Literature DB >> 19279212

Negative autoregulation linearizes the dose-response and suppresses the heterogeneity of gene expression.

Dmitry Nevozhay1, Rhys M Adams, Kevin F Murphy, Kresimir Josic, Gábor Balázsi.   

Abstract

Although several recent studies have focused on gene autoregulation, the effects of negative feedback (NF) on gene expression are not fully understood. Our purpose here was to determine how the strength of NF regulation affects the characteristics of gene expression in yeast cells harboring chromosomally integrated transcriptional cascades that consist of the yEGFP reporter controlled by (i) the constitutively expressed tetracycline repressor TetR or (ii) TetR repressing its own expression. Reporter gene expression in the cascade without feedback showed a steep (sigmoidal) dose-response and a wide, nearly bimodal yEGFP distribution, giving rise to a noise peak at intermediate levels of induction. We developed computational models that reproduced the steep dose-response and the noise peak and predicted that negative autoregulation changes reporter expression from bimodal to unimodal and transforms the dose-response from sigmoidal to linear. Prompted by these predictions, we constructed a "linearizer" circuit by adding TetR autoregulation to our original cascade and observed a massive (7-fold) reduction of noise at intermediate induction and linearization of dose-response before saturation. A simple mathematical argument explained these findings and indicated that linearization is highly robust to parameter variations. These findings have important implications for gene expression control in eukaryotic cells, including the design of synthetic expression systems.

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Year:  2009        PMID: 19279212      PMCID: PMC2654390          DOI: 10.1073/pnas.0809901106

Source DB:  PubMed          Journal:  Proc Natl Acad Sci U S A        ISSN: 0027-8424            Impact factor:   11.205


  45 in total

Review 1.  Noise in gene expression: origins, consequences, and control.

Authors:  Jonathan M Raser; Erin K O'Shea
Journal:  Science       Date:  2005-09-23       Impact factor: 47.728

2.  Regulated cell-to-cell variation in a cell-fate decision system.

Authors:  Alejandro Colman-Lerner; Andrew Gordon; Eduard Serra; Tina Chin; Orna Resnekov; Drew Endy; C Gustavo Pesce; Roger Brent
Journal:  Nature       Date:  2005-09-18       Impact factor: 49.962

Review 3.  Stochasticity in gene expression: from theories to phenotypes.

Authors:  Mads Kaern; Timothy C Elston; William J Blake; James J Collins
Journal:  Nat Rev Genet       Date:  2005-06       Impact factor: 53.242

4.  From fluctuations to phenotypes: the physiology of noise.

Authors:  Michael S Samoilov; Gavin Price; Adam P Arkin
Journal:  Sci STKE       Date:  2006-12-19

5.  Phenotypic consequences of promoter-mediated transcriptional noise.

Authors:  William J Blake; Gábor Balázsi; Michael A Kohanski; Farren J Isaacs; Kevin F Murphy; Yina Kuang; Charles R Cantor; David R Walt; James J Collins
Journal:  Mol Cell       Date:  2006-12-28       Impact factor: 17.970

6.  A bottom-up approach to gene regulation.

Authors:  Nicholas J Guido; Xiao Wang; David Adalsteinsson; David McMillen; Jeff Hasty; Charles R Cantor; Timothy C Elston; J J Collins
Journal:  Nature       Date:  2006-02-16       Impact factor: 49.962

7.  Noise in gene expression determines cell fate in Bacillus subtilis.

Authors:  Hédia Maamar; Arjun Raj; David Dubnau
Journal:  Science       Date:  2007-06-14       Impact factor: 47.728

8.  Gene network shaping of inherent noise spectra.

Authors:  D W Austin; M S Allen; J M McCollum; R D Dar; J R Wilgus; G S Sayler; N F Samatova; C D Cox; M L Simpson
Journal:  Nature       Date:  2006-02-02       Impact factor: 49.962

9.  Combinatorial promoter design for engineering noisy gene expression.

Authors:  Kevin F Murphy; Gábor Balázsi; James J Collins
Journal:  Proc Natl Acad Sci U S A       Date:  2007-07-24       Impact factor: 11.205

10.  Accurate prediction of gene feedback circuit behavior from component properties.

Authors:  Nitzan Rosenfeld; Jonathan W Young; Uri Alon; Peter S Swain; Michael B Elowitz
Journal:  Mol Syst Biol       Date:  2007-11-13       Impact factor: 11.429

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  135 in total

1.  Systems biology: The cost of feedback control.

Authors:  Li Sun; Attila Becskei
Journal:  Nature       Date:  2010-09-09       Impact factor: 49.962

2.  Design of regulation and dynamics in simple biochemical pathways.

Authors:  Ram Rup Sarkar; R Maithreye; Somdatta Sinha
Journal:  J Math Biol       Date:  2010-10-19       Impact factor: 2.259

3.  Bimodal gene expression in noncooperative regulatory systems.

Authors:  Anna Ochab-Marcinek; Marcin Tabaka
Journal:  Proc Natl Acad Sci U S A       Date:  2010-12-06       Impact factor: 11.205

Review 4.  Network inference and network response identification: moving genome-scale data to the next level of biological discovery.

Authors:  Diogo F T Veiga; Bhaskar Dutta; Gábor Balázsi
Journal:  Mol Biosyst       Date:  2009-12-11

5.  Engineering of regulated stochastic cell fate determination.

Authors:  Min Wu; Ri-Qi Su; Xiaohui Li; Tom Ellis; Ying-Cheng Lai; Xiao Wang
Journal:  Proc Natl Acad Sci U S A       Date:  2013-06-10       Impact factor: 11.205

6.  Synthetic negative feedback circuits using engineered small RNAs.

Authors:  Ciarán L Kelly; Andreas W K Harris; Harrison Steel; Edward J Hancock; John T Heap; Antonis Papachristodoulou
Journal:  Nucleic Acids Res       Date:  2018-10-12       Impact factor: 16.971

7.  Synthetic biosensors for precise gene control and real-time monitoring of metabolites.

Authors:  Jameson K Rogers; Christopher D Guzman; Noah D Taylor; Srivatsan Raman; Kelley Anderson; George M Church
Journal:  Nucleic Acids Res       Date:  2015-07-07       Impact factor: 16.971

8.  Protein-level fluctuation correlation at the microcolony level and its application to the Vibrio harveyi quorum-sensing circuit.

Authors:  Yufang Wang; Kimberly C Tu; N P Ong; Bonnie L Bassler; Ned S Wingreen
Journal:  Biophys J       Date:  2011-06-22       Impact factor: 4.033

9.  Gene regulation and noise reduction by coupling of stochastic processes.

Authors:  Alexandre F Ramos; José Eduardo M Hornos; John Reinitz
Journal:  Phys Rev E Stat Nonlin Soft Matter Phys       Date:  2015-02-26

10.  Competitive inhibition can linearize dose-response and generate a linear rectifier.

Authors:  Yonatan Savir; Benjamin P Tu; Michael Springer
Journal:  Cell Syst       Date:  2015-09-23       Impact factor: 10.304

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