FISIK: Framework for the Inference of In Situ Interaction Kinetics from Single-Molecule Imaging Data

Abstract

Receptor interactions in the plasma membrane are critical for transmembrane signal transduction. Using live-cell single-molecule imaging it is possible to monitor inter-receptor interactions with high spatiotemporal resolution in their native environment, although only for the labeled subset of receptors, which tends to be a small fraction (often <10% of the full population). As a result, it has remained a challenge to calculate receptor interaction kinetics, especially association rates, from single-molecule data. To overcome this challenge, we developed a mathematical modeling-based Framework for the Inference of in Situ Interaction Kinetics from single-molecule imaging data (termed “FISIK”). FISIK consists of (1) devising a mathematical model of receptor dynamics and interactions, mimicking the biological system and data acquisition setup, and (2) estimating the unknown model parameters, including receptor association and dissociation rates, by fitting the model to experimental single-molecule data. Due to the stochastic nature of model and data, we adapted the method of indirect inference for model calibration. To validate FISIK, we simulated trajectories of diffusing receptors that interact with each other, considering a wide range of model parameters, and including tracking errors that result in noisy data for model calibration. Our tests demonstrated that FISIK has the sensitivity to determine association and dissociation rates; its accuracy depends on the labeled fraction of receptors as well as the extent of tracking errors. For conditions where the labeled fraction was relatively low (e.g. to afford accurate tracking), we found that combining dynamic single-molecule imaging data with static localization microscopy data improves FISIK's performance. All in all, FISIK is a promising novel approach for the derivation of receptor interaction kinetics in their native plasma membrane from single-molecule data.