A Systems-Biology Analysis of Feedback Inhibition in the Sho1 Osmotic-Stress-Response Pathway

Hao, Nan; Behar, Marcelo; Parnell, Stephen C.; Torres, Matthew P.; Borchers, Christoph H.; Elston, Timothy C.; Dohlman, Henrik G.

doi:10.1016/j.cub.2007.02.044

Cited by 95 publications

(107 citation statements)

References 24 publications

(37 reference statements)

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“…To decide what osmotic stress to apply at a given time, we used an elementary model of pSTL1 induction. Many models have been proposed for the hyperosmotic stress response in yeast (10,(26)(27)(28)(29)(30). We used a generic model of gene expression written as a two-variable delay differential equation system, where the first variable denotes the recent osmotic stress felt by the cell and the second variable is the protein fluorescence level (Fig.…”

mentioning

confidence: 99%

Long-term model predictive control of gene expression at the population and single-cell levels

Uhlendorf

Miermont

Delaveau

et al. 2012

Proc. Natl. Acad. Sci. U.S.A.

219

237

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Gene expression plays a central role in the orchestration of cellular processes. The use of inducible promoters to change the expression level of a gene from its physiological level has significantly contributed to the understanding of the functioning of regulatory networks. However, from a quantitative point of view, their use is limited to short-term, population-scale studies to average out cell-to-cell variability and gene expression noise and limit the nonpredictable effects of internal feedback loops that may antagonize the inducer action. Here, we show that, by implementing an external feedback loop, one can tightly control the expression of a gene over many cell generations with quantitative accuracy. To reach this goal, we developed a platform for real-time, closed-loop control of gene expression in yeast that integrates microscopy for monitoring gene expression at the cell level, microfluidics to manipulate the cells' environment, and original software for automated imaging, quantification, and model predictive control. By using an endogenous osmostress responsive promoter and playing with the osmolarity of the cells environment, we show that long-term control can, indeed, be achieved for both time-constant and time-varying target profiles at the population and even the single-cell levels. Importantly, we provide evidence that real-time control can dynamically limit the effects of gene expression stochasticity. We anticipate that our method will be useful to quantitatively probe the dynamic properties of cellular processes and drive complex, synthetically engineered networks.model based control | computational biology | high osmolarity glycerol pathway | quantitative systems biology U nderstanding the information processing abilities of biological systems is a central problem for systems and synthetic biology (1-6). The properties of a living system are often inferred from the observation of its response to static perturbations. Timevarying perturbations have the potential to be much more informative regarding the dynamics of cellular functions (7-12). Currently, it is not possible to precisely perturb protein levels in an analogous manner, even though this perturbation would be instrumental in our understanding of gene regulatory networks. Indeed, despite the development of novel regulatory systems, including various RNA-based solutions (13), transcriptional control by means of inducible promoters is still the preferred method for manipulating protein levels (14, 15). Unfortunately, inducible promoters have several generic limitations. First, there is a significant delay between gene expression activation and effective protein synthesis. Second, many cellular processes can interfere with gene expression through internal feedback loops whose effects are hard to predict. Third, the process of gene expression shows significant levels of noise (16)(17)(18). Given these limitations, novel experimental strategies are required to gain quantitative, real-time control of gene expression in vivo.Here, we see the...

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mentioning

confidence: 99%

Long-term model predictive control of gene expression at the population and single-cell levels

Uhlendorf

Miermont

Delaveau

et al. 2012

Proc. Natl. Acad. Sci. U.S.A.

219

237

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“…A series of simple mathematical models were fit to the data, and these models suggested the existence of a key phosphorylation event early in the pathway. Further experimental analysis revealed that Hog1 phosphorylates Sho1, and also established that Sho1 exists normally as a homooligomer; moreover, mutation of the phosphorylation site leads to diminished Sho1 oligomerization and diminished signaling (Hao et al, 2007). These observations led to the model of pathway adaptation shown in Figure 2a.…”

Section: Modeling Mechanisms Of Pathway Regulationmentioning

confidence: 88%

“…Such a delay would allow the cell to adapt to strong signals yet remain sensitive enough to detect weak signals. Thus, as multicomponent signaling cascades are well known to confer signal amplification, we postulate that multiple components also allow cells to respond appropriately to a wide range of signal strengths without the need for amplification (Hao et al, 2007).…”

Section: Modeling Mechanisms Of Pathway Regulationmentioning

confidence: 99%

Systems biology analysis of G protein and MAP kinase signaling in yeast

et al. 2007

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neurotransmitter reuptake or by blocking the inactivation of intracellular second messengers. These drugs have revolutionized the treatment of human disease. However, the complexity of G protein signaling mechanisms has significantly hampered our ability to identify additional new drug targets. Moreover, today's molecular pharmacologists are accustomed to working on narrowly focused problems centered on a single protein or enzymatic process. Here we describe emerging efforts in yeast aimed at identifying proteins and processes that modulate the function of receptors, G proteins and MAP kinase effectors. The scope of these efforts is far more systematic, comprehensive and quantitative than anything attempted previously, and includes integrated approaches in genetics, proteomics and computational biology.

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“…Cell Extracts and Immunoblotting-Protein extracts were produced by glass bead lysis in trichloroacetic acid as described previously (38). Protein extracts were resolved by SDS-PAGE, transferred onto nitrocellulose, and subjected to immunoblotting.…”

Section: Methodsmentioning

confidence: 99%

Dynamic Ubiquitination of the Mitogen-activated Protein Kinase Kinase (MAPKK) Ste7 Determines Mitogen-activated Protein Kinase (MAPK) Specificity

Hurst

Dohlman

2013

Journal of Biological Chemistry

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Background: Ubiquitination is a post-translational modification that regulates protein behavior. Results: Pheromone stimulation induces dynamic ubiquitination of the MAPKK Ste7; disruption of this modification leads to altered MAPK signal specificity. Conclusion: Dynamic ubiquitination is required to maintain the strength and fidelity of the pheromone response. Significance: This study identifies a novel regulatory mechanism in MAPK cascades, a signaling module that is central to human physiology and disease.

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A Systems-Biology Analysis of Feedback Inhibition in the Sho1 Osmotic-Stress-Response Pathway

Abstract: These findings reveal a novel phosphorylation-dependent feedback loop leading to diminished cellular responses to an osmotic-stress stimulus.

Cited by 95 publications

References 24 publications

Long-term model predictive control of gene expression at the population and single-cell levels

Long-term model predictive control of gene expression at the population and single-cell levels

Systems biology analysis of G protein and MAP kinase signaling in yeast

Dynamic Ubiquitination of the Mitogen-activated Protein Kinase Kinase (MAPKK) Ste7 Determines Mitogen-activated Protein Kinase (MAPK) Specificity

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