Multilinear Slicing for curve resolution of fluorescence imaging with sequential illumination.

Fluorescence microscopy is an extremely powerful technique that allows to distinguish multiple labels based on their emission color or other properties, such as their photobleaching and fluorescence recovery kinetics. These kinetics are ideally assumed to be mono-exponential in nature, where the time constants intrinsic to each fluorophore can be used to quantify their presence in the sample. However, these time constants also depend on the specifics of the illumination and sample conditions, meaning that identifying the different contributions in a mixture using a single-channel detection may not be straightforward. In this work, we propose a factor analysis approach called Slicing to identify the different contributions in a multiplexed fluorescence microscopy image exploiting a single measurement channel. With Slicing, a two-way dataset is rearranged into a three-way dataset, which allows the application of a trilinear decomposition model to derive individual profiles for all the model components. We demonstrate this method on bleaching - recovery fluorescence microscopy imaging data of U2OS cells, allowing us to determine the spatial distribution of the dyes and their associated characteristic relaxation traces, without relying on a parametric fitting. By requiring little a priori knowledge and efficiently handling perturbation factors, our method represents a general approach for the recovery of multiple mono-exponential profiles from single-channel microscopy data.

Self-contained and modular structured illumination microscope.

We present a modular implementation of structured illumination microscopy (SIM) that is fast, largely self-contained and that can be added onto existing fluorescence microscopes. Our strategy, which we call HIT-SIM, can theoretically deliver well over 50 super-resolved images per second and is readily compatible with existing acquisition software packages. We provide a full technical package consisting of schematics, a list of components and an alignment scheme that provides detailed specifications and assembly instructions. We illustrate the performance of the instrument by imaging optically large samples containing sequence-specifically stained DNA fragments.

Design of experiments for the optimization of SOFI super-resolution microscopy imaging.

Super-resolution optical fluctuation imaging (SOFI) is a well-known super-resolution technique appreciated for its versatility and broad applicability. However, even though an extended theoretical description is available, it is still not fully understood how the interplay between different experimental parameters influences the quality of a SOFI image. We investigated the relationship between five experimental parameters (measurement time, on-time t on, off-time t off, probe brightness, and out of focus background) and the quality of the super-resolved images they yielded, expressed as Signal to Noise Ratio (SNR). Empirical relationships were modeled for second- and third-order SOFI using data simulated according to a D-Optimal design of experiments, which is an ad-hoc design built to reduce the experimental load when the total number of trials to be conducted becomes too high for practical applications. This approach proves to be more reliable and efficient for parameter optimization compared to the more classical parameter by parameter approach. Our results indicate that the best image quality is achieved for the fastest emitter blinking (lowest t on and t off), lowest background level, and the highest measurement duration, while the brightness variation does not affect the quality in a statistically significant way within the investigated range. However, when the ranges spanned by the parameters are constrained, a different set of optimal conditions may arise. For example, for second-order SOFI, we identified situations in which the increase of t off can be beneficial to SNR, such as when the measurement duration is long enough. In general, optimal values of t on and t off have been found to be highly dependent from each other and from the measurement duration.