Literature DB >> 25313165

Impact of upstream and downstream constraints on a signaling module's ultrasensitivity.

Edgar Altszyler1, Alejandra Ventura, Alejandro Colman-Lerner, Ariel Chernomoretz.   

Abstract

Much work has been done on the study of the biochemical mechanisms that result in ultrasensitive behavior of simple biochemical modules. However, in a living cell, such modules are embedded in a bigger network that constrains the range of inputs that the module will receive as well as the range of the module's outputs that network will be able to detect. Here, we studied how the effective ultrasensitivity of a modular system is affected by these restrictions. We use a simple setup to explore to what extent the dynamic range spanned by upstream and downstream components of an ultrasensitive module impact on the effective sensitivity of the system. Interestingly, we found for some ultrasensitive motifs that dynamic range limitations imposed by downstream components can produce effective sensitivities much larger than that of the original module when considered in isolation.

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Year:  2014        PMID: 25313165      PMCID: PMC4233326          DOI: 10.1088/1478-3975/11/6/066003

Source DB:  PubMed          Journal:  Phys Biol        ISSN: 1478-3967            Impact factor:   2.583


  47 in total

1.  Negative feedback and ultrasensitivity can bring about oscillations in the mitogen-activated protein kinase cascades.

Authors:  B N Kholodenko
Journal:  Eur J Biochem       Date:  2000-03

2.  Design principles of a bacterial signalling network.

Authors:  Markus Kollmann; Linda Løvdok; Kilian Bartholomé; Jens Timmer; Victor Sourjik
Journal:  Nature       Date:  2005-11-24       Impact factor: 49.962

3.  Molecular titration and ultrasensitivity in regulatory networks.

Authors:  Nicolas E Buchler; Matthieu Louis
Journal:  J Mol Biol       Date:  2008-10-10       Impact factor: 5.469

4.  Quantification of information transfer via cellular signal transduction pathways.

Authors:  B N Kholodenko; J B Hoek; H V Westerhoff; G C Brown
Journal:  FEBS Lett       Date:  1997-09-08       Impact factor: 4.124

Review 5.  Non-transcriptional regulatory processes shape transcriptional network dynamics.

Authors:  J Christian J Ray; Jeffrey J Tabor; Oleg A Igoshin
Journal:  Nat Rev Microbiol       Date:  2011-10-11       Impact factor: 60.633

6.  An amplified sensitivity arising from covalent modification in biological systems.

Authors:  A Goldbeter; D E Koshland
Journal:  Proc Natl Acad Sci U S A       Date:  1981-11       Impact factor: 11.205

7.  Tunable signal processing in synthetic MAP kinase cascades.

Authors:  Ellen C O'Shaughnessy; Santhosh Palani; James J Collins; Casim A Sarkar
Journal:  Cell       Date:  2011-01-07       Impact factor: 41.582

Review 8.  Nature, nurture, or chance: stochastic gene expression and its consequences.

Authors:  Arjun Raj; Alexander van Oudenaarden
Journal:  Cell       Date:  2008-10-17       Impact factor: 41.582

Review 9.  Synthetic biology.

Authors:  Steven A Benner; A Michael Sismour
Journal:  Nat Rev Genet       Date:  2005-07       Impact factor: 53.242

10.  A hidden feedback in signaling cascades is revealed.

Authors:  Alejandra C Ventura; Jacques-A Sepulchre; Sofía D Merajver
Journal:  PLoS Comput Biol       Date:  2008-03-21       Impact factor: 4.475

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  2 in total

1.  G Protein-Coupled Receptor Endocytosis Confers Uniformity in Responses to Chemically Distinct Ligands.

Authors:  Nikoleta G Tsvetanova; Michelle Trester-Zedlitz; Billy W Newton; Daniel P Riordan; Aparna B Sundaram; Jeffrey R Johnson; Nevan J Krogan; Mark von Zastrow
Journal:  Mol Pharmacol       Date:  2016-11-22       Impact factor: 4.436

2.  Ultrasensitivity in signaling cascades revisited: Linking local and global ultrasensitivity estimations.

Authors:  Edgar Altszyler; Alejandra C Ventura; Alejandro Colman-Lerner; Ariel Chernomoretz
Journal:  PLoS One       Date:  2017-06-29       Impact factor: 3.240

  2 in total

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