Inferring Stochastic Rates from Heterogeneous Snapshots of Particle Positions.

Many imaging techniques for biological systems-like fixation of cells coupled with fluorescence microscopy-provide sharp spatial resolution in reporting locations of individuals at a single moment in time but also destroy the dynamics they intend to capture. These snapshot observations contain no information about individual trajectories, but still encode information about movement and demographic dynamics, especially when combined with a well-motivated biophysical model. The relationship between spatially evolving populations and single-moment representations of their collective locations is well-established with partial differential equations (PDEs) and their inverse problems. However, experimental data is commonly a set of locations whose number is insufficient to approximate a continuous-in-space PDE solution. Here, motivated by popular subcellular imaging data of gene expression, we embrace the stochastic nature of the data and investigate the mathematical foundations of parametrically inferring demographic rates from snapshots of particles undergoing birth, diffusion, and death in a nuclear or cellular domain. Toward inference, we rigorously derive a connection between individual particle paths and their presentation as a Poisson spatial process. Using this framework, we investigate the properties of the resulting inverse problem and study factors that affect quality of inference. One pervasive feature of this experimental regime is the presence of cell-to-cell heterogeneity. Rather than being a hindrance, we show that cell-to-cell geometric heterogeneity can increase the quality of inference on dynamics for certain parameter regimes. Altogether, the results serve as a basis for more detailed investigations of subcellular spatial patterns of RNA molecules and other stochastically evolving populations that can only be observed for single instants in their time evolution.

Structured illumination microscopy artefacts caused by illumination scattering.

Despite its wide application in live-cell super-resolution (SR) imaging, structured illumination microscopy (SIM) suffers from aberrations caused by various sources. Although artefacts generated from inaccurate reconstruction parameter estimation and noise amplification can be minimized, aberrations due to the scattering of excitation light on samples have rarely been investigated. In this paper, by simulating multiple subcellular structure with the distinct refractive index from water, we study how different thicknesses of this subcellular structure scatter incident light on its optical path of SIM excitation. Because aberrant interference light aggravates with the increase in sample thickness, the reconstruction of the 2D-SIM SR image degraded with the change of focus along the axial axis. Therefore, this work may guide the future development of algorithms to suppress SIM artefacts caused by scattering in thick samples. This article is part of the Theo Murphy meeting issue 'Super-resolution structured illumination microscopy (part 1)'.

Extended mechanical force measurements using structured illumination microscopy.

Quantifying cell generated mechanical forces is key to furthering our understanding of mechanobiology. Traction force microscopy (TFM) is one of the most broadly applied force probing technologies, but its sensitivity is strictly dependent on the spatio-temporal resolution of the underlying imaging system. In previous works, it was demonstrated that increased sampling densities of cell derived forces permitted by super-resolution fluorescence imaging enhanced the sensitivity of the TFM method. However, these recent advances to TFM based on super-resolution techniques were limited to slow acquisition speeds and high illumination powers. Here, we present three novel TFM approaches that, in combination with total internal reflection, structured illumination microscopy and astigmatism, improve the spatial and temporal performance in either two-dimensional or three-dimensional mechanical force quantification, while maintaining low illumination powers. These three techniques can be straightforwardly implemented on a single optical set-up offering a powerful platform to provide new insights into the physiological force generation in a wide range of biological studies. This article is part of the Theo Murphy meeting issue 'Super-resolution structured illumination microscopy (part 1)'.

mmSIM: an open toolbox for accessible structured illumination microscopy.

Since the first practical super-resolution structured illumination fluorescence microscopes (SIM) were demonstrated more than two decades ago, the method has become increasingly popular for a wide range of bioimaging applications. The high cost and relative inflexibility of commercial systems, coupled with the conceptual simplicity of the approach and the desire to exploit and customize existing hardware, have led to the development of a large number of home-built systems. Several detailed hardware designs are available in the scientific literature, complemented by open-source software tools for SIM image validation and reconstruction. However, there remains a lack of simple open-source software to control these systems and manage the synchronization between hardware components, which is critical for effective SIM imaging. This article describes a new suite of software tools based on the popular Micro-Manager package, which enable the keen microscopist to develop and run a SIM system. We use the software to control two custom-built, high-speed, spatial light modulator-based SIM systems, evaluating their performance by imaging a range of fluorescent samples. By simplifying the process of SIM hardware development, we aim to support wider adoption of the technique. This article is part of the Theo Murphy meeting issue 'Super-resolution structured illumination microscopy (part 1)'.

Answers to fundamental questions in superresolution microscopy.

