COMPACTNESS AND CYCLES IN SIGNAL TRANSDUCTION AND TRANSCRIPTIONAL REGULATION NETWORKS: A SIGNATURE OF NATURAL SELECTION?

2004 ◽  
Vol 07 (03n04) ◽  
pp. 419-432 ◽  
Author(s):  
ANDREAS WAGNER ◽  
JEREMIAH WRIGHT
Keyword(s):  
Signal Transduction ◽  
Transcriptional Regulation ◽  
Natural Selection ◽  
Biological Networks ◽  
Feedback Loops ◽  
Regulatory Pathways ◽  
Signal Transduction Networks ◽  
Transmission Of Information ◽  
Randomized Networks ◽  
Genome Scale

We ask whether natural selection has shaped three biologically important features of 15 signal transduction networks and two genome-scale transcriptional regulation networks. These features are regulatory cycles, the lengths of the longest pathways through a network — a measure of network compactness — and the abundance of node pairs connected by many alternative regulatory pathways. We determine whether these features are significantly more or less abundant in biological networks than in randomized networks with the same distribution of incoming and outgoing connections per network node. We find that autoregulatory cycles are of exceptionally high abundance in transcriptional regulation networks. All other cycles, however, are significantly less abundant in several signal transduction networks. This suggests that the multistability caused by complex feedback loops in a network may interfere with the functioning of such networks. We also find that several of the networks we examine are more compact than expected by chance alone. This raises the possibility that the transmission of information through such networks, which is fastest in compact networks, is a biologically important characteristic of such networks.

scholarly journals S100A4 and its role in metastasis – computational integration of data on biological networks

2015 ◽  
Vol 11 (8) ◽  
pp. 2238-2246 ◽  
Author(s):  
Antoine Buetti-Dinh ◽  
Igor V. Pivkin ◽  
Ran Friedman
Keyword(s):  
Signal Transduction ◽  
Biological Networks ◽  
Signal Transduction Networks

Characterising signal transduction networks is fundamental to our understanding of biology.

scholarly journals A scalable method for parameter-free simulation and validation of mechanistic cellular signal transduction network models

2020 ◽  
Vol 6 (1) ◽  
Author(s):  
Jesper Romers ◽  
Sebastian Thieme ◽  
Ulrike Münzner ◽  
Marcus Krantz
Keyword(s):  
Signal Transduction ◽  
Network Models ◽  
Boolean Model ◽  
Boolean Logic ◽  
System Level ◽  
Signal Transduction Networks ◽  
Scale Models ◽  
Update Rules ◽  
Genome Scale ◽  
Simulation And Validation

AbstractThe metabolic modelling community has established the gold standard for bottom-up systems biology with reconstruction, validation and simulation of mechanistic genome-scale models. Similar methods have not been established for signal transduction networks, where the representation of complexes and internal states leads to scalability issues in both model formulation and execution. While rule- and agent-based methods allow efficient model definition and execution, respectively, model parametrisation introduces an additional layer of uncertainty due to the sparsity of reliably measured parameters. Here, we present a scalable method for parameter-free simulation of mechanistic signal transduction networks. It is based on rxncon and uses a bipartite Boolean logic with separate update rules for reactions and states. Using two generic update rules, we enable translation of any rxncon model into a unique Boolean model, which can be used for network validation and simulation—allowing the prediction of system-level function directly from molecular mechanistic data. Through scalable model definition and simulation, and the independence of quantitative parameters, it opens up for simulation and validation of mechanistic genome-scale models of signal transduction networks.

scholarly journals A scalable method for parameter-free simulation and validation of mechanistic cellular signal transduction network models

2017 ◽  
Author(s):  
Jesper Romers ◽  
Sebastian Thieme ◽  
Ulrike Münzner ◽  
Marcus Krantz
Keyword(s):  
Signal Transduction ◽  
Network Models ◽  
Boolean Model ◽  
Boolean Logic ◽  
System Level ◽  
Signal Transduction Networks ◽  
Scale Models ◽  
Update Rules ◽  
Genome Scale ◽  
Simulation And Validation

