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钙振荡的统计观点。

A Statistical View on Calcium Oscillations.

机构信息

Centre for Mathematical Medicine and Biology, School of Mathematical Sciences, University of Nottingham, Nottingham, UK.

Max Delbrück Centre for Molecular Medicine, Berlin, Germany.

出版信息

Adv Exp Med Biol. 2020;1131:799-826. doi: 10.1007/978-3-030-12457-1_32.

Abstract

Transient rises and falls of the intracellular calcium concentration have been observed in numerous cell types and under a plethora of conditions. There is now a growing body of evidence that these whole-cell calcium oscillations are stochastic, which poses a significant challenge for modelling. In this review, we take a closer look at recently developed statistical approaches to calcium oscillations. These models describe the timing of whole-cell calcium spikes, yet their parametrisations reflect subcellular processes. We show how non-stationary calcium spike sequences, which e.g. occur during slow depletion of intracellular calcium stores or in the presence of time-dependent stimulation, can be analysed with the help of so-called intensity functions. By utilising Bayesian concepts, we demonstrate how values of key parameters of the statistical model can be inferred from single cell calcium spike sequences and illustrate what information whole-cell statistical models can provide about the subcellular mechanistic processes that drive calcium oscillations. In particular, we find that the interspike interval distribution of HEK293 cells under constant stimulation is captured by a Gamma distribution.

摘要

在众多细胞类型和多种条件下,已经观察到细胞内钙离子浓度的瞬时上升和下降。现在有越来越多的证据表明,这些全细胞钙振荡是随机的,这给建模带来了重大挑战。在这篇综述中,我们仔细研究了最近开发的钙振荡统计方法。这些模型描述了全细胞钙峰的时间,但它们的参数化反映了亚细胞过程。我们展示了如何使用所谓的强度函数来分析非平稳钙峰序列,例如在细胞内钙库缓慢耗竭期间或存在时变刺激时发生的钙峰序列。通过利用贝叶斯概念,我们演示了如何从单个细胞钙峰序列推断统计模型的关键参数值,并说明了全细胞统计模型可以提供关于驱动钙振荡的亚细胞机制过程的哪些信息。特别是,我们发现恒定刺激下 HEK293 细胞的峰间间隔分布由伽马分布捕获。

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