Detecting molecular separation in nano-fluidic channels through velocity analysis of temporal image sequences by multivariate curve resolution

In this study, we report on a method of determining individual velocities of molecular species being separated in a fluid medium within array of nanofluidic channels that can be useful in the detection of molecular species. The method is based on the application of multivariate image analysis methods, in this case principal component analysis and multivariate curve resolution, to temporal image series capturing multiple species moving through the medium. There are two novel and unique advantages of the reported method. First, it is possible to identify transport velocities of different molecular species, even those tagged with the same fluorophore. And second, the velocity determination can be made before there is any visual separation of the species in the medium at the very initial stages of separation. The capability of the methodology to detect the separation of species without fluorescent labeling and to provide an accurate ratio of their velocities even at the very early pre-visual stage of separation will significantly optimize separation experiments and assist in fast and accurate detection of analytes based on microand nano-fluidics assays. The presented method can be practiced in connection with various molecular separation techniques including, but not limited to, nanochannel electrophoresis, microchannel capillary electrophoresis, and gel electrophoresis.