AbstractThe metabolic modelling community has established the gold standard for bottom-up systems biology with reconstruction, validation and simulation of mechanistic genome-scale models. Similar methods have not been established for signal transduction networks, where the representation of internal states leads to scalability issues in both model formulation and execution. While rule- and agent-based methods allow efficient model definition and execution, respectively, model parametrisation introduces an additional layer of uncertainty due to the sparsity of reliably measured parameters. Here, we present a scalable method for parameter-free simulation of mechanistic signal transduction networks. It is based on rxncon and uses a bipartite Boolean logic with separate update rules for reactions and states. Using two generic update rules, we enable translation of any rxncon model into a unique Boolean model, which can be used for network validation and simulation - allowing the prediction of system level function directly from molecular mechanistic data. Through scalable model definition and simulation, and the independence of quantitative parameters, it opens up for simulation and validation of mechanistic genome-scale models of signal transduction networks.

Toward Genome-Scale Models of Signal Transduction Networks

2017 ◽  
pp. 215-242 ◽  
Author(s):  
Ulrike Münzner ◽  
Timo Lubitz ◽  
Edda Klipp ◽  
Marcus Krantz
Keyword(s):  
Signal Transduction ◽  
Signal Transduction Networks ◽  
Scale Models ◽  
Genome Scale

Genetic regulation of entry into meiosis in Caenorhabditis elegans

Development ◽  
1998 ◽  
Vol 125 (10) ◽  
pp. 1803-1813 ◽  
Author(s):  
L.C. Kadyk ◽  
J. Kimble
Keyword(s):  
Signal Transduction ◽  
Caenorhabditis Elegans ◽  
Germ Cells ◽  
Genetic Regulation ◽  
Signal Transduction Pathway ◽  
Mitotic Cell ◽  
Transduction Pathway ◽  
Germline Development ◽  
Large Tumor ◽  
Regulatory Pathways

The Caenorhabditis elegans germline is composed of mitotically dividing cells at the distal end that give rise to meiotic cells more proximally. Specification of the distal region as mitotic relies on induction by the somatic distal tip cell and the glp-1 signal transduction pathway. However, the genetic control over the transition from mitosis to meiosis is not understood. In this paper, we report the identification of a gene, gld-2, that has at least two functions in germline development. First, gld-2 is required for normal progression through meiotic prophase. Second, gld-2 promotes entry into meiosis from the mitotic cell cycle. With respect to this second function, gld-2 appears to be functionally redundant with a previously described gene, gld-1 (Francis, R., Barton, M. K., Kimble, J. and Schedl, T. (1995) Genetics 139, 579–606). Germ cells in gld-1(o) and gld-2 single mutants enter meiosis at the normal time, but germ cells in gld-2 gld-1(o) double mutants do not enter meiosis. Instead, the double mutant germline is mitotic throughout and forms a large tumor. We suggest that gld-1 and gld-2 define two independent regulatory pathways, each of which can be sufficient for entry into meiosis. Epistasis analyses show that gld-1 and gld-2 work downstream of the glp-1 signal transduction pathway. Therefore, we hypothesize that glp-1 promotes proliferation by inhibiting the meiosis-promoting functions of gld-1 and gld-2.

scholarly journals Transcriptional regulation of metabolism in disease: From transcription factors to epigenetics

PeerJ ◽  
2018 ◽  
Vol 6 ◽  
pp. e5062 ◽  
Author(s):  
Liam J. Hawkins ◽  
Rasha Al-attar ◽  
Kenneth B. Storey
Keyword(s):  
Transcriptional Regulation ◽  
Genomic Sequence ◽  
Regulatory Elements ◽  
Regulatory Pathways ◽  
Transcriptional Dysregulation ◽  
Disease States ◽  
Specific Subset ◽  
Transcriptional Regulatory ◽  
Cis And Trans ◽  
Or Genes

