Gene switching rate determines response to extrinsic perturbations in the self-activation transcriptional network motif View Full Text


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Article Info

DATE

2016-06-03

AUTHORS

Sebastiano de Franciscis, Giulio Caravagna, Giancarlo Mauri, Alberto d’Onofrio

ABSTRACT

Gene switching dynamics is a major source of randomness in genetic networks, also in the case of large concentrations of the transcription factors. In this work, we consider a common network motif - the positive feedback of a transcription factor on its own synthesis - and assess its response to extrinsic noises perturbing gene deactivation in a variety of settings where the network might operate. These settings are representative of distinct cellular types, abundance of transcription factors and ratio between gene switching and protein synthesis rates. By investigating noise-induced transitions among the different network operative states, our results suggest that gene switching rates are key parameters to shape network response to external perturbations and that such response depends on the particular biological setting, i.e. the characteristic time scales and protein abundance. These results might have implications on our understanding of irreversible transitions for noise-related phenomena such as cellular differentiation. In addition these evidences suggest to adopt the appropriate mathematical model of the network in order to analyze the system consistently to the reference biological setting. More... »

PAGES

26980

References to SciGraph publications

  • 2006. Noise-Induced Transitions, Theory and Applications in Physics, Chemistry, and Biology in NONE
  • 2005-05. Enhancement of cellular memory by reducing stochastic transitions in NATURE
  • 2013-04-14. Absolute quantification of transcription factors during cellular differentiation using multiplexed targeted proteomics in NATURE METHODS
  • 2013. Bounded Noises in Physics, Biology, and Engineering in NONE
  • 2005-08-07. Contributions of low molecule number and chromosomal positioning to stochastic gene expression in NATURE GENETICS
  • 2010-09. Functional roles for noise in genetic circuits in NATURE
  • 2006-03. Stochastic protein expression in individual cells at the single molecule level in NATURE
  • 1972-04. Chemical reaction models for non-equilibrium phase transitions in ZEITSCHRIFT FÜR PHYSIK A HADRONS AND NUCLEI
  • 2014-04-04. Classification of transient behaviours in a time-dependent toggle switch model in BMC SYSTEMS BIOLOGY
  • 2003-11. A positive-feedback-based bistable ‘memory module’ that governs a cell fate decision in NATURE
  • 2011. Delay Stochastic Simulation of Biological Systems: A Purely Delayed Approach in TRANSACTIONS ON COMPUTATIONAL SYSTEMS BIOLOGY XIII
  • 2014-01-06. Global dynamic optimization approach to predict activation in metabolic pathways in BMC SYSTEMS BIOLOGY
  • 2000-01. Construction of a genetic toggle switch in Escherichia coli in NATURE
  • 2006-02-28. Multistable and multistep dynamics in neutrophil differentiation in BMC MOLECULAR AND CELL BIOLOGY
  • 2000-06. Engineering stability in gene networks by autoregulation in NATURE
  • 2014-07-21. The linear interplay of intrinsic and extrinsic noises ensures a high accuracy of cell fate selection in budding yeast in SCIENTIFIC REPORTS
  • 2003-04. Noise in eukaryotic gene expression in NATURE
  • 2002-11. Control, exploitation and tolerance of intracellular noise in NATURE
  • 1977. Synergetics, A Workshop Proceedings of the International Workshop on Synergetics at Schloss Elmau, Bavaria, May 2–7, 1977 in NONE
  • 2014-05-13. Bounded noises as a natural tool to model extrinsic fluctuations in biomolecular networks in NATURAL COMPUTING
  • 2005-05-10. Stochasticity in gene expression: from theories to phenotypes in NATURE REVIEWS GENETICS
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1038/srep26980

    DOI

    http://dx.doi.org/10.1038/srep26980

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1014449236

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/27256916


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