This article presents answers to the questions on superresolution and structured illumination microscopy (SIM) as raised in the editorial of this collection of articles (https://doi.org/10.1098/rsta.2020.0143). These answers are based on my personal views on superresolution in light microscopy, supported by reasoning. Discussed are the definition of superresolution, Abbe's resolution limit and the classification of superresolution methods into nonlinear-, prior knowledge- and near-field-based superresolution. A further focus is put on the capabilities and technical aspects of present and future SIM methods. This article is part of the Theo Murphy meeting issue 'Super-resolution structured illumination microscopy (part 1)'.

Improving axial resolution in Structured Illumination Microscopy using deep learning.

Structured Illumination Microscopy (SIM) is a widespread methodology to image live and fixed biological structures smaller than the diffraction limits of conventional optical microscopy. Using recent advances in image up-scaling through deep learning models, we demonstrate a method to reconstruct 3D SIM image stacks with twice the axial resolution attainable through conventional SIM reconstructions. We further demonstrate our method is robust to noise and evaluate it against two-point cases and axial gratings. Finally, we discuss potential adaptions of the method to further improve resolution. This article is part of the Theo Murphy meeting issue 'Super-resolution structured illumination microscopy (part 1)'.

Structured illumination microscopy and image scanning microscopy: a review and comparison of imaging properties.

Structured illumination microscopy and image scanning microscopy are two microscopical tech- niques, rapidly increasing in practical application, that can result in improvement in transverse spatial resolution, and/or improvement in axial imaging performance. The history and principles of these techniques are reviewed, and the imaging properties of the two methods compared. This article is part of the Theo Murphy meeting issue 'Super-resolution structured illumination microscopy (part 1)'.

Testing independence between two random sets for the analysis of colocalization in bioimaging.

Colocalization aims at characterizing spatial associations between two fluorescently tagged biomolecules by quantifying the co-occurrence and correlation between the two channels acquired in fluorescence microscopy. Colocalization is presented either as the degree of overlap between the two channels or the overlays of the red and green images, with areas of yellow indicating colocalization of the molecules. This problem remains an open issue in diffraction-limited microscopy and raises new challenges with the emergence of superresolution imaging, a microscopic technique awarded by the 2014 Nobel prize in chemistry. We propose GcoPS, for Geo-coPositioning System, an original method that exploits the random sets structure of the tagged molecules to provide an explicit testing procedure. Our simulation study shows that GcoPS unequivocally outperforms the best competitive methods in adverse situations (noise, irregularly shaped fluorescent patterns, and different optical resolutions). GcoPS is also much faster, a decisive advantage to face the huge amount of data in superresolution imaging. We demonstrate the performances of GcoPS on two biological real data sets, obtained by conventional diffraction-limited microscopy technique and by superresolution technique, respectively.

Biobeam-Multiplexed wave-optical simulations of light-sheet microscopy.

Sample-induced image-degradation remains an intricate wave-optical problem in light-sheet microscopy. Here we present biobeam, an open-source software package that enables simulation of operational light-sheet microscopes by combining data from 105-106 multiplexed and GPU-accelerated point-spread-function calculations. The wave-optical nature of these simulations leads to the faithful reproduction of spatially varying aberrations, diffraction artifacts, geometric image distortions, adaptive optics, and emergent wave-optical phenomena, and renders image-formation in light-sheet microscopy computationally tractable.

An Overview of data science uses in bioimage informatics.

This review aims at providing a practical overview of the use of statistical features and associated data science methods in bioimage informatics. To achieve a quantitative link between images and biological concepts, one typically replaces an object coming from an image (a segmented cell or intracellular object, a pattern of expression or localisation, even a whole image) by a vector of numbers. They range from carefully crafted biologically relevant measurements to features learnt through deep neural networks. This replacement allows for the use of practical algorithms for visualisation, comparison and inference, such as the ones from machine learning or multivariate statistics. While originating mainly, for biology, in high content screening, those methods are integral to the use of data science for the quantitative analysis of microscopy images to gain biological insight, and they are sure to gather more interest as the need to make sense of the increasing amount of acquired imaging data grows more pressing.

Stochastic approach to the molecular counting problem in superresolution microscopy.

