SOFI Simulation Tool: A Software Package for Simulating and Testing Super-Resolution Optical Fluctuation Imaging

Super-resolution optical fluctuation imaging (SOFI) allows one to perform sub-diffraction fluorescence microscopy of living cells. By analyzing the acquired image sequence with an advanced correlation method, i.e. a high-order cross-cumulant analysis, super-resolution in all three spatial dimensions can be achieved. Here we introduce a software tool for a simple qualitative comparison of SOFI images under simulated conditions considering parameters of the microscope setup and essential properties of the biological sample. This tool incorporates SOFI and STORM algorithms, displays and describes the SOFI image processing steps in a tutorial-like fashion. Fast testing of various parameters simplifies the parameter optimization prior to experimental work. The performance of the simulation tool is demonstrated by comparing simulated results with experimentally acquired data.

Multi-plane super-resolution microscopy

Azat Sharipov

Understanding cell functions is the major goal of molecular biology, which intends to elucidate the interactions between biomolecules at a subcellular level. One of the widely used techniques in molecular biology is fluorescence microscopy, which offers high specificity and sensitivity at the submicrometer spatial scale but is limited by diffraction to about 200nm lateral resolution, which is insufficient for the observation of many molecular processes. During the last two decades several super-resolution techniques overcoming the diffraction limit have been developed. However, imaging samples in three dimensions (3D) at high speed remains a challenging and not yet resolved task. This thesis focuses on enhancing super-resolution imaging towards fast, live-cell and 3D imaging. Super-resolution optical fluctuation imaging (SOFI) is a technique based on the stochastic fluctuations of photoswitchable fluorescent markers. It possesses several unique features such as background reduction, capability of increased pixel grid generation, i.e. spatial oversampling, as well as tolerance and robustness to a wide range of photoswitching conditions. In this thesis SOFI was extended to perform 3D analysis. As a result, the resolution in all three spatial dimensions can be improved and the depth sampling increased. We present a novel design of a 3D fluorescence microscope capable of acquiring images of eight depth planes simultaneously. This design incorporates an image-splitting prism, a single optical element allowing to achieve in-depth image separation. The optical performance of the 3D microscope was described and experimentally verified. The simultaneous depth plane acquisition allows to fully exploit the 3D capabilities of SOFI while generating additional virtual depth planes. An algorithm for the extraction of switching kinetics of fluorescent markers is presented. Using appropriate imaging conditions, we demonstrate the applications of 3D SOFI on several examples of fixed and living cells. We also present the potential of the 3D microscope for phase retrieval in transparent samples.

EPFL2017

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

Corinne Berclaz, Noelia Laura Bocchio, Claudio Dellagiacoma, Stefan Geissbuehler, Theo Lasser, Marcel Leutenegger

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. 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. 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.

2012

Dielectric-sphere-based microsystem for optical super-resolution imaging

Gergely Huszka

Well-established imaging techniques proved that features below the diffraction limit can be observed optically using so-called super-resolution microscopies, which overcome Abbe's resolution limit. In traditional far-field microscopy, the introduction of fluorescent samples and engineered light paths was key for this breakthrough. In parallel, near-field techniques with similar performance were developed, but they suffered from a limited field-of-view. The merge of the two approaches was already demonstrated ~15 years ago, when micrometer-sized dielectric objects positioned on a sample were found to be able to image the sample with super-resolution. By observing the sample through the micro-object with a classical optical microscope, the latter could capture a virtual image showing sub-diffraction details. Although this way the near-field information transfer into the far-field by the micro-object was proven and found to be key for enabling super-resolution imaging, the limited field-of-view, as determined by the size of the micro-object, remained an issue. In this dissertation, a novel method is presented that provides a microscopy technique capable of achieving super-resolution without field-of-view restrictions. Based on previous studies, dielectric microspheres were chosen for this imaging technique. First, the working principle of these microspheres was explored by investigating both the illumination and the reflected light path. These findings provided a better understanding on the phenomena working behind microsphere-assisted imaging and allowed to create an engineering toolbox that can be used to design microsphere-based optical systems. This was followed by an investigation on microfabrication techniques, in order to create a microchip that can serve as a bridge between a single microsphere and the macro-sized-components of a classical optical microscope. The resulting chip was later embedded in a custom fixation system that allowed scanning of this microsphere over the sample, while keeping its position fixed compared to the microscope objective. The microscope mounted camera recorded pictures during the scan, which were used to generate a large field-of-view super-resolution image by stitching. After initial successes, the setup was improved in terms of robustness and application range. The new version allowed field-of-view in the millimeter range, while it could be operated in both oil- and water-immersion. Parallel imaging with an array of microspheres was also implemented, which further enhanced the imaging speed. The algorithmic background (including an automated scanning and image reconstruction protocol) of this microscopy method was developed in-house. Its validation showed superior performance compared to existing software. Future developments (e.g. employment of 3D-printing for mass-production, imaging in vivo biological samples, metrology applications) are envisioned. The findings presented here may pave the road for an easy-to-use, generalized super-resolution imaging system.

EPFL2018