1,927 research outputs found

    Topological basis of signal integration in the transcriptional-regulatory network of the yeast, Saccharomyces cerevisiae

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    BACKGROUND: Signal recognition and information processing is a fundamental cellular function, which in part involves comprehensive transcriptional regulatory (TR) mechanisms carried out in response to complex environmental signals in the context of the cell's own internal state. However, the network topological basis of developing such integrated responses remains poorly understood. RESULTS: By studying the TR network of the yeast Saccharomyces cerevisiae we show that an intermediate layer of transcription factors naturally segregates into distinct subnetworks. In these topological units transcription factors are densely interlinked in a largely hierarchical manner and respond to external signals by utilizing a fraction of these subnets. CONCLUSION: As transcriptional regulation represents the 'slow' component of overall information processing, the identified topology suggests a model in which successive waves of transcriptional regulation originating from distinct fractions of the TR network control robust integrated responses to complex stimuli

    An evolutionary and functional assessment of regulatory network motifs.

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    BackgroundCellular functions are regulated by complex webs of interactions that might be schematically represented as networks. Two major examples are transcriptional regulatory networks, describing the interactions among transcription factors and their targets, and protein-protein interaction networks. Some patterns, dubbed motifs, have been found to be statistically over-represented when biological networks are compared to randomized versions thereof. Their function in vitro has been analyzed both experimentally and theoretically, but their functional role in vivo, that is, within the full network, and the resulting evolutionary pressures remain largely to be examined.ResultsWe investigated an integrated network of the yeast Saccharomyces cerevisiae comprising transcriptional and protein-protein interaction data. A comparative analysis was performed with respect to Candida glabrata, Kluyveromyces lactis, Debaryomyces hansenii and Yarrowia lipolytica, which belong to the same class of hemiascomycetes as S. cerevisiae but span a broad evolutionary range. Phylogenetic profiles of genes within different forms of the motifs show that they are not subject to any particular evolutionary pressure to preserve the corresponding interaction patterns. The functional role in vivo of the motifs was examined for those instances where enough biological information is available. In each case, the regulatory processes for the biological function under consideration were found to hinge on post-transcriptional regulatory mechanisms, rather than on the transcriptional regulation by network motifs.ConclusionThe overabundance of the network motifs does not have any immediate functional or evolutionary counterpart. A likely reason is that motifs within the networks are not isolated, that is, they strongly aggregate and have important edge and/or node sharing with the rest of the network

    Data integration, pathway analysis and mining for systems biology

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    Post-genomic molecular biology embodies high-throughput experimental techniques and hence is a data-rich field. The goal of this thesis is to develop bioinformatics methods to utilise publicly available data in order to produce knowledge and to aid mining of newly generated data. As an example of knowledge or hypothesis generation, consider function prediction of biological molecules. Assignment of protein function is a non-trivial task owing to the fact that the same protein may be involved in different biological processes, depending on the state of the biological system and protein localisation. The function of a gene or a gene product may be provided as a textual description in a gene or protein annotation database. Such textual descriptions lack in providing the contextual meaning of the gene function. Therefore, we need ways to represent the meaning in a formal way. Here we apply data integration approach to provide rich representation that enables context-sensitive mining of biological data in terms of integrated networks and conceptual spaces. Context-sensitive gene function annotation follows naturally from this framework, as a particular application. Next, knowledge that is already publicly available can be used to aid mining of new experimental data. We developed an integrative bioinformatics method that utilises publicly available knowledge of protein-protein interactions, metabolic networks and transcriptional regulatory networks to analyse transcriptomics data and predict altered biological processes. We applied this method to a study of dynamic response of Saccharomyces cerevisiae to oxidative stress. The application of our method revealed dynamically altered biological functions in response to oxidative stress, which were validated by comprehensive in vivo metabolomics experiments. The results provided in this thesis indicate that integration of heterogeneous biological data facilitates advanced mining of the data. The methods can be applied for gaining insight into functions of genes, gene products and other molecules, as well as for offering functional interpretation to transcriptomics and metabolomics experiments

