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Originally published as Biophys J. BioFAST on September 29, 2006.
doi:10.1529/biophysj.106.086157
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Biophysical Journal 91:4350-4367 (2006)
© 2006 The Biophysical Society

Diffusion of Transcription Factors Can Drastically Enhance the Noise in Gene Expression

Jeroen S. van Zon *, Marco J. Morelli {dagger}, Sorin Tanase-Nicola {dagger} and Pieter Rein ten Wolde {dagger}

* Division of Physics and Astronomy, Vrije Universiteit, Amsterdam, The Netherlands; and {dagger} FOM Institute for Atomic and Molecular Physics, Amsterdam, The Netherlands

Correspondence: Address reprint requests to Pieter Rein ten Wolde, E-mail: tenwolde{at}amolf.nl.

We study by Green's Function Reaction Dynamics the effect of the diffusive motion of repressor molecules on the noise in mRNA and protein levels for a gene that is under the control of a repressor. We find that spatial fluctuations due to diffusion can drastically enhance the noise in gene expression. After dissociation from the operator, a repressor can rapidly rebind to the DNA. Our results show that the rebinding trajectories are so short that, on this timescale, the RNA polymerase (RNAP) cannot effectively compete with the repressor for binding to the promoter. As a result, a dissociated repressor molecule will on average rebind many times, before it eventually diffuses away. These rebindings thus lower the effective dissociation rate, and this increases the noise in gene expression. Another consequence of the timescale separation between repressor rebinding and RNAP association is that the effect of spatial fluctuations can be described by a well-stirred, zero-dimensional, model by renormalizing the reaction rates for repressor-DNA (un) binding. Our results thus support the use of well-stirred, zero-dimensional models for describing noise in gene expression. We also show that for a fixed repressor strength, the noise due to diffusion can be minimized by increasing the number of repressors or by decreasing the rate of the open complex formation. Lastly, our results emphasize that power spectra are a highly useful tool for studying the propagation of noise through the different stages of gene expression.




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