A workingperson's guide to deconvolution in light microscopy

PML mutants from arsenic-resistant patients reveal SUMO1-TOPORS and SUMO2/3-RNF4 degradation pathways

Arsenic effectively treats acute promyelocytic leukemia by inducing SUMO and ubiquitin-dependent degradation of the promyelocytic leukemia (PML)-retinoic acid receptor alpha oncogenic fusion protein. However, some patients relapse with arsenic-resistant disease because of missense mutations in PML. To determine the mechanistic basis for arsenic resistance, PML-/- cells were reconstituted with YFP fusions of wild-type PML-V and two common patient mutants: A216T and L217F. Both mutants were resistant to degradation by arsenic but for different biochemical reasons. Arsenic did not trigger SUMOylation of A216T PML, which failed to recruit the SUMO-targeting ubiquitin ligases RNF4 and TOPORS. L217F PML did respond with increased SUMO2/3 conjugation that facilitated RNF4 engagement but failed to reach the threshold of SUMO1 conjugation required to recruit TOPORS. Thus, neither mutant accumulated the appropriate polyubiquitin signal required for p97 binding. These PML mutants have revealed a convergence of SUMO1, SUMO2/3, TOPORS, and RNF4 that facilitates the arsenic-induced degradation of PML.

Making sense of blobs, whorls, and shades: methods for label-free, inverse imaging in bright-field optical microscopy

Despite its long history and widespread use, conventional bright-field optical microscopy has received recent attention as an excellent option to perform accurate, label-free, imaging of biological objects. As with any imaging system, bright-field produces an ill-defined representation of the specimen, in this case characterized by intertwined phase and amplitude in image formation, invisibility of phase objects at exact focus, and both positive and negative contrast present in images. These drawbacks have prevented the application of bright-field to the accurate imaging of unlabeled specimens. To address these challenges, a variety of methods using hardware, software or both have been developed, with the goal of providing solutions to the inverse imaging problem set in bright-field. We revise the main operating principles and characteristics of bright-field microscopy, followed by a discussion of the solutions (and potential limitations) to reconstruction in two dimensions (2D). We focus on methods based on conventional optics, including defocusing microscopy, transport of intensity, ptychography and deconvolution. Advances to achieving three-dimensional (3D) bright-field imaging are presented, including methods that exploit multi-view reconstruction, physical modeling, deep learning and conventional digital image processing. Among these techniques, optical sectioning in bright-field microscopy (OSBM) constitutes a direct approach that captures z-image stacks using a standard microscope and applies digital filters in the spatial domain, yielding inverse-imaging solutions in 3D. Finally, additional techniques that expand the capabilities of bright-field are discussed. Label-free, inverse imaging in conventional optical microscopy thus emerges as a powerful biophysical tool for accurate 2D and 3D imaging of biological samples.

STED super-resolution microscopy of mitochondrial translocases

The mitochondrial translocases of the outer membrane (TOM) and of the inner membrane (TIM) act together to facilitate the import of nuclear-encoded proteins across the mitochondrial membranes. Stimulated Emission Depletion (STED) super-resolution microscopy enables the in situ imaging of such complexes in single cells at sub-diffraction resolution. STED microscopy requires only conventional sample preparation techniques and provides super-resolved raw data without the need for further image processing. In this chapter, we provide a detailed example protocol for STED microscopy of TOM20 and mitochondrial DNA in fixed mammalian cells. The protocol includes instructions on sample preparation for immunolabeling, including cell line selection, fixation, permeabilization, blocking, labeling and mounting, but also recommendations for sample and microscope performance evaluation. The protocol is supplemented by considerations on key factors that influence the quality of the final image and also includes some considerations for the analysis of the acquired images. While the protocol described here is aimed at imaging TOM20 and DNA, it contains all the information for an immediate adaptation to other cellular targets.

