Literature DB >> 25601722

Analysis of Coupled Reaction-Diffusion Equations for RNA Interactions.

Maryann E Hohn1, Bo Li2, Weihua Yang3.   

Abstract

We consider a system of coupled reaction-diffusion equations that models the interaction between multiple types of chemical species, particularly the interaction between one messenger RNA and different types of non-coding microRNAs in biological cells. We construct various modeling systems with different levels of complexity for the reaction, nonlinear diffusion, and coupled reaction and diffusion of the RNA interactions, respectively, with the most complex one being the full coupled reaction-diffusion equations. The simplest system consists of ordinary differential equations (ODE) modeling the chemical reaction. We present a derivation of this system using the chemical master equation and the mean-field approximation, and prove the existence, uniqueness, and linear stability of equilibrium solution of the ODE system. Next, we consider a single, nonlinear diffusion equation for one species that results from the slow diffusion of the others. Using variational techniques, we prove the existence and uniqueness of solution to a boundary-value problem of this nonlinear diffusion equation. Finally, we consider the full system of reaction-diffusion equations, both steady-state and time-dependent. We use the monotone method to construct iteratively upper and lower solutions and show that their respective limits are solutions to the reaction-diffusion system. For the time-dependent system of reaction-diffusion equations, we obtain the existence and uniqueness of global solutions. We also obtain some asymptotic properties of such solutions.

Entities:  

Keywords:  RNA; gene expression; maximum principle; monotone methods; reaction-diffusion systems; variational methods; well-posedness

Year:  2015        PMID: 25601722      PMCID: PMC4296743          DOI: 10.1016/j.jmaa.2014.12.028

Source DB:  PubMed          Journal:  J Math Anal Appl        ISSN: 0022-247X            Impact factor:   1.583


  11 in total

Review 1.  MicroRNAs: small RNAs with a big role in gene regulation.

Authors:  Lin He; Gregory J Hannon
Journal:  Nat Rev Genet       Date:  2004-07       Impact factor: 53.242

2.  Competition between small RNAs: a quantitative view.

Authors:  Adiel Loinger; Yael Shemla; Itamar Simon; Hanah Margalit; Ofer Biham
Journal:  Biophys J       Date:  2012-04-18       Impact factor: 4.033

3.  Target-specific and global effectors in gene regulation by MicroRNA.

Authors:  Erel Levine; Eshel Ben Jacob; Herbert Levine
Journal:  Biophys J       Date:  2007-09-14       Impact factor: 4.033

Review 4.  Small non-coding RNAs in animal development.

Authors:  Giovanni Stefani; Frank J Slack
Journal:  Nat Rev Mol Cell Biol       Date:  2008-03       Impact factor: 94.444

Review 5.  Activation of gene expression by small RNA.

Authors:  Kathrin S Fröhlich; Jörg Vogel
Journal:  Curr Opin Microbiol       Date:  2009-10-31       Impact factor: 7.934

6.  Regulation by small RNAs via coupled degradation: mean-field and variational approaches.

Authors:  Thierry Platini; Tao Jia; Rahul V Kulkarni
Journal:  Phys Rev E Stat Nonlin Soft Matter Phys       Date:  2011-08-25

7.  Exosome-mediated transfer of mRNAs and microRNAs is a novel mechanism of genetic exchange between cells.

Authors:  Hadi Valadi; Karin Ekström; Apostolos Bossios; Margareta Sjöstrand; James J Lee; Jan O Lötvall
Journal:  Nat Cell Biol       Date:  2007-05-07       Impact factor: 28.824

Review 8.  Small RNAs establish gene expression thresholds.

Authors:  Erel Levine; Terence Hwa
Journal:  Curr Opin Microbiol       Date:  2008-11-18       Impact factor: 7.934

9.  Quantitative characteristics of gene regulation by small RNA.

Authors:  Erel Levine; Zhongge Zhang; Thomas Kuhlman; Terence Hwa
Journal:  PLoS Biol       Date:  2007-09       Impact factor: 8.029

10.  Small regulatory RNAs may sharpen spatial expression patterns.

Authors:  Erel Levine; Peter McHale; Herbert Levine
Journal:  PLoS Comput Biol       Date:  2007-11       Impact factor: 4.475

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