The linear interplay of intrinsic and extrinsic noises ensures a high accuracy of cell fate selection in budding yeast

Abstract

To gain insights into the mechanisms of cell fate decision in a noisy environment, the effects of intrinsic and extrinsic noises on cell fate are explored at the single cell level. Specifically, we theoretically define the impulse of Cln1/2 as an indication of cell fates. The strong dependence between the impulse of Cln1/2 and cell fates is exhibited. Based on the simulation results, we illustrate that increasing intrinsic fluctuations causes the parallel shift of the separation ratio of Whi5P but that increasing extrinsic fluctuations leads to the mixture of different cell fates. Our quantitative study also suggests that the strengths of intrinsic and extrinsic noises around an approximate linear model can ensure a high accuracy of cell fate selection. Furthermore, this study demonstrates that the selection of cell fates is an entropy-decreasing process. In addition, we reveal that cell fates are significantly correlated with the range of entropy decreases.

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

“…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).…”

Mathematical modeling for intracellular transport and binding of HIV-1 Gag proteins

“…This topic is currently under investigation and 308 will be reported in our future work. In addition, to verify the stability 309 of HIV-1 Gag assembly, a stochastic model is expected in our next 310 research [24]. 311 This study focuses on the time period from the initial production 312 of gag protein monomers in the cytoplasm to the initial appearance of 313 τ K 1 + τ ,…”

“…22 Other work on quantitative models for intercellular transport were 23 proposed in [10,11]. However, those models mostly focus on the traf- 24 ficking of a single virus. In [12], all of the species of gag proteins, 25 including monomers, dimers, and trimers, were treated as quasi-26 monomers with equivalent concentrations.…”

Negative feedback contributes to the stochastic expression of the interferon-β gene in virus-triggered type I interferon signaling pathways

“…Some experimental results showed that the cell-to-cell heterogeneity was a pervasive feature of the IFN system and can arise not only from the cell's intrinsic stochasticity occurring in the biochemical reactions but also from extrinsic factors such as differences in cell-cycle stage or cellular environment, which can be reflected in the kinetic parameters [54][55][56]. Here, we assumed that the intrinsic noise is determined by the fluctuations generated by the system size, and the extrinsic noise is defined as the fluctuations and variability in the kinetic parameters, particularly the positive feedback strength k 4 and negative feedback strength k 3 associated with the autocrine and paracrine of IFNβ.…”