Mapping parameter spaces of biological switches.

Mapping parameter spaces of biological switches.
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DOI:
10.1371/journal.pcbi.1008711
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发表时间:
2021-03
影响因子:
4.3
通讯作者:
Mischaikow K
Mischaikow K
中科院分区:
生物学2区
文献类型:
--
作者:
Diegmiller R;Zhang L;Gameiro M;Barr J;Imran Alsous J;Schedl P;Shvartsman SY;Mischaikow K

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自从1961年Monod和Jacob的开创性论文发表以来,生物分子电路的数学模型指导了我们对细胞调控的理解。基于模型的探索任何给定电路的功能能力需要系统地映射模型参数的多维空间。尽管计算动力系统方法取得了重大进展,但这种分析仍然是一项艰巨的任务。在这里,我们使用一个非线性常微分方程系统来模拟果蝇的卵母细胞选择,这是一个依赖于卵母细胞特异性因子的自调节定位的健壮的对称性破坏事件。通过应用一种实现符号计算和拓扑方法的算法方法,我们列举了当非线性调节相互作用成为离散开关时,在极限下稳定稳态的所有相位肖像。利用这种初始精确划分并进一步使用数值探索,我们定位了在非线性不是无限尖锐的纯不对称稳态下密集的参数区域,从而能够系统地识别与稳健的卵母细胞选择相对应的参数区域。这个框架可以推广到映射全参数空间在一个广泛的类模型涉及生物开关。识别生物分子开关模型中不同性质的机制对于理解复杂生物过程的动力学至关重要,包括细胞和细胞网络中的对称性破坏。我们展示了拓扑方法、符号计算和数值模拟如何结合起来,在果蝇卵母细胞规范的数学模型中系统地映射对称破碎状态,果蝇是动物卵子发生的主要实验系统。我们的算法框架揭示了与强大的卵母细胞规格相对应的参数域的全局连通性,并能够在大类生物分子开关中通过多维参数空间进行系统导航。
Since the seminal 1961 paper of Monod and Jacob, mathematical models of biomolecular circuits have guided our understanding of cell regulation. Model-based exploration of the functional capabilities of any given circuit requires systematic mapping of multidimensional spaces of model parameters. Despite significant advances in computational dynamical systems approaches, this analysis remains a nontrivial task. Here, we use a nonlinear system of ordinary differential equations to model oocyte selection in Drosophila, a robust symmetry-breaking event that relies on autoregulatory localization of oocyte-specification factors. By applying an algorithmic approach that implements symbolic computation and topological methods, we enumerate all phase portraits of stable steady states in the limit when nonlinear regulatory interactions become discrete switches. Leveraging this initial exact partitioning and further using numerical exploration, we locate parameter regions that are dense in purely asymmetric steady states when the nonlinearities are not infinitely sharp, enabling systematic identification of parameter regions that correspond to robust oocyte selection. This framework can be generalized to map the full parameter spaces in a broad class of models involving biological switches. Identification of qualitatively different regimes in models of biomolecular switches is essential for understanding dynamics of complex biological processes, including symmetry breaking in cells and cell networks. We demonstrate how topological methods, symbolic computation, and numerical simulations can be combined for systematic mapping of symmetry-broken states in a mathematical model of oocyte specification in Drosophila, a leading experimental system of animal oogenesis. Our algorithmic framework reveals global connectedness of parameter domains corresponding to robust oocyte specification and enables systematic navigation through multidimensional parameter spaces in a large class of biomolecular switches.
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期刊: Physica D. Nonlinear phenomena
影响因子: --
作者:
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