Spatial Heterogeneity Regulates Plant-Pollinator Networks across Multiple Landscape Scales

PubMed Central

Moreira, Eduardo Freitas; Boscolo, Danilo; Viana, Blandina Felipe

2015-01-01

Mutualistic plant-pollinator interactions play a key role in biodiversity conservation and ecosystem functioning. In a community, the combination of these interactions can generate emergent properties, e.g., robustness and resilience to disturbances such as fluctuations in populations and extinctions. Given that these systems are hierarchical and complex, environmental changes must have multiple levels of influence. In addition, changes in habitat quality and in the landscape structure are important threats to plants, pollinators and their interactions. However, despite the importance of these phenomena for the understanding of biological systems, as well as for conservation and management strategies, few studies have empirically evaluated these effects at the network level. Therefore, the objective of this study was to investigate the influence of local conditions and landscape structure at multiple scales on the characteristics of plant-pollinator networks. This study was conducted in agri-natural lands in Chapada Diamantina, Bahia, Brazil. Pollinators were collected in 27 sampling units distributed orthogonally along a gradient of proportion of agriculture and landscape diversity. The Akaike information criterion was used to select models that best fit the metrics for network characteristics, comparing four hypotheses represented by a set of a priori candidate models with specific combinations of the proportion of agriculture, the average shape of the landscape elements, the diversity of the landscape and the structure of local vegetation. The results indicate that a reduction of habitat quality and landscape heterogeneity can cause species loss and decrease of networks nestedness. These structural changes can reduce robustness and resilience of plant-pollinator networks what compromises the reproductive success of plants, the maintenance of biodiversity and the pollination service stability. We also discuss the possible explanations for these relationships and the implications for landscape planning in agricultural areas. PMID:25856293