Azzoni Caterina, Jüttner Rene, Sporbert Anje, Gotthardt Michael, Llewelyn Roderick H, Falcke Martin
Max Delbrück Center for Molecular Medicine (MDC), Berlin, Germany.
Faculty of Life Sciences, Humboldt-Universität zu Berlin, Berlin, Germany.
PLoS Comput Biol. 2025 Aug 22;21(8):e1013322. doi: 10.1371/journal.pcbi.1013322. eCollection 2025 Aug.
Mathematical theory that accounts for the stochastic character of spike sequences of IP3-induced Ca2+ signalling calculates the probability distributions of the features of the [Ca2+]i time course, their moments and correlations. Including slow feedback from [Ca2+]i to components of the pathway poses a challenge to stochastic modelling. Here, we present a stochastic model that takes this feedback into account, allows for a non-linear dependency of the open probability of the Inositol 1,4,5-trisphosphate receptor channel (IP3R) on the feedback variable and the inclusion of more than one feedback with different relaxation time scales. We use this novel modelling approach to describe the effect of ER depletion by non-linear rate expressions for Ca2+-induced Ca2+ release (CICR) and the measured non-linear IP3-dependency of the open probability as part of the dynamic feedback. Our theory can calculate spike amplitude distributions, correlation coefficients (Cc) of interspike intervals (ISIs) and amplitudes, simulate ISI distributions and calculate their moments. We apply it to experiments with HEK293 cells. We find very good agreement between theoretical ISI distributions and their moments with experimental results. Many measured Ccs show positive values in accordance with the ideas formulated by our theory. Surprisingly, most ISI-amplitude correlations are weak despite the decay of negative feedback during the ISI, which affects spike probability. We even find negative values of Ccs, which indicate feedback that decreases the open probability of IP3R with increasing ISI. The components of the pathway causing this anticorrelation have not yet been identified. Our data suggest that they involve components that are subject to cell variability.
解释IP3诱导的Ca2+信号尖峰序列随机特性的数学理论计算了[Ca2+]i时间进程特征的概率分布、它们的矩和相关性。将[Ca2+]i对信号通路组分的慢反馈纳入考虑,对随机建模提出了挑战。在此,我们提出一种随机模型,该模型考虑了这种反馈,允许肌醇1,4,5-三磷酸受体通道(IP3R)的开放概率对反馈变量存在非线性依赖性,并纳入了具有不同弛豫时间尺度的多个反馈。我们使用这种新颖的建模方法,通过Ca2+诱导的Ca2+释放(CICR)的非线性速率表达式以及作为动态反馈一部分的开放概率的实测非线性IP3依赖性,来描述内质网耗竭的影响。我们的理论可以计算尖峰幅度分布、峰间期(ISI)和幅度的相关系数(Cc),模拟ISI分布并计算它们的矩。我们将其应用于HEK293细胞实验。我们发现理论ISI分布及其矩与实验结果非常吻合。许多实测的Cc值与我们理论提出的观点一致,为正值。令人惊讶的是,尽管ISI期间负反馈衰减会影响尖峰概率,但大多数ISI-幅度相关性较弱。我们甚至发现Cc值为负,这表明反馈会随着ISI增加而降低IP3R的开放概率。导致这种反相关的信号通路组分尚未确定。我们的数据表明,它们涉及受细胞变异性影响的组分。