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Fluorescence microspectroscopy (FMS) with environmentally sensitive dyes provides information about local molecular surroundings at microscopic spatial resolution. Until recently, only probes exhibiting large spectral shifts due to local changes have been used. For filter-based experimental systems, where signal at different wavelengths is acquired sequentially, photostability has been required in addition. Herein, we systematically analyzed our spectral fitting models and bleaching correction algorithms which mitigate both limitations. We showed that careful analysis of data acquired by stochastic wavelength sampling enables nanometer spectral peak position resolution even for highly photosensitive fluorophores. To demonstrate how small spectral shifts and changes in bleaching rates can be exploited, we analyzed vesicles in different lipid phases. Our findings suggest that a wide range of dyes, commonly used in bulk spectrofluorimetry but largely avoided in microspectroscopy due to the above-mentioned restrictions, can be efficiently applied also in FMS.

Complexity of biological systems is one of the toughest problems for any experimental technique. Complex biochemical composition and a variety of biophysical interactions governing the evolution of a state of a biological system imply that the experimental response of the system would be superimposed of many different responses. To obtain a reliable characterization of such a system based on spin-label Electron Paramagnetic Resonance (EPR) spectroscopy, multiple Hybrid Evolutionary Optimization (HEO) combined with spectral simulation can be applied. Implemented as the GHOST algorithm this approach is capable of handling the huge solution space and provides an insight into the "quasicontinuous" distribution of parameters that describe the biophysical properties of an experimental system. However, the analysis procedure requires several hundreds of runs of the evolutionary optimization routine making this algorithm extremely computationally demanding. As only the best parameter sets from each run are assumed to contribute into the final solution, this algorithm appears far from being optimized. The goal of this study is to modify the optimization routine in a way that 20-40 runs would be enough to obtain qualitatively the same characterization. However, to keep the solution diversity throughout the HEO run, fitness sharing and newly developed shaking mechanisms are applied and tested on various test EPR spectra. In addition, other evolutionary optimization parameters such as population size and probability of genetic operators were also varied to tune the algorithm. According to the testing examples a speed-up factor of 5-7 was achieved.

Standard methods of characterization of electron paramagnetic resonance (EPR) spectra of spin-labeled biomembranes limit the resolution of lateral heterogeneity to only two or three domain types. This disables examination of the structure-function relationship in complex membranes, which might be composed of a larger number of different domain types. To enable exploration of this kind, a new approach based on analysis of EPR spectra with multi-run, hybrid evolutionary optimization is proposed here. From the multiple runs a quasi-continuous distribution of membrane spectral parameters (order parameter, proportion of spectral component, polarity correction factor, rotational correlation time and broadening constant) can be constructed and presented by a new presentation technique CODE (colored distribution of E PR spectral parameters). Through this the concept of a "soft" picture of membrane heterogeneity is introduced, in contrast to the standard "discrete" domain picture. The "soft" characterization method, established on synthetic spectra, was used to examine the lateral heterogeneity of liposome membranes as well as of membranes of neutrophils from healthy and asthmatic horses. In liposome membranes the determined number of domain types was the same as already established by standard procedures of EPR spectra line-shape interpretation. In membranes of neutrophils a quasi-continuous distribution of membrane domain properties was detected by the new method.