Photon-HDF5 is an open-source and open file format for storing photon-counting data from single molecule microscopy experiments, introduced to simplify data exchange and increase the reproducibility of data analysis. Part of the Photon-HDF5 ecosystem, is phconvert, an extensible python library that allows converting proprietary formats into Photon-HDF5 files. However, its use requires some proficiency with command line instructions, the python programming language, and the YAML markup format. This creates a significant barrier for potential users without that expertise, but who want to benefit from the advantages of releasing their files in an open format. In this work, we present a GUI that lowers this barrier, thus simplifying the use of Photon-HDF5. This tool uses the phconvert python library to convert data files originally saved in proprietary data formats to Photon-HDF5 files, without users having to write a single line of code. Because reproducible analyses depend on essential experimental information, such as laser power or sample description, the GUI also includes (currently limited) functionality to associate valid metadata with the converted file, without having to write any YAML. Finally, the GUI includes several productivity-enhancing features such as whole-directory batch conversion and the ability to re-run a failed batch, only converting the files that could not be converted in the previous run.
Single-molecule fluorescence resonant energy transfer (smFRET) allows identifying sub-populations within doubly-labeled molecules, based on the distances between the donor (D) and acceptor (A) fluorescent labels. Solution-based smFRET allows measurement of binding-unbinding events or conformational changes of dye-labeled biomolecules without ensemble averaging and free from surface perturbations. When employing dual (or multi) laser excitation, smFRET allows resolving the number of fluorescent labels on each molecule, greatly enhancing the ability to study heterogeneous samples. A major drawback to solution-based smFRET techniques is their low throughput, which renders measurements time-consuming and prevents from studying kinetic phenomena in real-time.
Here we demonstrate a high-throughput smFRET setup which multiplexes acquisition by using 48 excitation spots and two 48-pixel single-photon avalanche diode (SPAD) arrays. Using two excitation lasers, one of which is alternated on the 10 us time scale, allows identifying and sorting species with one or two active fluorophores, extending the range of measurable FRET efficiencies and enabling proper fluorescence-aided molecular sorting. The performance of the system is demonstrated with a set of doubly-labeled double-stranded DNA oligonucleotides with different D-A distances. We show that the acquisition time for accurate subpopulation identification is reduced from several minutes to seconds, opening the way to high-throughput screening applications and real-time kinetics studies of enzymatic reactions.
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