High-resolution cell imaging using white light phase shifting interferometry and iterative phase deconvolution

An optimization algorithm is presented for the deconvolution of a complex field to improve the resolution and accuracy of quantitative phase imaging (QPI). A high-resolution phase map can be recovered by solving a constrained optimization problem of deconvolution using a complex gradient operator. The method is demonstrated on phase measurements of samples using a white light based phase shifting interferometry (WLPSI) method. The application of the algorithm on real and simulated objects shows a significant resolution and contrast improvement. Experiments performed on Escherichia coli bacterium have revealed its sub-cellular structures that were not visible in the raw WLPSI images obtained using a five phase shifting method. These features can give valuable insights into the structures and functioning of biological cells. The algorithm is simple in implementation and can be incorporated into other QPI modalities .

Multiplexed 3D Analysis of Immune States and Niches in Human Tissue

Tissue homeostasis and the emergence of disease are controlled by changes in the proportions of resident and recruited cells, their organization into cellular neighbourhoods, and their interactions with acellular tissue components. Highly multiplexed tissue profiling (spatial omics)1 makes it possible to study this microenvironment in situ, usually in 4-5 micron thick sections (the standard histopathology format)2. Microscopy-based tissue profiling is commonly performed at a resolution sufficient to determine cell types but not to detect subtle morphological features associated with cytoskeletal reorganisation, juxtracrine signalling, or membrane trafficking3. Here we describe a high-resolution 3D imaging approach able to characterize a wide variety of organelles and structures at sub-micron scale while simultaneously quantifying millimetre-scale spatial features. This approach combines cyclic immunofluorescence (CyCIF) imaging4 of over 50 markers with confocal microscopy of archival human tissue thick enough (30-40 microns) to fully encompass two or more layers of intact cells. 3D imaging of entire cell volumes substantially improves the accuracy of cell phenotyping and allows cell proximity to be scored using plasma membrane apposition, not just nuclear position. In pre-invasive melanoma in situ5, precise phenotyping shows that adjacent melanocytic cells are plastic in state and participate in tightly localised niches of interferon signalling near sites of initial invasion into the underlying dermis. In this and metastatic melanoma, mature and precursor T cells engage in an unexpectedly diverse array of juxtracrine and membrane-membrane interactions as well as looser "neighbourhood" associations6 whose morphologies reveal functional states. These data provide new insight into the transitions occurring during early tumour formation and immunoediting and demonstrate the potential for phenotyping of tissues at a level of detail previously restricted to cultured cells and organoids.

Quantitative super-resolution microscopy reveals the differences in the nanoscale distribution of nuclear phosphatidylinositol 4,5-bisphosphate in human healthy skin and skin warts

Introduction: Imaging of human clinical formalin-fixed paraffin-embedded (FFPE) tissue sections provides insights into healthy and diseased states and therefore represents a valuable resource for basic research, as well as for diagnostic and clinical purposes. However, conventional light microscopy does not allow to observe the molecular details of tissue and cell architecture due to the diffraction limit of light. Super-resolution microscopy overcomes this limitation and provides access to the nanoscale details of tissue and cell organization. Methods: Here, we used quantitative multicolor stimulated emission depletion (STED) nanoscopy to study the nanoscale distribution of the nuclear phosphatidylinositol 4,5-bisphosphate (nPI(4,5)P2) with respect to the nuclear speckles (NS) marker SON. Results: Increased nPI(4,5)P2 signals were previously linked to human papillomavirus (HPV)-mediated carcinogenesis, while NS-associated PI(4,5)P2 represents the largest pool of nPI(4,5)P2 visualized by staining and microscopy. The implementation of multicolor STED nanoscopy in human clinical FFPE skin and wart sections allowed us to provide here the quantitative evidence for higher levels of NS-associated PI(4,5)P2 in HPV-induced warts compared to control skin. Discussion: These data expand the previous reports of HPV-induced increase of nPI(4,5)P2 levels and reveal for the first time the functional, tissue-specific localization of nPI(4,5)P2 within NS in clinically relevant samples. Moreover, our approach is widely applicable to other human clinical FFPE tissues as an informative addition to the classical histochemistry.

