Mapping molecular statistics with balanced super-resolution optical fluctuation imaging (bSOFI)

Abstract

Background: Super-resolution optical fluctuation imaging (SOFI) achieves 3D super-resolution by computing temporal cumulants or spatio-temporal cross-cumulants of stochastically blinking fluorophores. In contrast to localization microscopy, SOFI is compatible with weakly emitting fluorophores and a wide range of blinking conditions. The main drawback of SOFI is the nonlinear response to brightness and blinking heterogeneities in the sample, which limits the use of higher cumulant orders for improving the resolution. Balanced super-resolution optical fluctuation imaging (bSOFI) analyses several cumulant orders for extracting molecular parameter maps, such as molecular state lifetimes, concentration and brightness distributions of fluorophores within biological samples. Moreover, the estimated blinking statistics are used to balance the image contrast, i.e. linearize the brightness and blinking response and to obtain a resolution improving linearly with the cumulant order. Results: Using a widefield total-internal-reflection (TIR) fluorescence microscope, we acquired image sequences of fluorescently labelled microtubules in fixed HeLa cells. We demonstrate an up to five-fold resolution improvement as compared to the diffraction-limited image, despite low single-frame signal-to-noise ratios. Due to the TIR illumination, the intensity profile in the sample decreases exponentially along the optical axis, which is reported by the estimated spatial distributions of the molecular brightness as well as the blinking on-ratio. Therefore, TIR-bSOFI also encodes depth information through these parameter maps. Conclusions: bSOFI is an extended version of SOFI that cancels the nonlinear response to brightness and blinking heterogeneities. The obtained balanced image contrast significantly enhances the visual perception of super-resolution based on higher-order cumulants and thereby facilitates the access to higher resolutions. Furthermore, bSOFI provides microenvironment-related molecular parameter maps and paves the way for functional super-resolution microscopy based on stochastic switching.

PALM and STORM: Into large fields and high-throughput microscopy with sCMOS detectors

“…As with 3B, this method is computationally demanding and one group reported taking a whole day to process a 100 lm 2 region [83]. Stochastic Optical Fluctuation Imaging (SOFI) is capable of doubling the resolution with a standard widefield microscope (200 frames) [86] and achieving 80 nm resolution with a TIRF microscope with low laser powers (5000 frames) [87]. The virtual removal of background and out-of-focus light in SOFI allows it to generate optically sectioned z-stacks, and a Matlab SOFI package is freely available SOFI package [88].…”

Combining PALM and SOFI for quantitative imaging of focal adhesions in living cells

“…Compared with PALM, this technique tolerates higher fluorophore densities or higher activation rates, resulting in an improved temporal resolution 11 . Additionally, an extension called balanced SOFI (bSOFI) can be used to determine the fluorophore on-time ratio, which allows to estimate of the fluorophore density 12 . In previous work, we investigated the complementarity of PALM and SOFI by applying both techniques to the same sequence of camera frames 13 .…”

Computational methods in super-resolution microscopy

“…5, the SOFI technique can be employed on various platforms, e.g., wide-field, total internal reflection fluorescence (TIRF), and spinningdisk confocal microscopes (Dertinger et al, 2013). Geissbuehler et al (2012) proposed balanced SOFI (bSOFI) combining multiple SOFI orders to improve spatial resolution and alleviate reconstruction artifacts. Zeng et al (2015) proposed joint tagging SOFI (JT-SOFI) to achieve fast, high-fidelity super-resolution imaging.…”