    Integrating Phosphorylation Network with Transcriptional Network Reveals Novel Functional Relationships

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    Phosphorylation and transcriptional regulation events are critical for cells to transmit and respond to signals. In spite of its importance, systems-level strategies that couple these two networks have yet to be presented. Here we introduce a novel approach that integrates the physical and functional aspects of phosphorylation network together with the transcription network in S.cerevisiae, and demonstrate that different network motifs are involved in these networks, which should be considered in interpreting and integrating large scale datasets. Based on this understanding, we introduce a HeRS score (hetero-regulatory similarity score) to systematically characterize the functional relevance of kinase/phosphatase involvement with transcription factor, and present an algorithm that predicts hetero-regulatory modules. When extended to signaling network, this approach confirmed the structure and cross talk of MAPK pathways, inferred a novel functional transcription factor Sok2 in high osmolarity glycerol pathway, and explained the mechanism of reduced mating efficiency upon Fus3 deletion. This strategy is applicable to other organisms as large-scale datasets become available, providing a means to identify the functional relationships between kinases/phosphatases and transcription factors

    Engineering microbialm phenotypes through rewiring of genetic networks

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    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

    Beyond hairballs: depicting complexity of a kinase-phosphatase network in the budding yeast

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    Les kinases et les phosphatases (KP) représentent la plus grande famille des enzymes dans la cellule. Elles régulent les unes les autres ainsi que 60 % du protéome, formant des réseaux complexes kinase-phosphatase (KP-Net) jouant un rôle essentiel dans la signalisation cellulaire. Ces réseaux caractérisés d’une organisation de type commandes-exécutions possèdent généralement une structure hiérarchique. Malgré les nombreuse études effectuées sur le réseau KP-Net chez la levure, la structure hiérarchique ainsi que les principes fonctionnels sont toujours peux connu pour ce réseau. Dans ce contexte, le but de cette thèse consistait à effectuer une analyse d’intégration des données provenant de différentes sources avec la structure hiérarchique d’un réseau KP-Net de haute qualité chez la levure, S. cerevisiae, afin de générer des hypothèses concernant les principes fonctionnels de chaque couche de la hiérarchie du réseau KP-Net. En se basant sur une curation de données d’interactions effectuée dans la présente et dans d’autres études, le plus grand et authentique réseau KP-Net reconnu jusqu’à ce jour chez la levure a été assemblé dans cette étude. En évaluant le niveau hiérarchique du KP-Net en utilisant la métrique de la centralisation globale et en élucidant sa structure hiérarchique en utilisant l'algorithme vertex-sort (VS), nous avons trouvé que le réseau KP-Net possède une structure hiérarchique ayant la forme d’un sablier, formée de trois niveaux disjoints (supérieur, central et inférieur). En effet, le niveau supérieur du réseau, contenant un nombre élevé de KPs, était enrichi par des KPs associées à la régulation des signaux cellulaire; le niveau central, formé d’un nombre limité de KPs fortement connectées les unes aux autres, était enrichi en KPs impliquées dans la régulation du cycle cellulaire; et le niveau inférieur, composé d’un nombre important de KPs, était enrichi en KPs impliquées dans des processus cellulaires diversifiés. En superposant une grande multitude de propriétés biologiques des KPs sur le réseau KP-Net, le niveau supérieur était enrichi en phosphatases alors que le niveau inférieur en était appauvri, suggérant que les phosphatases seraient moins régulées par phosphorylation et déphosphorylation que les kinases. De plus, le niveau central était enrichi en KPs représentant des « bottlenecks », participant à plus d’une voie de signalisation, codées par des gènes essentiels et en KPs qui étaient les plus strictement régulées dans l’espace et dans le temps. Ceci implique que les KPs qui jouent un rôle essentiel dans le réseau KP-Net devraient être étroitement contrôlées. En outre, cette étude a montré que les protéines des KPs classées au niveau supérieur du réseau sont exprimées à des niveaux d’abondance plus élevés et à un niveau de bruit moins élevé que celles classées au niveau inférieur du réseau, suggérant que l’expression des enzymes à des abondances élevées invariables au niveau supérieur du réseau KP-Net pourrait être importante pour assurer un système robuste de signalisation. L’étude de l’algorithme VS a montré que le degré des nœuds affecte leur classement dans les différents niveaux d’un réseau hiérarchique sans biaiser les résultats biologiques du réseau étudié. En outre, une analyse de robustesse du réseau KP-Net a montré que les niveaus du réseau KP-Net sont modérément stable dans des réseaux bruités générés par ajout d’arrêtes au réseau KP-Net. Cependant, les niveaux de ces réseaux bruités et de ceux du réseau KP-Net se superposent significativement. De plus, les propriétés topologiques et biologiques du réseau KP-Net étaient retenues