Every cell in an individual has largely the same genomic sequence and yet cells in different tissues can present widely different phenotypes. This variation arises because each cell expresses a specific subset of genomic instructions. Control over which instructions, or genes, are expressed is largely controlled by transcriptional regulatory pathways. Each cell must assimilate a huge amount of environmental input, and thus it is of no surprise that transcription is regulated by many intertwining mechanisms. This large regulatory landscape means there are ample possibilities for problems to arise, which in a medical context means the development of disease states. Metabolism within the cell, and more broadly, affects and is affected by transcriptional regulation. Metabolism can therefore contribute to improper transcriptional programming, or pathogenic metabolism can be the result of transcriptional dysregulation. Here, we discuss the established and emerging mechanisms for controling transcription and how they affect metabolism in the context of pathogenesis. Cis- and trans-regulatory elements, microRNA and epigenetic mechanisms such as DNA and histone methylation, all have input into what genes are transcribed. Each has also been implicated in diseases such as metabolic syndrome, various forms of diabetes, and cancer. In this review, we discuss the current understanding of these areas and highlight some natural models that may inspire future therapeutics.

Intracellular signalling

2010 ◽  
pp. 169-176
Author(s):  
R. Andres Floto
Keyword(s):  
Signal Transduction ◽  
Plasma Membrane ◽  
Cell Surface ◽  
Intracellular Signalling ◽  
Cell Surface Receptors ◽  
Surface Receptors ◽  
Transmission Of Information ◽  
Effective Transmission

This section outlines the general principles of intracellular signalling. Focusing on cell surface receptors, the requirements for effective transmission of information across the plasma membrane are outlined. The principal mechanisms utilized in mammalian signal transduction are described. For each, the pathological consequences of aberrant signalling and means by which pathways can be pharmacologically targeted are described in molecular terms....

Intracellular signalling

2020 ◽  
pp. 256-265
Author(s):  
R. Andres Floto
Keyword(s):  
Signal Transduction ◽  
Plasma Membrane ◽  
Cell Surface ◽  
Intracellular Signalling ◽  
Signalling Pathways ◽  
Molecular Processes ◽  
Surface Receptors ◽  
Intracellular Signalling Pathways ◽  
Transmission Of Information ◽  
Effective Transmission

This chapter outlines the general principles of intracellular signalling. Focusing on cell surface receptors, the requirements for effective transmission of information across the plasma membrane are outlined. The principal mechanisms utilized in mammalian signal transduction are described. For each, the pathological consequences of aberrant signalling and means by which pathways can be pharmacologically targeted are described in molecular terms. Intracellular signalling pathways permit the transmission and integration of information within cells. Mammalian receptor signalling relies on only a small number of distinct molecular processes which interact to determine cellular responses. Rapid advances in our knowledge of the mechanisms of intracellular signalling has greatly increased understanding of how cells function physiologically, how they malfunction pathologically, and how their behaviour might be manipulated therapeutically.

Adaptable Ancestors

2020 ◽  
pp. 71-91
Author(s):  
David F. Bjorklund
Keyword(s):  
Natural Selection ◽  
Evolutionary Change ◽  
Behavioral Changes ◽  
Social Transmission ◽  
Significant Extent ◽  
Transmission Of Information ◽  
Selection Behavior ◽  
Novel Environments ◽  
High Level ◽  
Or Genes

The high level of plasticity shown by children today was also a feature of our forechildren. Experiences early in life can modify the morphology or behavior of an animal and result in new pressures that can be the focus of natural selection. Behavior, in fact, takes the lead in evolution, because it is more susceptible to change than morphology or genes. Most of the changes early in development, at least for mammals, were accomplished in the presence of mothers. To a significant extent, mothers are the environment for young mammals, making mothers the environment for evolutionary change. Significant behavioral changes in evolution are most likely to occur in large-brained animals, who are better able to deal with novel environments through innovation and social transmission of information than smaller-brained animals.

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