Optimizing the Acquisition and Analysis of Confocal Images for Quantitative Single-Mobile-Particle Detection
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Quantification of the fluorescence properties of diffusing particles in solution is an invaluable source of information for characterizing the interactions, stoichiometry, or conformation of molecules directly in their native environment. In the case of heterogeneous populations, single-particle detection should be the method of choice and it can, in principle, be achieved by using confocal imaging. However, the detection of single mobile particles in confocal images presents specific challenges. In particular, it requires an adapted set of imaging parameters for capturing the confocal images and an adapted event-detection scheme for analyzing the image. Herein, we report a theoretical framework that allows a prediction of the properties of a homogenous particle population. This model assumes that the particles have linear trajectories with reference to the confocal volume, which holds true for particles with moderate mobility. We compare the predictions of our model to the results as obtained by analyzing the confocal images of solutions of fluorescently labeled liposomes. Based on this comparison, we propose improvements to the simple line-by-line thresholding event-detection scheme, which is commonly used for single-mobile-particle detection. We show that an optimal combination of imaging and analysis parameters allows the reliable detection of fluorescent liposomes for concentrations between 1 and 100 pM. This result confirms the importance of confocal single-particle detection as a complementary technique to ensemble fluorescence-correlation techniques for the studies of mobile particle.
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