Tunable Signal Processing Through Modular Control of Transcription Factor Translocation
Harvard University Faculty of Arts and Sciences Center for Systems Biology, Cambridge, MA 02138, USA. Science
(Impact Factor: 33.61).
01/2013; 339(6118):460-4. DOI: 10.1126/science.1227299
Signaling pathways can induce different dynamics of transcription factor (TF) activation. We explored how TFs process signaling
inputs to generate diverse dynamic responses. The budding yeast general stress–responsive TF Msn2 acted as a tunable signal
processor that could track, filter, or integrate signals in an input-dependent manner. This tunable signal processing appears
to originate from dual regulation of both nuclear import and export by phosphorylation, as mutants with one form of regulation
sustained only one signal-processing function. Versatile signal processing by Msn2 is crucial for generating distinct dynamic
responses to different natural stresses. Our findings reveal how complex signal-processing functions are integrated into a
single molecule and provide a guide for the design of TFs with "programmable" signal-processing functions.
Available from: Anders Sejr Hansen
- "To investigate the relationship between the architecture of a promoter and how it decodes TF dynamics, we study the SIP18 promoter, which is activated by the budding yeast TF, Msn2. During stress exposure, Msn2 encodes information about stress identity in its nuclear translocation dynamics—for example, Msn2 exhibits brief nuclear pulses with dose-dependent frequency under glucose limitation but a sustained pulse with dose-dependent amplitude under oxidative stress (Hao et al., 2013; Hao and O'Shea, 2012; Petrenko et al., 2013). Msn2 target genes can differentially decode Msn2 dynamics such that stress-relevant target genes are predominantly expressed under the relevant stress (Hansen and O'Shea, 2013, 2015; Hao and O'Shea, 2012). "
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ABSTRACT: Although the relationship between DNA cis-regulatory sequences and gene expression has been extensively studied at steady state, how cis-regulatory sequences affect the dynamics of gene induction is not known. The dynamics of gene induction can be described by the promoter activation timescale (AcTime) and amplitude threshold (AmpThr). Combining high-throughput microfluidics with quantitative time-lapse microscopy, we control the activation dynamics of the budding yeast transcription factor, Msn2, and reveal how cis-regulatory motifs in 20 promoter variants of the Msn2-target-gene SIP18 affect AcTime and AmpThr. By modulating Msn2 binding sites, we can decouple AmpThr from AcTime and switch the SIP18 promoter class from high AmpThr and slow AcTime to low AmpThr and either fast or slow AcTime. We present a model that quantitatively explains gene-induction dynamics on the basis of the Msn2-binding-site number, TATA box location, and promoter nucleosome organization. Overall, we elucidate the cis-regulatory logic underlying promoter decoding of TF dynamics.
Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.
Available from: Matthew M Crane
- "A single transcription factor (Msn2p) is involved in the activation of hundreds of different stress response genes–. Msn2p has unusual dynamics, with alternative modes of nuclear shuttling that lead to activation of different subsets of genes –. Responding appropriately to stress involves prima facie careful regulation. A cell that fails to sense a significant and increasing stress could fail to respond and thus be removed from the gene pool. "
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ABSTRACT: Recognition of the importance of cell-to-cell variability in cellular decision-making and a growing interest in stochastic modeling of cellular processes has led to an increased demand for high density, reproducible, single-cell measurements in time-varying surroundings. We present ALCATRAS (A Long-term Culturing And TRApping System), a microfluidic device that can quantitatively monitor up to 1000 cells of budding yeast in a well-defined and controlled environment. Daughter cells are removed by fluid flow to avoid crowding allowing experiments to run for over 60 hours, and the extracellular media may be changed repeatedly and in seconds. We illustrate use of the device by measuring ageing through replicative life span curves, following the dynamics of the cell cycle, and examining history-dependent behaviour in the general stress response.
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