Semi-adaptive response and noise attenuation in bone morphogenetic protein signalling

Hong, Tian; Fung, Ernest S.; Zhang, Lei; Huynh, Grace; Monuki, Edwin S.; Nie, Qing

doi:10.1098/rsif.2015.0258

Cited by 3 publications

(3 citation statements)

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“…Tradeoffs in designing biological circuits have been extensively studied previously; e.g., the tradeoff between noise attenuation and speed of response, and that between maximizing information content in individual cells and cell populations [53] , [54] . However, the roles of tradeoffs in complex traits such as tissue patterning remain elusive.…”

Section: Discussionmentioning

confidence: 99%

A mathematical model for understanding synergistic regulations and paradoxical feedbacks in the shoot apical meristem

Liu

Shpak

Hong

2020

Computational and Structural Biotechnology Journal

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Section: Discussionmentioning

confidence: 99%

A mathematical model for understanding synergistic regulations and paradoxical feedbacks in the shoot apical meristem

Liu

Shpak

Hong

2020

Computational and Structural Biotechnology Journal

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“…Therefore, the gene expression fluctuations need to be considered to simulate the real cellular environments. Some noise attenuation mechanisms have been suggested in cell fate decision processes during developmental patterning [ 15 , 16 ]. Recently, Zhang et al proposed a noise induced cell fate switching mechanism to explain gene expression boundary sharpening in the zebrafish hindbrain [ 15 ].…”

Section: Introductionmentioning

confidence: 99%

Landscape reveals critical network structures for sharpening gene expression boundaries

Zhang

Nie

2018

BMC Syst Biol

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BackgroundSpatial pattern formation is a critical issue in developmental biology. Gene expression boundary sharpening has been observed from both experiments and modeling simulations. However, the mechanism to determine the sharpness of the boundary is not fully elucidated.ResultsWe investigated the boundary sharpening resulted by three biological motifs, interacting with morphogens, and uncovered their probabilistic landscapes. The landscape view, along with calculated average switching time between attractors, provides a natural explanation for the boundary sharpening behavior relying on the noise induced gene state switchings. To possess boundary sharpening potential, a gene network needs to generate an asymmetric bistable state, i.e. one of the two stable states is less stable than the other. We found that the mutual repressed self-activation model displays more robust boundary sharpening ability against parameter perturbation, compared to the mutual repression or the self-activation model. This is supported by the results of switching time calculated from the landscape, which indicate that the mutual repressed self-activation model has shortest switching time, among three models. Additionally, introducing cross gradients of morphogens provides a more stable mechanism for the boundary sharpening of gene expression, due to a two-way switching mechanism.ConclusionsOur results reveal the underlying principle for the gene expression boundary sharpening, and pave the way for the mechanistic understanding of cell fate decisions in the pattern formation processes of development.Electronic supplementary materialThe online version of this article (10.1186/s12918-018-0595-5) contains supplementary material, which is available to authorized users.

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“…[8][9][10] Noise has been shown to play critical roles in cell fate decision processes during developmental patterning. [11][12][13] However, it is unclear what roles noise play in the EMT networks, and it remains challenging to elucidate the global properties of the EMT system, such as the global stability of different states and associated dynamics under fluctuations. The potential landscape theory might provide a route for addressing these issues.…”

Section: Introductionmentioning

confidence: 99%

Quantifying the landscape and kinetic paths for epithelial–mesenchymal transition from a core circuit

Hong

Nie

2016

Phys. Chem. Chem. Phys.

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The epithelial-mesenchymal transition (EMT), as a crucial process in embryonic development and cancer metastasis, has been investigated extensively. However, how to quantify the global stability and transition dynamics for EMT under fluctuations remains to be elucidated. Starting from a core EMT genetic circuit composed of three key proteins or microRNAs (microRNA-200, ZEB and SNAIL), we uncovered the potential landscape for the EMT process. Three attractors emerge from the landscape, which correspond to epithelial, mesenchymal and partial EMT states respectively. Based on the landscape, we analyzed two important quantities of the EMT system: the barrier heights between different basins of attraction that describe the degree of difficulty for EMT or backward transition, and the mean first passage time (MFPT) that characterizes the kinetic transition rate. These quantities can be harnessed as measurements for the stability of cell types and the degree of difficulty of transitions between different cell types. We also calculated the minimum action paths (MAPs) by path integral approaches. The MAP delineates the transition processes between different cell types quantitatively. We propose two different EMT processes: a direct EMT from E to P, and a step-wise EMT going through an intermediate state, depending on different extracellular environments. The landscape and kinetic paths we acquired offer new physical and quantitative way for understanding the mechanisms of EMT processes, and indicate the possible roles for the intermediate states.

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Semi-adaptive response and noise attenuation in bone morphogenetic protein signalling

Cited by 3 publications

References 42 publications

A mathematical model for understanding synergistic regulations and paradoxical feedbacks in the shoot apical meristem

A mathematical model for understanding synergistic regulations and paradoxical feedbacks in the shoot apical meristem

Landscape reveals critical network structures for sharpening gene expression boundaries

Quantifying the landscape and kinetic paths for epithelial–mesenchymal transition from a core circuit

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