Single-molecule spectroscopy (SMS) is a powerful technique that enables access to dynamics and properties of (macro)molecules and nanoparticles, which are averaged out in ensemble measurements. The technique is typically based on fluorescence emission originating from the molecules or particles themselves or from fluorescent markers, enabling a broad range of biological applications such as investigations into protein conformational dynamics, enzyme reactions, DNA transcription, functional switching of light-harvesting complexes, and changes in the oligomeric or diffusive states of macromolecules and nanoparticles. SMS measurements often provide multiparameter data such as fluorescence brightness, lifetimes, and spectra, and thus a combination of different data analysis techniques is usually needed to gain a more complete understanding of the data.
The cover image for the September 11 issue of Biophysical Reports, designed by Alexey Chizhik, shows an artistic depiction of the new, multipurpose, graphical user interface (GUI)-based, open-source application we have developed for analyzing single-molecule spectroscopic data. The software, called “Full SMS”, offers powerful analysis types not available in existing GUI-based applications and is written in Python, an open-source language. The stylized laptop in the image is running the Full SMS software and is placed on an optical table equipped with a single-molecule spectroscopy setup. The main analysis types included in the software are represented by large icons on a horizontal sensor screen, with the Spectra functionality being selected, while the laptop monitor displays a screenshot of the software’s Spectra tab. The other main analysis functionalities, represented by the other icons, are as follows: in the Intensity tab, fluorescence intensities can be analyzed by using change-point analysis to resolve intensity levels; in the Lifetime tab, fluorescence lifetimes can be fitted for each intensity level; the Filtering tab allows powerful visual filtering of the resulting intensity-lifetime data; in the Grouping tab, levels can be grouped by using a clustering algorithm; the Antibunching tab allows the calculation of second-order photon correlations; the Raster Scan tab displays raster-scan images; and the Export tab features various export options for further analysis of the data or creation of plots.
Our goal with the creation of Full SMS was to streamline the analysis of SMS data and to create an application that can be used by anyone doing SMS. An additional advantage is the extension of the fluorescence lifetime functionality to bulk samples. The data analysis algorithms are based on state-of-the-art, unbiased statistical approaches. The software is specifically designed to be usable without any programming knowledge and features parallel processing capabilities for significantly increased performance. We hope that the software finds wide use, and we welcome any feedback, suggestions, or extensions. More information about our research can be found at https://biophysicsup.netlify.app.
— Joshua L. Botha, Bertus van Heerden, and Tjaart P.J. Krüger