Parameter-free rendering of single-molecule localization microscopy data for parameter-free resolution estimation

Localization microscopy is a super-resolution imaging technique that relies on the spatial and temporal separation of blinking fluorescent emitters. These blinking events can be individually localized with a precision significantly smaller than the classical diffraction limit. This sub-diffraction localization precision is theoretically bounded by the number of photons emitted per molecule and by the sensor noise. These parameters can be estimated from the raw images. Alternatively, the resolution can be estimated from a rendered image of the localizations. Here, we show how the rendering of localization datasets can influence the resolution estimation based on decorrelation analysis. We demonstrate that a modified histogram rendering, termed bilinear histogram, circumvents the biases introduced by Gaussian or standard histogram rendering. We propose a parameter-free processing pipeline and show that the resolution estimation becomes a function of the localization density and the localization precision, on both simulated and state-of-the-art experimental datasets.

Development of novel experimental and computational methods for three-dimensional coherent and super-resolution microscopy

Adrien Charles-François Raymond Descloux

Optical microscopy is one widely used tool to study cell functions and the interaction of molecules at a sub-cellular level. Optical microscopy techniques can be broadly divided into two categories: partially coherent and incoherent. Coherent microscopy techniques are usually label-free and provide diffraction limited structural information about the sample refractive index distribution though the measurement of phase delay induced by the sample. Since they can be very conservative in the illumination power directed toward the sample, they exhibit very low photo-toxicity and are suitable for both high speed and time lapse imaging. Fluorescence microscopy is an incoherent microscopy method which uses biochemistry techniques to label cellular structures with fluorescent molecules which emit light when excited by a laser. Fluorescence microscopy provides diffraction limited high specificity imaging but is limited in time due to photo-bleaching and photo-toxicity. Super-resolution microscopy is a sub-category of fluorescence microscopy which manipulates and exploits some properties of the fluorescent molecules to achieve high specificity sub-diffraction imaging. Super-resolution comes however at the price of an increased total acquisition time, which limits the applications of super-resolution microscopy to relatively slow cellular processes. The ideal microscope however does not exist; due to the limited spatio-temporal bandwidth of far-field microscopy, there will always be unavoidable trade-offs. There is therefore a need to find new ways to ensure that the methods are reaching their optimal performances and a need to study how different methods can complement each others. I start by presenting a new method for three-dimensional quantitative phase retrieval. I derive a model for the image formation of three-dimensional bright field images and extrapolate a novel expression allowing to retrieve the phase distribution from a bright field image stack. Using a unique image-splitting multi-plane prism that allows to acquire 8 distinct focal planes in a single exposure, I demonstrate three-dimensional quantitative phase imaging at 200 Hz . Finally, I show the association of three-dimensional super-resolution SOFI with phase imaging. To improve the imaging speed and lower the illumination intensity, I combine the same prism platform with a high-speed structured illumination. Since the structured illumination presented is using a digital micro-mirror device, about 90 % of the laser light is diffracted outside of the optical path. To improve the illumination efficiency but keep its speed and flexibility, I present a new approach for achromatic high power high speed SIM, based on a Michelson interferometer. With the access to high illumination power density, I also show the first experimental combination of SIM with SOFI using a self-blinking dye. Motivated by the absence of tools to objectively judge the performance of the microscopy methods I develop, I present a novel algorithm for image resolution estimation. The method estimate the resolution by correlating the image with several filtered version of itself without any external parameters. Finally, in the context of the AD-gut consortium, I show a practical application of deep neural networks used to assists the segmentation and mapping of the microscopy image of enzymatically labeled DNA molecules.

EPFL2020

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

Three-dimensional Nano-Localization of Fluroescent Emitters

François Aguet, Noelia Laura Bocchio, Theo Lasser, Iwan Märki

The use of fluorescence light for far-field imaging at the nanometer scale has drawn much attention worldwide. Example techniques include STED microscopy and localization microscopy (PALM, STORM). Typically, nanoscopy approaches have been focused on the manipulation and detection of the intensity of fluorescence light leading to lateral accuracy of a few nanometers. However, three-dimensional nanometer accuracy, in particular axial accuracy of the same order, remains a challenge. The phase of fluorescence light has shown to be valuable for axial measurements at the nano-scale. We extent the framework of phase microscopy to fluorescence light at the single-molecule level and demonstrate an approach combining super resolution microscopy with fluorescence interferometry for localizing a single nano-object to within several nanometres in all three dimensions. In a first proof of principle we demonstrate three-dimensional nano-localization of quantum dots within a standard deviation for the lateral and axial localization in the order of 6 nm and 4 nm, respectively. As the localization precision of the single nano-object in all three dimensions depends on the number of detected photons, we are exploring ways to increase the number of detected photons. As a result, we expect our approach to pave the way for three-dimensional, molecular-resolution fluorescence imaging.