The p97/VCP segregase is essential for arsenic-induced degradation of PML and PML-RARA

Acute Promyelocytic Leukemia is caused by expression of the oncogenic Promyelocytic Leukemia (PML)-Retinoic Acid Receptor Alpha (RARA) fusion protein. Therapy with arsenic trioxide results in degradation of PML-RARA and PML and cures the disease. Modification of PML and PML-RARA with SUMO and ubiquitin precedes ubiquitin-mediated proteolysis. To identify additional components of this pathway, we performed proteomics on PML bodies. This revealed that association of p97/VCP segregase with PML bodies is increased after arsenic treatment. Pharmacological inhibition of p97 altered the number, morphology, and size of PML bodies, accumulated SUMO and ubiquitin modified PML and blocked arsenic-induced degradation of PML-RARA and PML. p97 localized to PML bodies in response to arsenic, and siRNA-mediated depletion showed that p97 cofactors UFD1 and NPLOC4 were critical for PML degradation. Thus, the UFD1-NPLOC4-p97 segregase complex is required to extract poly-ubiquitinated, poly-SUMOylated PML from PML bodies, prior to degradation by the proteasome.

Optimised generalized polarisation analysis of C-laurdan reveals clear order differences between T cell membrane compartments

Heterogenous packing of plasma membrane lipids is important for cellular processes like signalling, adhesion and sorting of membrane components. Solvatochromic membrane fluorophores that respond to changes from liquid-ordered (l_o) phase to liquid-disordered (l_d) by red shifts in their emission spectra are often used to assess lipid packing. Their response can be quantified using generalized polarisation (GP) using fluorescence microscopy images from two emission ranges, preferably from a region of interest (ROI) limited to a specific membrane compartment. However, image quality is limited by Poisson noise and convolution by the point spread function of the imaging system. Examining GP-analysis of C-laurdan labelled T cells using the image restoration procedure deconvolution, we demonstrate that deconvolution substantially improves the image resolution by making the plasma membrane clearly discernible and facilitating plasma membrane ROI selection. We conclude that automatic ROI selection has advantages over manual ROI selection when it comes to reproducibility and speed, but reliable GP-measurements can also be obtained by manually demarcated ROIs. We find that deconvolution enhances the difference in GP-values between the plasma and intracellular membranes and demonstrate that moving an intensity defined plasma membrane ROI outwards from the cell further improves this differentiation. By systematically changing the key deconvolution regularization parameter signal to noise, we establish a protocol for deconvolution optimisation applicable to any solvatochromic dye and imaging system. The image processing and ROI selection protocol presented improves both the resolution and precision of GP-measurement and will enable detection of smaller changes in membrane order than is currently achievable.

Practical considerations for quantitative light sheet fluorescence microscopy

Fluorescence microscopy has evolved from a purely observational tool to a platform for quantitative, hypothesis-driven research. As such, the demand for faster and less phototoxic imaging modalities has spurred a rapid growth in light sheet fluorescence microscopy (LSFM). By restricting the excitation to a thin plane, LSFM reduces the overall light dose to a specimen while simultaneously improving image contrast. However, the defining characteristics of light sheet microscopes subsequently warrant unique considerations in their use for quantitative experiments. In this Perspective, we outline many of the pitfalls in LSFM that can compromise analysis and confound interpretation. Moreover, we offer guidance in addressing these caveats when possible. In doing so, we hope to provide a useful resource for life scientists seeking to adopt LSFM to quantitatively address complex biological hypotheses.

