The Role of Input Noise in Transcriptional Regulation

Tkačik, Gašper; Gregor, Thomas; Bialek, William

doi:10.1371/journal.pone.0002774

Cited by 99 publications

(127 citation statements)

References 42 publications

Supporting

Mentioning

120

Contrasting

Order By: Relevance

“…The consequences of limited TFbinding rates can be modelled by the basic steps in expressing a TF gene and the TF binding to the DNA [12][13][14][15][16][17][18][19] , illustrated in Fig. 1.…”

Section: Resultsmentioning

confidence: 99%

Transcription factor binding kinetics constrain noise suppression via negative feedback

2013

View full text Add to dashboard Cite

Negative autoregulation, where a transcription factor regulates its own expression by preventing transcription, is commonly used to suppress fluctuations in gene expression. Recent single molecule in vivo imaging has shown that it takes significant time for a transcription factor molecule to bind its chromosomal binding site. Given the slow association kinetics, transcription factor mediated feedback cannot at the same time be fast and strong. Here we show that with a limited association rate follows an optimal transcription factor binding strength where noise is maximally suppressed. At the optimal binding strength the binding site is free a fixed fraction of the time independent of the transcription factor concentration. One consequence is that high-copy number transcription factors should bind weakly to their operators, which is observed for transcription factors in Escherichia coli. The results demonstrate that a binding site's strength may be uncorrelated to its functional importance.

show abstract

Section: Resultsmentioning

confidence: 99%

Transcription factor binding kinetics constrain noise suppression via negative feedback

2013

View full text Add to dashboard Cite

show abstract

“…Receptors in our visual system can detect single photons [66], some animals can smell single molecules [15], swimming bacteria can respond to the binding and unbinding of only a limited number of molecules [12,72], and eukaryotic cells can respond to a difference in ∼10 molecules between the front and the back of the cell [80]. Recent experiments suggest that the precision of the embryonic development of the fruitfly Drosophila is close to the limit set by the available number of regulatory proteins [27,32,39,78]. This raises the question what is the fundamental limit to the precision of chemical concentration measurements.…”

Section: Introductionmentioning

confidence: 99%

Fundamental Limits to Cellular Sensing

et al. 2016

View full text Add to dashboard Cite

In recent years experiments have demonstrated that living cells can measure low chemical concentrations with high precision, and much progress has been made in understanding what sets the fundamental limit to the precision of chemical sensing. Chemical concentration measurements start with the binding of ligand molecules to receptor proteins, which is an inherently noisy process, especially at low concentrations. The signaling networks that transmit the information on the ligand concentration from the receptors into the cell have to filter this receptor input noise as much as possible. These networks, however, are also intrinsically stochastic in nature, which means that they will also add noise to the transmitted signal. In this review, we will first discuss how the diffusive transport and binding of ligand to the receptor sets the receptor correlation time, which is the timescale over which fluctuations in the state of the receptor, arising from the stochastic receptor-ligand binding, decay. We then describe how downstream signaling pathways integrate these receptor-state fluctuations, and how the number of receptors, the receptor correlation time, and the effective integration time set by the downstream network, together impose a fundamental limit on the precision of sensing. We then discuss how cells can remove the receptor input noise while simultaneously suppressing the intrinsic noise in the signaling network. We describe why this mechanism of time integration requires three classes (groups) of resources-receptors and their integration time, readout molecules, energy-and how each resource class sets a fundamental sensing limit. We also briefly discuss the scheme of maximum-likelihood estimation, the role of receptor cooperativity, and how cellular copy protocols differ from canonical copy protocols typically considered in the computational literature, explaining why cellular sensing systems can never reach the Landauer limit on the optimal trade-off between accuracy and energetic cost.B Pieter Rein ten Wolde tenwolde@amolf.nl

show abstract

“…Importantly, there are (at least) two contributions to the noise [26], and optimal networks find a balance between these. In transcriptional regulation, the most common gene regulatory mechanism, a commonly appreciated component of noise comes from the stochastic birth and death of the synthesized protein and mRNA molecules [27], which we refer to as "output noise."…”

Section: Introductionmentioning

confidence: 99%

Extending the dynamic range of transcription factor action by translational regulation

Sokolowski¹,

Walczak²,

Bialek³

et al. 2016

Phys. Rev. E

Self Cite

View full text Add to dashboard Cite

A crucial step in the regulation of gene expression is binding of transcription factor (TF) proteins to regulatory sites along the DNA. But transcription factors act at nanomolar concentrations, and noise due to random arrival of these molecules at their binding sites can severely limit the precision of regulation. Recent work on the optimization of information flow through regulatory networks indicates that the lower end of the dynamic range of concentrations is simply inaccessible, overwhelmed by the impact of this noise. Motivated by the behavior of homeodomain proteins, such as the maternal morphogen Bicoid in the fruit fly embryo, we suggest a scheme in which transcription factors also act as indirect translational regulators, binding to the mRNA of other regulatory proteins. Intuitively, each mRNA molecule acts as an independent sensor of the input concentration, and averaging over these multiple sensors reduces the noise. We analyze information flow through this scheme and identify conditions under which it outperforms direct transcriptional regulation. Our results suggest that the dual role of homeodomain proteins is not just a historical accident, but a solution to a crucial physics problem in the regulation of gene expression.

show abstract

The Role of Input Noise in Transcriptional Regulation

Cited by 99 publications

References 42 publications

Transcription factor binding kinetics constrain noise suppression via negative feedback

Transcription factor binding kinetics constrain noise suppression via negative feedback

Fundamental Limits to Cellular Sensing

Extending the dynamic range of transcription factor action by translational regulation

Contact Info

Product

Resources

About