dans les réseaux bruités à différents niveaux. Ces résultats indiquant que bien qu’une robustesse partielle de nos résultats ait été observée, ces derniers représentent l’état actuel de nos connaissances des réseaux KP-Nets. Finalement, l’amélioration des techniques dédiées à l’identification des substrats des KPs aideront davantage à comprendre comment les réseaux KP-Nets fonctionnent. À titre d’exemple, je décris, dans cette thèse, une stratégie que nous avons conçu et qui permet à déterminer les interactions KP-substrats et les sous-unités régulatrices sur lesquelles ces interactions dépendent. Cette stratégie est basée sur la complémentation des fragments de protéines basée sur la cytosine désaminase chez la levure (OyCD PCA). L’OyCD PCA représente un essai in vivo à haut débit qui promet une description plus précise des réseaux KP-Nets complexes. En l’appliquant pour déterminer les substrats de la kinase cycline-dépendante de type 1 (Cdk1, appelée aussi Cdc28) chez la levure et l’implication des cyclines dans la phosphorylation de ces substrats par Cdk1, l’essai OyCD PCA a montré un comportement compensatoire collectif des cyclines pour la majorité des substrats. De plus, cet essai a montré que la tubuline- γ est phosphorylée spécifiquement par Clb3-Cdk1, établissant ainsi le moment pendant lequel cet événement contrôle l'assemblage du fuseau mitotique.Kinases and phosphatases (KP) form the largest family of enzymes in living cells. They regulate each other and 60 % of the proteome forming complex kinase-phosphatase networks (KP-Net) essential for cell signaling. Such networks having the command-execution aspect tend to have a hierarchical structure. Despite the extensive study of the KP-Net in the budding yeast, the hierarchical structure as well as the functional principles of this network are still not known. In this context, this thesis aims to perform an integrative analysis of multi-omics data with the hierarchical structure of a bona fide KP-Net in the budding yeast Saccharomyces cerevisiae, in order to generate hypotheses about the functional principles of each layer in the KP-Net hierarchy. Based on a literature curation effort accomplished in this and in other studies, the largest bona fide KP-Net of the S. cerevisiae known to date was assembled in this thesis. By assessing the hierarchical level of the KP-Net using the global reaching centrality and by elucidating the its hierarchical structure using the vertex-sort (VS) algorithm, we found that the KP-Net has a moderate hierarchical structure made of three disjoint layers (top, core and bottom) resembling a bow tie shape. The top layer having a large size was found enriched for signaling regulation; the core layer made of few strongly connected KPs was found enriched mostly for cell cycle regulation; and the bottom layer having a large size was found enriched for diverse biological processes. On overlaying a wide range of KP biological properties on top of the KP-Net hierarchical structure, the top layer was found enriched for and the bottom layer was found depleted for phosphatases, suggesting that phosphatases are less regulated by phosphorylation and dephosphoryation interactions (PDI) than kinases. Moreover, the core layer was found enriched for KPs representing bottlenecks, pathway-shared components, essential genes and for the most tightly regulated KPs in time and space, implying that KPs playing an essential role in the KP-Net should be firmly controlled. Interestingly, KP proteins in the top layer were found more abundant and less noisy than those of the bottom layer, suggesting that availability of enzymes at invariable protein expression level at the top of the network might be important to ensure a robust signaling. Analysis of the VS algorithm showed that node degrees affect their classification in the different layers of a network hierarchical structure without biasing biological results of the sorted network. Robustness analysis of the KP-Net showed that KP-Net layers are moderately stable in noisy networks generated by adding edges to the KP-Net. However, layers of these noisy overlap significantly with those of the KP-Net. Moreover, topological and biological properties of the KP-Net were retained in the noisy networks to different levels. These findings indicate that despite the observed partial robustness of our results, they mostly represent our current knowledge about KP-Nets. Finally, enhancement of techniques dedicated to identify KPs substrates will enhance our understanding about how KP-Nets function. As an example, I describe here a strategy that we devised to help in determining KP-substrate interactions and the regulatory subunits on which these interactions depend. The strategy is based on a protein-fragment complementation assay based on the optimized yeast cytosine deaminase (OyCD PCA). The OyCD PCA represents a large scale in vivo screen that promises a substantial improvement in delineating the complex KP-Nets. We applied the strategy to determine substrates of the cyclin-dependent kinase 1 (Cdk1; also called Cdc28) and cyclins implicated in phosphorylation of these substrates by Cdk1 in S. cerevisiae. The OyCD PCA showed a wide compensatory behavior of cyclins for most of the substrates and the phosphorylation of γ-tubulin specifically by Clb3-Cdk1, thus establishing the timing of the latter event in controlling assembly of the mitotic spindle

