University of Nottingham, Nottingham, NG7 2RD, UK.
Tumour Cell Biology Laboratory, The Francis Crick Institute, London, NW1 1AT, UK.
J Math Biol. 2021 Jun 15;83(1):1. doi: 10.1007/s00285-021-01616-z.
Fluorescence recovery after photobleaching (FRAP) is a common experimental method for investigating rates of molecular redistribution in biological systems. Many mathematical models of FRAP have been developed, the purpose of which is usually the estimation of certain biological parameters such as the diffusivity and chemical reaction rates of a protein, this being accomplished by fitting the model to experimental data. In this article, we consider a two species reaction-diffusion FRAP model. Using asymptotic analysis, we derive new FRAP recovery curve approximation formulae, and formally re-derive existing ones. On the basis of these formulae, invoking the concept of Fisher information, we predict, in terms of biological and experimental parameters, sufficient conditions to ensure that the values all model parameters can be estimated from data. We verify our predictions with extensive computational simulations. We also use computational methods to investigate cases in which some or all biological parameters are theoretically inestimable. In these cases, we propose methods which can be used to extract the maximum possible amount of information from the FRAP data.
荧光漂白后恢复(FRAP)是一种常用于研究生物系统中分子重分布速率的实验方法。已经开发了许多 FRAP 的数学模型,其目的通常是估计某些生物学参数,如蛋白质的扩散率和化学反应速率,这是通过将模型拟合到实验数据来实现的。在本文中,我们考虑了一个双物种反应扩散 FRAP 模型。使用渐近分析,我们推导出了新的 FRAP 恢复曲线近似公式,并正式重新推导了现有的公式。基于这些公式,借助 Fisher 信息的概念,我们根据生物学和实验参数预测了充分条件,以确保可以从数据中估计所有模型参数的值。我们通过广泛的计算模拟验证了我们的预测。我们还使用计算方法研究了某些或所有生物学参数在理论上不可估计的情况。在这些情况下,我们提出了可以从 FRAP 数据中提取最大信息量的方法。