Abstract
Super-resolution fluorescence imaging techniques allow optical imaging of specimens beyond the diffraction limit of light. Super-resolution optical fluctuation imaging (SOFI) relies on computational analysis of stochastic blinking events to obtain a super-resolved image. As with some other super-resolution methods, this strong dependency on computational analysis can make it difficult to gauge how well the resulting images reflect the underlying sample structure. We herein report SOFIevaluator, an unbiased and parameter-free algorithm for calculating a set of metrics that describes the quality of super-resolution fluorescence imaging data for SOFI. We additionally demonstrate how SOFIevaluator can be used to identify fluorescent proteins that perform well for SOFI imaging under different imaging conditions.
Highlights
The diffraction of light has long limited light-based microscopy to a spatial resolution of approximately 200 nm in the lateral direction
We previously developed a strategy for the model-free assessment of the measurement uncertainty associated with every pixel in the Super-resolution optical fluctuation imaging (SOFI) imaging, by using statistical resampling of the experimental data [17]
We developed a rigorous mathematical framework for estimating the quality of SOFIgenerated images using 3 different paradigms: model-free signal-to-noise ratio (SNR) estimation, time decorrelation to estimate the contribution of bleaching to the signal, and estimation of the observed point-spread function (PSF)
Summary
The diffraction of light has long limited light-based microscopy to a spatial resolution of approximately 200 nm in the lateral direction. Its main distinguishing feature is that it is relatively insensitive to background signal, and can be performed over a broad range of labelling densities and probe brightnesses [3,4] This robustness has made it possible to use the technique for the first sub-diffraction observation of kinase activity [5]. Even with perfect imaging, the available information may be limited, as is the case with low labeling densities. Such issues have been tackled by repeating the measurement several times, but true repetitive imaging is difficult to achieve in the face of issues such as biological heterogeneity, photobleaching and phototoxicity. In addition to presenting the fundamental algorithm, we used SOFIevaluator to test the suitability of 20 different fluorescent proteins, spanning the full optical window, for SOFI imaging
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
