Interactive Tutorials - Spinning Disk Fundamentals

Interactive Tutorials

Spectral Imaging

Spectral Imaging with Linear Unmixing

When experimental conditions permit, the thoughtful selection of fluorescent labels, laser multitracking strategies, filter set characteristics, and control specimen correction factors can combine to yield excellent results. In the real world, however, situations often arise where the choice of experimental parameters is limited and the use of fluorescent probes lacking in significant spectral overlap is not feasible. Such a scenario is often encountered when attempting to conduct multiple labeling investigations with fluorescent proteins. Experiments are also subject to artifacts arising from natural autofluorescence or fluorescence induced by the use of fixatives or DNA transfection reagents, which can span several detection channels. In these cases, a technique known as spectral imaging coupled with image analysis using linear unmixing can be employed to segregate mixed fluorescent signals and more clearly resolve the spatial contribution of each fluorophore (often referred to as emission fingerprinting). This interactive tutorial explores how multiple fluorophores can be distinguished using spectral imaging techniques.

A typical spectral image lambda stack gathered by the microscope is often composed many thousands or even millions of individual spectra (depending upon the lateral image dimensions), with essentially one spectrum being represented at each pixel location. The associated data files are therefore quite large and complex (virtually impossible to analyze by visual inspection), thus requiring a dedicated software palette for interpretation and presentation of the results. Analysis of lambda stacks can target the extraction of spectral data or image features (or both) using tools that are either packaged with the instrument or widely available from aftermarket manufacturers. Each fluorophore or absorbing dye, regardless of the degree of spectral overlap with other probes, has a unique spectral signature or emission fingerprint that can be determined independently and used to assign the proper contribution from that probe to individual pixels in a lambda stack. The result of the linear unmixing technique is the generation of distinct emission fingerprints for each fluorophore used in the specimen (or excitation fingerprints if excitation rather than emission spectra were employed to generate the lambda stack). In summary, the spectral information in an image captured by the microscope is binned into three broad spectral ranges roughly corresponding to the primary additive colors red, green, and blue. Linear unmixing enables the precise determination of spectral profiles at every pixel in the image to overcome overlap and binning artifacts, and therefore is able to reassign color to regions that would otherwise appear mixed. The algorithms can be readily applied to virtually any lambda stack generated using additive fluorescent probes, but images containing absorbing dye signatures (imaged in brightfield) and reflectance images must be converted to optical density before applying linear unmixing algorithms.

Contributing Authors

Adam M. Rainey and Michael W. Davidson - National High Magnetic Field Laboratory, 1800 East Paul Dirac Dr., The Florida State University, Tallahassee, Florida, 32310.