Literature DB >> 23283231

Gene regulation by riboswitches with and without negative feedback loop.

Jong-Chin Lin1, D Thirumalai.   

Abstract

Riboswitches, structured elements in the untranslated regions of messenger RNAs, regulate gene expression by binding specific metabolites. We introduce a kinetic network model that describes the functions of riboswitches at the systems level. Using experimental data for flavin mononucleotide riboswitch as a guide, we show that efficient function, implying a large dynamic range without compromising the requirement to suppress transcription, is determined by a balance between the transcription speed, the folding and unfolding rates of the aptamer, and the binding rates of the metabolite. We also investigated the effect of negative feedback accounting for binding to metabolites, which are themselves the products of genes that are being regulated. For a range of transcription rates negative feedback suppresses gene expression by nearly 10-fold. Negative feedback speeds the gene expression response time, and suppresses the change of steady-state protein concentration by half relative to that without feedback, when there is a modest spike in DNA concentration. A dynamic phase diagram expressed in terms of transcription speed, folding rates, and metabolite binding rates predicts different scenarios in riboswitch-mediated transcription regulation.
Copyright © 2012 Biophysical Society. Published by Elsevier Inc. All rights reserved.

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Year:  2012        PMID: 23283231      PMCID: PMC3514527          DOI: 10.1016/j.bpj.2012.10.026

Source DB:  PubMed          Journal:  Biophys J        ISSN: 0006-3495            Impact factor:   4.033


  28 in total

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Authors:  Daniel R Larson; Daniel Zenklusen; Bin Wu; Jeffrey A Chao; Robert H Singer
Journal:  Science       Date:  2011-04-22       Impact factor: 47.728

2.  Model-driven engineering of RNA devices to quantitatively program gene expression.

Authors:  James M Carothers; Jonathan A Goler; Darmawi Juminaga; Jay D Keasling
Journal:  Science       Date:  2011-12-23       Impact factor: 47.728

3.  Guiding bacteria with small molecules and RNA.

Authors:  Shana Topp; Justin P Gallivan
Journal:  J Am Chem Soc       Date:  2007-05-05       Impact factor: 15.419

Review 4.  Riboswitches: emerging themes in RNA structure and function.

Authors:  Rebecca K Montange; Robert T Batey
Journal:  Annu Rev Biophys       Date:  2008       Impact factor: 12.981

5.  The glmS riboswitch integrates signals from activating and inhibitory metabolites in vivo.

Authors:  Peter Y Watson; Martha J Fedor
Journal:  Nat Struct Mol Biol       Date:  2011-02-13       Impact factor: 15.369

6.  Defining network topologies that can achieve biochemical adaptation.

Authors:  Wenzhe Ma; Ala Trusina; Hana El-Samad; Wendell A Lim; Chao Tang
Journal:  Cell       Date:  2009-08-21       Impact factor: 41.582

7.  Control of alternative RNA splicing and gene expression by eukaryotic riboswitches.

Authors:  Ming T Cheah; Andreas Wachter; Narasimhan Sudarsan; Ronald R Breaker
Journal:  Nature       Date:  2007-04-29       Impact factor: 49.962

Review 8.  Engineering ligand-responsive gene-control elements: lessons learned from natural riboswitches.

Authors:  K H Link; R R Breaker
Journal:  Gene Ther       Date:  2009-07-09       Impact factor: 5.250

9.  Design principles for riboswitch function.

Authors:  Chase L Beisel; Christina D Smolke
Journal:  PLoS Comput Biol       Date:  2009-04-17       Impact factor: 4.475

10.  Design principles for ligand-sensing, conformation-switching ribozymes.

Authors:  Xi Chen; Andrew D Ellington
Journal:  PLoS Comput Biol       Date:  2009-12-24       Impact factor: 4.475

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  4 in total

1.  Using simulations and kinetic network models to reveal the dynamics and functions of riboswitches.

Authors:  Jong-Chin Lin; Jeseong Yoon; Changbong Hyeon; D Thirumalai
Journal:  Methods Enzymol       Date:  2015-02-03       Impact factor: 1.600

2.  Secondary structural entropy in RNA switch (Riboswitch) identification.

Authors:  Amirhossein Manzourolajdad; Jonathan Arnold
Journal:  BMC Bioinformatics       Date:  2015-04-28       Impact factor: 3.169

3.  In silico investigation of riboswitches in fungi: structural and dynamical insights into TPP riboswitches in Aspergillus oryzae.

Authors:  Valdemir Vargas-Junior; Deborah Antunes; Ana Carolina Guimarães; Ernesto Caffarena
Journal:  RNA Biol       Date:  2021-12-31       Impact factor: 4.652

4.  Kinetics of allosteric transitions in S-adenosylmethionine riboswitch are accurately predicted from the folding landscape.

Authors:  Jong-Chin Lin; D Thirumalai
Journal:  J Am Chem Soc       Date:  2013-10-22       Impact factor: 15.419

  4 in total

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