Incorporating the image formation process into deep learning improves network performance

We present Richardson-Lucy network (RLN), a fast and lightweight deep learning method for three-dimensional fluorescence microscopy deconvolution. RLN combines the traditional Richardson-Lucy iteration with a fully convolutional network structure, establishing a connection to the image formation process and thereby improving network performance. Containing only roughly 16,000 parameters, RLN enables four- to 50-fold faster processing than purely data-driven networks with many more parameters. By visual and quantitative analysis, we show that RLN provides better deconvolution, better generalizability and fewer artifacts than other networks, especially along the axial dimension. RLN outperforms classic Richardson-Lucy deconvolution on volumes contaminated with severe out of focus fluorescence or noise and provides four- to sixfold faster reconstructions of large, cleared-tissue datasets than classic multi-view pipelines. We demonstrate RLN's performance on cells, tissues and embryos imaged with widefield-, light-sheet-, confocal- and super-resolution microscopy.

Label free optical transmission tomography for biosystems: intracellular structures and dynamics

There is an increasing need for label free methods that could reveal intracellular structures and dynamics. In this context, we develop a new optical tomography method working in transmission - full-field optical transmission tomography (FF-OTT). The method can measure the forward scattering signals and reveals the time-dependent metabolic signals in living cells. FF-OTT is a common path interferometer taking advantage of the Gouy phase shift - a π phase shift that the light wave experiences around the focus. By modulating the position of the focus one can alter the phase of the scattered light. Demodulation of images with different phases rejects the background and enhances the light from the depth-of-field, thus producing an optical section. We test FF-OTT by imaging single-cell diatoms and ex vivo biological samples. In fresh samples, we show that the intracellular motions create visible intensity fluctuations in FF-OTT so that the method is able to reveal a metabolic dynamic contrast. FF-OTT was found to be an efficient label free technique that can be readily implemented thanks to a robust common-path speckle-free interferometer design using an incoherent light source.

Simulation-driven learning: a deep learning approach for image scanning microscopy via physical imaging models

Image reconstruction based on deep learning has become an effective tool in fluorescence microscopy. Most deep learning reconstruction methods ignore the mechanism of the imaging process where a large number of datasets are required. In addition, a lot of time is spent solving the aliasing problem from multi-scaled image pairs for data pre-processing. Here we demonstrate an improved generative adversarial network for image scanning microscopy (ISM) that can be trained by simulation data and has good generalization. Based on physical imaging models, this method can generate matching image pairs from simulation images and uses them as datasets for network training, without capturing a large number of real ISM images and avoiding image alignment preprocessing. Simulation and experimental results show that this simulation data-driven method improves the imaging quality of conventional microscopic images and reduces the cost of experiments. This method provides inspiration for optimizing network generalizability of the deep learning network.

Imaging the Actin Cytoskeleton in Live Budding Yeast Cells

Although budding yeast, Saccharomyces cerevisiae, is widely used as a model organism in biological research, studying cell biology in yeast was hindered due to its small size, rounded morphology, and cell wall. However, with improved techniques, researchers can acquire high-resolution images and carry out rapid multidimensional analysis of a yeast cell. As a result, imaging in yeast has emerged as an important tool to study cytoskeletal organization, function, and dynamics. This chapter describes techniques and approaches for visualizing the actin cytoskeleton in live yeast cells.

Nanometer-Scale Molecular Mapping by Super-resolution Fluorescence Microscopy

The structural organization of macromolecules and their association in assemblies and organelles is key to understand cellular function. Super-resolution fluorescence microscopy has expanded our toolbox for examining such nanometer-scale cellular structures, by enabling positional mapping of proteins in situ. Here, we detail the workflow to build nanometer-scale maps focusing on two complementary super-resolution modalities: structured illumination microscopy (SIM) and stochastic optical reconstruction microscopy (STORM).

