中国物理B ›› 2021, Vol. 30 ›› Issue (11): 118703-118703.doi: 10.1088/1674-1056/ac21bf

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Nonlinear signal transduction network with multistate

Han-Yu Jiang(姜寒玉) and Jun He(何军)   

  1. School of Physics and Technology, Nanjing Normal University, Nanjing 210097, China
  • 收稿日期:2021-06-01 修回日期:2021-08-02 接受日期:2021-08-27 出版日期:2021-10-13 发布日期:2021-10-27
  • 通讯作者: Jun He E-mail:junhe@njnu.edu.cn
  • 基金资助:
    Project supported by the National Natural Science Foundation of China (Grant No. 11675228) and China Postdoctoral Science Foundation (Grant No. 2015M572662XB).

Nonlinear signal transduction network with multistate

Han-Yu Jiang(姜寒玉) and Jun He(何军)   

  1. School of Physics and Technology, Nanjing Normal University, Nanjing 210097, China
  • Received:2021-06-01 Revised:2021-08-02 Accepted:2021-08-27 Online:2021-10-13 Published:2021-10-27
  • Contact: Jun He E-mail:junhe@njnu.edu.cn
  • Supported by:
    Project supported by the National Natural Science Foundation of China (Grant No. 11675228) and China Postdoctoral Science Foundation (Grant No. 2015M572662XB).

摘要: Signal transduction is an important and basic mechanism to cell life activities. The stochastic state transition of receptor induces the release of signaling molecular, which triggers the state transition of other receptors. It constructs a nonlinear sigaling network, and leads to robust switchlike properties which are critical to biological function. Network architectures and state transitions of receptor affect the performance of this biological network. In this work, we perform a study of nonlinear signaling on biological polymorphic network by analyzing network dynamics of the Ca2+-induced Ca2+ release (CICR) mechanism, where fast and slow processes are involved and the receptor has four conformational states. Three types of networks, Erdös-Rényi (ER) network, Watts-Strogatz (WS) network, and BaraBási-Albert (BA) network, are considered with different parameters. The dynamics of the biological networks exhibit different patterns at different time scales. At short time scale, the second open state is essential to reproduce the quasi-bistable regime, which emerges at a critical strength of connection for all three states involved in the fast processes and disappears at another critical point. The pattern at short time scale is not sensitive to the network architecture. At long time scale, only monostable regime is observed, and difference of network architectures affects the results more seriously. Our finding identifies features of nonlinear signaling networks with multistate that may underlie their biological function.

关键词: signal transduction, biological network with multistate, CICR, nonlinear signaling

Abstract: Signal transduction is an important and basic mechanism to cell life activities. The stochastic state transition of receptor induces the release of signaling molecular, which triggers the state transition of other receptors. It constructs a nonlinear sigaling network, and leads to robust switchlike properties which are critical to biological function. Network architectures and state transitions of receptor affect the performance of this biological network. In this work, we perform a study of nonlinear signaling on biological polymorphic network by analyzing network dynamics of the Ca2+-induced Ca2+ release (CICR) mechanism, where fast and slow processes are involved and the receptor has four conformational states. Three types of networks, Erdös-Rényi (ER) network, Watts-Strogatz (WS) network, and BaraBási-Albert (BA) network, are considered with different parameters. The dynamics of the biological networks exhibit different patterns at different time scales. At short time scale, the second open state is essential to reproduce the quasi-bistable regime, which emerges at a critical strength of connection for all three states involved in the fast processes and disappears at another critical point. The pattern at short time scale is not sensitive to the network architecture. At long time scale, only monostable regime is observed, and difference of network architectures affects the results more seriously. Our finding identifies features of nonlinear signaling networks with multistate that may underlie their biological function.

Key words: signal transduction, biological network with multistate, CICR, nonlinear signaling

中图分类号:  (Signal transduction networks)

  • 87.18.Mp
87.16.Xa (Signal transduction and intracellular signaling) 87.17.Aa (Modeling, computer simulation of cell processes)