Single molecule diffusion coefficient estimation by image analysis of simulated CCD images to aid high-throughput screening.

Extension of one-dimensional signal analysis to two-dimensional image analysis could accelerate conventional methods of high-throughput screening in the discovery of new pharmaceutical agents. This work describes a first step taken towards this goal - the evaluation of image-analysis based estimation strategies of the diffusion coefficient of a single molecule transported within a microfabricated flowcell. A computer simulation of single-molecule imaging by a charge-coupled device (CCD) camera is used to determine if it is possible to distinguish three different types of molecules with different diffusion coefficients. The Gaussian fitting algorithm finds the variance of the transverse trajectory, which increases linearly with the diffusion coefficient; the path analysis algorithm determines the diffusion coefficient from cumulative summation of the squared displacement along the imaged path; the detector area analysis algorithm determines the number of resolvable positions or pixels in the imaged trajectory. Of the three methods, the path analysis strategy appears to provide the most reliable measure of diffusion coefficient with relative error of 13.6% and 6.4% between single molecules with diffusion coefficients of 2.85e-7 and 1.425e-7 cm(2)/s. The detector area analysis method can statistically distinguish between single molecules with diffusion coefficients of 5.7e-7 and 1.425e-7 cm(2)/s at the p(0.05) level.

Duke Scholars

Author Pengfei Song Biomedical Engineering