    Graph Theory and Networks in Biology

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    In this paper, we present a survey of the use of graph theoretical techniques in Biology. In particular, we discuss recent work on identifying and modelling the structure of bio-molecular networks, as well as the application of centrality measures to interaction networks and research on the hierarchical structure of such networks and network motifs. Work on the link between structural network properties and dynamics is also described, with emphasis on synchronization and disease propagation.Comment: 52 pages, 5 figures, Survey Pape

    The Metabolic Core and Catalytic Switches Are Fundamental Elements in the Self-Regulation of the Systemic Metabolic Structure of Cells

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    [Background] Experimental observations and numerical studies with dissipative metabolic networks have shown that cellular enzymatic activity self-organizes spontaneously leading to the emergence of a metabolic core formed by a set of enzymatic reactions which are always active under all environmental conditions, while the rest of catalytic processes are only intermittently active. The reactions of the metabolic core are essential for biomass formation and to assure optimal metabolic performance. The on-off catalytic reactions and the metabolic core are essential elements of a Systemic Metabolic Structure which seems to be a key feature common to all cellular organisms. [Methodology/Principal Findings] In order to investigate the functional importance of the metabolic core we have studied different catalytic patterns of a dissipative metabolic network under different external conditions. The emerging biochemical data have been analysed using information-based dynamic tools, such as Pearson's correlation and Transfer Entropy (which measures effective functionality). Our results show that a functional structure of effective connectivity emerges which is dynamical and characterized by significant variations of bio-molecular information flows. [Conclusions/Significance] We have quantified essential aspects of the metabolic core functionality. The always active enzymatic reactions form a hub –with a high degree of effective connectivity- exhibiting a wide range of functional information values being able to act either as a source or as a sink of bio-molecular causal interactions. Likewise, we have found that the metabolic core is an essential part of an emergent functional structure characterized by catalytic modules and metabolic switches which allow critical transitions in enzymatic activity. Both, the metabolic core and the catalytic switches in which also intermittently-active enzymes are involved seem to be fundamental elements in the self-regulation of the Systemic Metabolic Structure.Consejo Superior de Investigaciones Cientificas (CSIC),grant 201020I026. Ministerio de Ciencia e Innovacion (MICINN). Programa Ramon y Cajal. Campus de Excelencia Internacional CEI BioTIC GENIL, grant PYR-2010-14. Junta de Andalucia, grant P09-FQM-4682
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