Superresolution imaging methods--now widely used to characterize biological structures below the diffraction limit--are poised to reveal in quantitative detail the stoichiometry of protein complexes in living cells. In practice, the photophysical properties of the fluorophores used as tags in superresolution methods have posed a severe theoretical challenge toward achieving this goal. Here we develop a stochastic approach to enumerate fluorophores in a diffraction-limited area measured by superresolution microscopy. The method is a generalization of aggregated Markov methods developed in the ion channel literature for studying gating dynamics. We show that the method accurately and precisely enumerates fluorophores in simulated data while simultaneously determining the kinetic rates that govern the stochastic photophysics of the fluorophores to improve the prediction's accuracy. This stochastic method overcomes several critical limitations of temporal thresholding methods.

Building cell models and simulations from microscope images.

The use of fluorescence microscopy has undergone a major revolution over the past twenty years, both with the development of dramatic new technologies and with the widespread adoption of image analysis and machine learning methods. Many open source software tools provide the ability to use these methods in a wide range of studies, and many molecular and cellular phenotypes can now be automatically distinguished. This article presents the next major challenge in microscopy automation, the creation of accurate models of cell organization directly from images, and reviews the progress that has been made towards this challenge.

Fast, three-dimensional super-resolution imaging of live cells.

We report super-resolution fluorescence imaging of live cells with high spatiotemporal resolution using stochastic optical reconstruction microscopy (STORM). By labeling proteins either directly or via SNAP tags with photoswitchable dyes, we obtained two-dimensional (2D) and 3D super-resolution images of living cells, using clathrin-coated pits and the transferrin cargo as model systems. Bright, fast-switching probes enabled us to achieve 2D imaging at spatial resolutions of ∼25 nm and temporal resolutions as fast as 0.5 s. We also demonstrated live-cell 3D super-resolution imaging. We obtained 3D spatial resolution of ∼30 nm in the lateral direction and ∼50 nm in the axial direction at time resolutions as fast as 1-2 s with several independent snapshots. Using photoswitchable dyes with distinct emission wavelengths, we also demonstrated two-color 3D super-resolution imaging in live cells. These imaging capabilities open a new window for characterizing cellular structures in living cells at the ultrastructural level.

Implementation of transportation distance for analyzing FLIM and FRET experiments.

Analysis of fluorescence lifetime imaging microscopy (FLIM) and Förster resonance energy transfer (FRET) experiments in living cells is usually based on mean lifetimes computations. However, these mean lifetimes can induce misinterpretations. We propose in this work the implementation of the transportation distance for FLIM and FRET experiments in vivo. This non-fitting indicator, which is easy to compute, reflects the similarity between two distributions and can be used for pixels clustering to improve the estimation of the FRET parameters. We study the robustness and the discriminating power of this transportation distance, both theoretically and numerically. In addition, a comparison study with the largely used mean lifetime differences is performed. We finally demonstrate practically the benefits of the transportation distance over the usual mean lifetime differences for both FLIM and FRET experiments in living cells.

Automated, portable, low-cost bright-field and fluorescence microscope with autofocus and autoscanning capabilities.

Optical microscopy is a simple, yet essential, imaging technology. Conventional laboratory-grade optical microscopes are bulky and costly, confining their use to within laboratory settings and restricting their accessibility in regions of limited resources. With the aim of overcoming these limitations, we have realized a portable, low-cost, and highly automated optical microscope that integrates mass-manufactured components, including light-emitting diodes, a web camera, optical disk drives, and a microcontroller. Our implementation is capable of bright-field and fluorescence imaging with micrometer-scale resolution and controlled mechanical actuation of both the lens and sample. We interface the lighting, image capture, and mechanical actuators of the microscope into a single software environment, enabling automation of common microscope operations, such as image focusing and large-area sample visualization. Combination of mechanical actuation and software automation into a compact, low-cost microscope system is an important initial step toward the goal of making optical microscopy universally accessible, portable, and easy to use.

Fast, background-free, 3D super-resolution optical fluctuation imaging (SOFI).

Super-resolution optical microscopy is a rapidly evolving area of fluorescence microscopy with a tremendous potential for impacting many fields of science. Several super-resolution methods have been developed over the last decade, all capable of overcoming the fundamental diffraction limit of light. We present here an approach for obtaining subdiffraction limit optical resolution in all three dimensions. This method relies on higher-order statistical analysis of temporal fluctuations (caused by fluorescence blinking/intermittency) recorded in a sequence of images (movie). We demonstrate a 5-fold improvement in spatial resolution by using a conventional wide-field microscope. This resolution enhancement is achieved in iterative discrete steps, which in turn allows the evaluation of images at different resolution levels. Even at the lowest level of resolution enhancement, our method features significant background reduction and thus contrast enhancement and is demonstrated on quantum dot-labeled microtubules of fibroblast cells.

Diagnostics of autoimmune bullous diseases in German dermatology departments.

