Tuning and controlling gene expression noise in synthetic gene networks

Kevin F. Murphy, Rhys M. Adams, Xiao Wang, Gábor Balázsi, James J. Collins

Research output: Contribution to journalArticlepeer-review

116 Scopus citations


Synthetic gene networks can be used to control gene expression and cellular phenotypes in a variety of applications. In many instances, however, such networks can behave unreliably due to gene expression noise. Accordingly, there is a need to develop systematic means to tune gene expression noise, so that it can be suppressed in some cases and harnessed in others, e.g. in cellular differentiation to create population-wide heterogeneity. Here, we present a method for controlling noise in synthetic eukaryotic gene expression systems, utilizing reduction of noise levels by TATA box mutations and noise propagation in transcriptional cascades. Specifically, we introduce TATA box mutations into promoters driving TetR expression and show that these mutations can be used to effectively tune the noise of a target gene while decoupling it from the mean, with negligible effects on the dynamic range and basal expression. We apply mathematical and computational modeling to explain the experimentally observed effects of TATA box mutations. This work, which highlights some important aspects of noise propagation in gene regulatory cascades, has practical implications for implementing gene expression control in synthetic gene networks.

Original languageEnglish (US)
Article numbergkq091
Pages (from-to)2712-2726
Number of pages15
JournalNucleic acids research
Issue number8
StatePublished - Mar 8 2010
Externally publishedYes

ASJC Scopus subject areas

  • Genetics


Dive into the research topics of 'Tuning and controlling gene expression noise in synthetic gene networks'. Together they form a unique fingerprint.

Cite this