Automatic channel unmixing for high-throughput quantitative analysis of fluorescence images

Laser-scanning microscopy allows rapid acquisition of multi-channel data, paving the way for high-throughput, high-content analysis of large numbers of images. An inherent problem of using multiple fluorescent dyes is overlapping emission spectra, which results in channel cross-talk and reduces the ability to extract quantitative measurements. Traditional unmixing methods rely on measuring channel cross-talk and using fixed acquisition parameters, but these requirements are not suited to high-throughput processing. Here we present a simple automatic method to correct for channel cross-talk in multi-channel images using image data only. The method is independent of the acquisition parameters but requires some spatial separation between different dyes in the image. We evaluate the method by comparing the cross-talk levels it estimates to those measured directly from a standard fluorescent slide. The method is then applied to a high-throughput analysis pipeline that measures nuclear volumes and relative expression of gene products from three-dimensional, multi-channel fluorescence images of whole Drosophila embryos. Analysis of images before unmixing revealed an aberrant spatial correlation between measured nuclear volumes and the gene expression pattern in the shorter wavelength channel. Applying the unmixing algorithm before performing these analyses removed this correlation.