BACKGROUND: No consistent data are available on the currently employed diagnostic tools for autoimmune bullous diseases in Germany. The aim of this survey was to describe currently performed diagnostic methods for bullous autoimmune diseases in German dermatology departments. METHODS: A standardized questionnaire evaluated the available diagnostic methods i. e. direct immunofluorescence microscopy (IFM), indirect IFM, commercial ELISA systems, and non-commercial serological tests as well as the number of samples per year in all 34 university and 39 non-university dermatology departments. RESULTS: The overall return rate was 89 %, 100 % and 79 % for the university and non-university departments, respectively. Direct IFM was the most frequently used method and was applied in 98 % of the responding departments. In 74 % of the responding departments, indirect IFM was used mainly on monkey esophagus and human salt-split skin. Commercial ELISA systems were employed in 58 % of the clinics; all of them used anti-desmoglein ELISA, while anti-BP180 and anti-BP230 ELISA were established in 49 % and 48 % of departments, respectively. Non-commercial analytic methods were only performed in 22 % of the departments. CONCLUSIONS: The high return rate of this survey allows a relatively precise description of the current diagnostic methods used in German dermatology departments. Standard diagnostic tests are available nationwide and in bullous pemphigoid and pemphigus, the antigen-specific detection of autoantibodies is routinely performed in half of the departments. Rare disorders may be diagnosed by cooperation with some specialized centers.

High-density localization of active molecules using Structured Sparse Model and Bayesian Information Criterion.

Localization-based super-resolution microscopy (or called localization microscopy) rely on repeated imaging and localization of active molecules, and the spatial resolution enhancement of localization microscopy is built upon the sacrifice of its temporal resolution. Developing algorithms for high-density localization of active molecules is a promising approach to increase the speed of localization microscopy. Here we present a new algorithm called SSM_BIC for such purpose. The SSM_BIC combines the advantages of the Structured Sparse Model (SSM) and the Bayesian Information Criterion (BIC). Through simulation and experimental studies, we evaluate systematically the performance between the SSM_BIC and the conventional Sparse algorithm in high-density localization of active molecules. We show that the SSM_BIC is superior in processing single molecule images with weak signal embedded in strong background.

Depth-resolved image mapping spectrometer (IMS) with structured illumination.

We present a depth-resolved Image Mapping Spectrometer (IMS) which is capable of acquiring 4D (x, y, z, λ) datacubes. Optical sectioning is implemented by structured illumination. The device's spectral imaging performance is demonstrated in a multispectral microsphere and mouse kidney tissue fluorescence imaging experiment. We also compare quantitatively the depth-resolved IMS with a hyperspectral confocal microscope (HCM) in a standard fluorescent bead imaging experiment. The comparison results show that despite the use of a light source with four orders of magnitude lower intensity in the IMS than that in the HCM, the image signal-to-noise ratio acquired by the IMS is 2.6 times higher than that achieved by the equivalent confocal approach.

A sensitive and specific ES-31 antigen detection based fluorometric assay for confirmation of Mycobacterium tuberculosis in cell culture.

Confirmation of presence of M. tuberculosis bacilli on microscopic examination is very important in diagnosis of tuberculosis. The present study was undertaken to find the usefulness of mycobacterial ES-31 serine protease as a marker to detect tuberculosis bacilli using fluorescein isothiocyanate conjugated anti-ES-31 serine protease antibody. This immunofluorescence method was compared with Ziehl-Neelsen and auramine-O staining methods for detection of tuberculosis bacilli. Slides were prepared for each serially diluted tuberculosis H37Ra bacilli (1 x 10(7) bacilli/ml to 5 bacilli/ml). Slides for each dilution group were stained by ZN method, auramine-O and immunostaining methods using fluorescein isothiocyanate conjugated anti-ES-31 serine protease antibody. ZN staining method showed efficacy for detection of M. tuberculosis H37Ra upto 1 x 10(4) bacilli/ml while auramine-O method showed upto 1 x 10(2) bacilli/ml. The presence of bacilli was indicated by green fluorescence on immunostaining using anti-ES-31 antibody conjugate and this method was effective upto 10 bacilli/ml. The slides which were negative for ZN (1 x 10(3) cells/ml) and auramine-O (100 cells/ml) method showed positivity on restaining with immunofluorescent staining method. The results of this preliminary study showed that immunofluorescent staining method using specific anti-ES-31 antibody conjugate was more sensitive for detection of tuberculosis bacilli than ZN and auramine-O methods in samples of laboratory strain. The utility of this method will be studied further in clinical specimens.