ABSTRACT
BACKGROUND: Spectral Imaging Microscopy is gaining attention in biological research. Most of the commercial systems in vogue employ linear spectral un-mixing algorithms and/or spectral profile matching algorithms to extract the component spectral information from the measured specimen spectra. The need to accurately deconvolve multiple spectra with minimal cross-contamination is always accompanied by an increase in system complexity and cost. METHODS: We describe here a variant of the spectral waveform cross-correlation analysis (SWCCA) method where the master reference spectral library is constructed by composite spectra with varying ratios of component spectra, unlike the conventional spectral library where pure spectra form the components. We demonstrate that this spectral kinetics ratiometric approach gives realistic estimates of fluorophore distribution in living cells with a better spectral correlation as compared with pure component spectral libraries. RESULTS: Biological applications demonstrated in this article include acceptor photobleaching FRET, caspase activity during cell death and mitochondrial membrane polarization kinetics during substrate metabolism. CONCLUSIONS: Beyond the representative applications presented in this article, we think the proposed approach can be valuable in dynamic studies of a variety of other cellular processes such as pH oscillations, photobleaching and quenching kinetics. Besides giving better spectral correlation and real-time monitoring of biophysical processes in living cells, this method can serve as an economical solution for high-throughput spectral classification requirements.
