Molecular-memory-driven phenotypic switching in a genetic toggle switch without cooperative binding

Qiu, Baohua; Zhang, Jiajun

doi:10.1103/physreve.101.022409

Cited by 5 publications

(3 citation statements)

References 48 publications

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“…Previous studies on bimodality mostly involve the intrinsic or extrinsic regulations, e.g., noise and feedback, of the underlying systems. [12][13][14][15][16][17][18][19][20][21][22][23] Bimodality characterized by mixed distributions also has been observed in these gene models involving promoter leakage, 82 and multiple exits of transcription. 47 However, it is unclear that bimodality can occur without these conditions.…”

Section: ⅴ Conclusion and Discussionmentioning

confidence: 69%

“…17 The second viewpoint is noise-induced bimodality, i.e., the stochastic fluctuation can induce a bimodal response that cannot occur in the deterministic case. 5–7, 18, 19 For example, using a synthetic system in budding yeast, To et al . found that positive feedback involving a promoter with multiple transcription factor (TF) binding sites can induce bimodality without cooperative binding of the TFs.…”

Section: Introductionmentioning

confidence: 99%

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Silent transcription intervals and translational bursting lead to diverse phenotypic switching

Yang

Luo

Zhang

et al. 2022

Preprint

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Bimodality of gene expression, as a mechanism generating phenotypic diversity, enhances the survival of cells in a fluctuating environment. Growing experimental evidence suggests that silent transcription intervals and translational bursting play important roles in regulating phenotypic switching. Characterizing these kinetics is challenging. Here, we develop an interpretable and tractable model, the generalized telegraph model (GTM), which considers silent transcription intervals described by a general waiting-time distribution and translational bursting characterized by an arbitrary distribution. Using methods of queuing theory, we derive analytical expressions of all moment statistics and distribution of protein counts. We show that non-exponential inactive times and translational bursting can lead to two nonzero bimodalities that cannot be captured in the classical telegraph model (CTM). In addition, we find that both silent-intervals noise and translational burst-size noise can amplify gene expression noise, as well as induce diverse dynamic expressions. Our results not only provide an alternative mechanism for phenotypic switching driven by silent transcription intervals and translational bursting, but also can be used to infer complex promoter structures based on experimental data.

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Section: ⅴ Conclusion and Discussionmentioning

confidence: 69%

Section: Introductionmentioning

confidence: 99%

Silent transcription intervals and translational bursting lead to diverse phenotypic switching

Yang

Luo

Zhang

et al. 2022

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…A little more than five decades ago, Waddington introduced the metaphor to view cellular differentiation into distinct lineages and cell types as a sequence of transitions among basins in a landscape, wherein basins indicate stable phenotypes (Waddington and Kacser, 1957). The appeal of this metaphor to intuition has inspired efforts of theoretical formulation at the molecular level by studying genetic networks formed by transcription factors (TF) (Sasai and Wolynes, 2003;Hornos et al, 2005;Kaern et al, 2005;Walczak et al, 2005a,b;Xu and Tao, 2006;Goldberg et al, 2007;Kim and Wang, 2007;Shahrezaei and Swain, 2008;Cao et al, 2010;Venegas-Ortiz and Evans, 2011;Wang et al, 2011Wang et al, , 2014Zhang et al, 2013;Zhang and Wolynes, 2014;Lv et al, 2015;Chen et al, 2016;Qiu et al, 2020). These studies highlighted the importance of gene expression noise in driving the transition among steady states.…”

Section: Introductionmentioning

confidence: 99%

Quantifying the Stability of Coupled Genetic and Epigenetic Switches With Variational Methods

Sood

Zhang

2021

Front. Genet.

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The Waddington landscape provides an intuitive metaphor to view development as a ball rolling down the hill, with distinct phenotypes as basins and differentiation pathways as valleys. Since, at a molecular level, cell differentiation arises from interactions among the genes, a mathematical definition for the Waddington landscape can, in principle, be obtained by studying the gene regulatory networks. For eukaryotes, gene regulation is inextricably and intimately linked to histone modifications. However, the impact of such modifications on both landscape topography and stability of attractor states is not fully understood. In this work, we introduced a minimal kinetic model for gene regulation that combines the impact of both histone modifications and transcription factors. We further developed an approximation scheme based on variational principles to solve the corresponding master equation in a second quantized framework. By analyzing the steady-state solutions at various parameter regimes, we found that histone modification kinetics can significantly alter the behavior of a genetic network, resulting in qualitative changes in gene expression profiles. The emerging epigenetic landscape captures the delicate interplay between transcription factors and histone modifications in driving cell-fate decisions.

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Optimal switching paths of a non-Markovian model of gene bursty expression

Yin

Shang-tao

et al. 2022

Chinese Journal of Physics

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Molecular-memory-driven phenotypic switching in a genetic toggle switch without cooperative binding

Cited by 5 publications

References 48 publications

Silent transcription intervals and translational bursting lead to diverse phenotypic switching

Silent transcription intervals and translational bursting lead to diverse phenotypic switching

Quantifying the Stability of Coupled Genetic and Epigenetic Switches With Variational Methods

Optimal switching paths of a non-Markovian model of gene bursty expression

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