Parameter estimation in fluorescence recovery after photobleaching: Quantitative analysis of protein binding reactions and diffusion

Williamson, Daniel E.; Sahai, Erik; Jenkins, Robert P.; O'Dea, Reuben D.; King, John R.

Abstract

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 diffu-sivity 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.

Citation

Williamson, D. E., Sahai, E., Jenkins, R. P., O'Dea, R. D., & King, J. R. (2021). Parameter estimation in fluorescence recovery after photobleaching: Quantitative analysis of protein binding reactions and diffusion. Journal of Mathematical Biology, 83, Article 1. https://doi.org/10.1007/s00285-021-01616-z

• Journal Article Type: Article
• Acceptance Date: Oct 27, 2020
• Online Publication Date: Jun 15, 2021
• Publication Date: 2021
• Deposit Date: Oct 29, 2020
• Publicly Available Date: Jun 16, 2022
• Journal: Journal of Mathematical Biology
• Print ISSN: 0303-6812
• Electronic ISSN: 1432-1416
• Peer Reviewed: Peer Reviewed
• Volume: 83
• Article Number: 1
• DOI: https://doi.org/10.1007/s00285-021-01616-z
• Public URL: https://nottingham-repository.worktribe.com/output/5006222
• Publisher URL: https://link.springer.com/article/10.1007/s00285-021-01616-z