Reliable cell cycle commitment in budding yeast is ensured by signal integration

Liu, Xili; Wang, Xin; Yang, Xiaojing; Liu, Sen; Jiang, Lingli; Qu, Youxing; Hu, Lufeng; Ouyang, Qi; Tang, Chao

doi:10.7554/elife.03977

Cited by 75 publications

(108 citation statements)

References 68 publications

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“…In either case, Cln3-Cdk complexes, whose number is likely proportional to cell size, would be titrated against a constant DNA yardstick. Consistent with this model, a recent study constitutively expressing Cln3 at different levels showed that the concentration of Cln3 inversely correlated with G 1 length (Liu et al 2015). However, the implications of these Cln3-titration conjectures remain largely untested.…”

Section: Titration Of Cyclins In Budding Yeastsupporting

confidence: 52%

Cell-Size Control

Amodeo

Skotheim

2015

Cold Spring Harb Perspect Biol

158

159

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Cells of a given type maintain a characteristic cell size to function efficiently in their ecological or organismal context. They achieve this through the regulation of growth rates or by actively sensing size and coupling this signal to cell division. We focus this review on potential size-sensing mechanisms, including geometric, external cue, and titration mechanisms. Mechanisms that titrate proteins against DNA are of particular interest because they are consistent with the robust correlation of DNA content and cell size. We review the literature, which suggests that titration mechanisms may underlie cell-size sensing in Xenopus embryos, budding yeast, and Escherichia coli, whereas alternative mechanisms may function in fission yeast.

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Section: Titration Of Cyclins In Budding Yeastsupporting

confidence: 52%

Cell-Size Control

Amodeo

Skotheim

2015

Cold Spring Harb Perspect Biol

158

159

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“…It has been recognized that feedback loops play significant roles in a variety of biological processes, such as calcium signaling (Berridge, 2001; Lewis, 2001), p53 regulation (Harris and Levine, 2005), galactose regulation (Acar et al, 2005), cell cycle (Morgan, 2006; Yang et al, 2013; Liu et al, 2015), and cell fate decision in budding yeast (Li et al, 2014, 2015). Some studies suggested that negative feedbacks typically attenuated noise and positive feedbacks tended to amplify noise (Becskei and Serrano, 2000; Austin et al, 2006; Alon, 2007); however, there were other studies revealing that positive feedbacks could attenuate noises and there were no strong correlations between the sign of feedbacks (negative or positive) and the noise attenuation properties (Hooshangi and Weiss, 2006; Hornung and Barkai, 2008).…”

Section: Introductionmentioning

confidence: 99%

Noise Decomposition Principle in a Coherent Feed-Forward Transcriptional Regulatory Loop

et al. 2016

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Coherent feed-forward loops exist extensively in realistic biological regulatory systems, and are common signaling motifs. Here, we study the characteristics and the propagation mechanism of the output noise in a coherent feed-forward transcriptional regulatory loop that can be divided into a main road and branch. Using the linear noise approximation, we derive analytical formulae for the total noise of the full loop, the noise of the branch, and the noise of the main road, which are verified by the Gillespie algorithm. Importantly, we find that (i) compared with the branch motif or the main road motif, the full motif can effectively attenuate the output noise level; (ii) there is a transition point of system state such that the noise of the main road is dominated when the underlying system is below this point, whereas the noise of the branch is dominated when the system is beyond the point. The entire analysis reveals the mechanism of how the noise is generated and propagated in a simple yet representative signaling module.

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“…We therefore measured Cln3 concentration during a pheromone-induced cell cycle arrest. Since the concentration of wild-type Cln3 cannot be measured using fluorescence microscopy due to its rapid and constitutive degradation (Tyers et al, 1992), we examined a mutant strain expressing a stabilized, more abundant, but less active Cln3 protein previously characterized and used to examine G1/S cell cycle regulation ( mCitrine-CLN3-11A ) (Bhaduri and Pryciak, 2011; Liu et al, 2015; Schmoller et al, 2015). In contrast to freely cycling cells, in which Cln3-11A was measured to be constant (Schmoller et al, 2015), Cln3-11A concentration gradually increased during pheromone-induced arrest on a similar time scale as cell growth (Figure 3C,D).…”

Section: Resultsmentioning

confidence: 99%

Switch-like Transitions Insulate Network Motifs to Modularize Biological Networks

Atay

Doncic

2016

Cell Systems

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Cellular decisions are made by complex networks that are difficult to analyze. While it is common to analyze smaller sub-networks known as network motifs, it is unclear whether this is valid because these motifs are embedded in complex larger networks. Here, we address the general question of modularity by examining the S. cerevisiae pheromone response. We demonstrate that the feedforward motif controlling the cell cycle inhibitor Far1 is insulated from cell cycle dynamics by the positive feedback switch that drives reentry to the cell cycle. Before cells switch on positive feedback, the feedforward motif model predicts the behavior of the larger network. Conversely, after the switch, the feedforward motif is dismantled and has no discernable effect on the cell cycle. When insulation is broken, the feedforward motif no longer predicts network behavior. This work illustrates how, despite the interconnectivity of networks, the activity of motifs can be insulated by switches that generate well-defined cellular states.

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Reliable cell cycle commitment in budding yeast is ensured by signal integration

Cited by 75 publications

References 68 publications

Cell-Size Control

Cell-Size Control

Noise Decomposition Principle in a Coherent Feed-Forward Transcriptional Regulatory Loop

Switch-like Transitions Insulate Network Motifs to Modularize Biological Networks

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