Live-cell visualization of cytochrome c: a tool to explore apoptosis

Apoptosis dysfunction is associated with several malignancies, including cancer and autoimmune diseases. Apoptosis restoration could be an attractive therapeutic approach to those diseases. Mitochondrial outer membrane permeabilization is regarded as the point of no return in the 'classical' apoptosis triggering pathway. Cytoplasmic release of cytochrome c (cyt c), a mitochondrial electron transporter, is a prominent indicator of such critical step. Therefore, visualizing cyt c efflux in living cells is a convenient approach to address apoptosis triggering and monitor performance of apoptosis restoration strategies. Recent years have been prolific in the development of biosensors to visualize cyt c mitochondrial efflux in living cells, by fluorescence microscopy. These biosensors specifically detect endogenous, untagged cyt c, while showing efficient cellular uptake and reduced cell toxicity. A common aspect is their fluorescence quenching in the absence or presence of bound cyt c, resulting in two main biosensor types: 'turn ON' and 'turn OFF'. In some of these systems, fluorescence intensity of fluorophore-bound aptamers is enhanced upon cyt c binding. In others, cyt c binding to quantum dots quenches their fluorescence. In the present minireview, I describe these biosensors and briefly introduce some hypotheses that could be addressed using these novel tools.

Imaging the Actin Cytoskeleton in Fixed Budding Yeast Cells

Budding yeast, Saccharomyces cerevisiae, is an appealing model organism to study the organization and function of the actin cytoskeleton. With the advent of techniques to perform high-resolution, multidimensional analysis of the yeast cell, imaging of yeast has emerged as an important tool for research on the cytoskeleton. This chapter describes techniques and approaches for visualizing the actin cytoskeleton in fixed yeast cells with wide-field and super-resolution fluorescence microscopy.

3D test sample for the calibration and quality control of stimulated emission depletion (STED) and confocal microscopes

Multiple samples are required to monitor and optimize the quality and reliability of quantitative measurements of stimulated emission depletion (STED) and confocal microscopes. Here, we present a single sample to calibrate these microscopes, align their laser beams and measure their point spread function (PSF) in 3D. The sample is composed of a refractive index matched colloidal crystal of silica beads with fluorescent and gold cores. The microscopes can be calibrated in three dimensions using the periodicity of the crystal; the alignment of the laser beams can be checked using the reflection of the gold cores; and the PSF can be measured at multiple positions and depths using the fluorescent cores. It is demonstrated how this sample can be used to visualize and improve the quality of STED and confocal microscopy images. The sample is adjustable to meet the requirements of different NA objectives and microscopy techniques and additionally can be used to evaluate refractive index mismatches as a function of depth quantitatively.

cAMP signaling through protein kinase A and Epac2 induces substance P release in the rat spinal cord

Using neurokinin 1 receptor (NK1R) internalization to measure of substance P release in rat spinal cord slices, we found that it was induced by the adenylyl cyclase (AC) activator forskolin, by the protein kinase A (PKA) activators 6-Bnz-cAMP and 8-Br-cAMP, and by the activator of exchange protein activated by cAMP (Epac) 8-pCPT-2-O-Me-cAMP (CPTOMe-cAMP). Conversely, AC and PKA inhibitors decreased substance P release induced by electrical stimulation of the dorsal root. Therefore, the cAMP signaling pathway mediates substance P release in the dorsal horn. The effects of forskolin and 6-Bnz-cAMP were not additive with NMDA-induced substance P release and were decreased by the NMDA receptor blocker MK-801. In cultured dorsal horn neurons, forskolin increased NMDA-induced Ca²⁺ entry and the phosphorylation of the NR1 and NR2B subunits of the NMDA receptor. Therefore, cAMP-induced substance P release is mediated by the activating phosphorylation by PKA of NMDA receptors. Voltage-gated Ca²⁺ channels, but not by TRPV1 or TRPA1, also contributed to cAMP-induced substance P release. Activation of PKA was required for the effects of forskolin and the three cAMP analogs. Epac2 contributed to the effects of forskolin and CPTOMe-cAMP, signaling through a Raf - mitogen-activated protein kinase pathway to activate Ca²⁺ channels. Epac1 inhibitors induced NK1R internalization independently of substance P release. In rats with latent sensitization to pain, the effect of 6-Bnz-cAMP was unchanged, whereas the effect of forskolin was decreased due to the loss of the stimulatory effect of Epac2. Hence, substance P release induced by cAMP decreases during pain hypersensitivity.

Application of Fast Non-Local Means Algorithm for Noise Reduction Using Separable Color Channels in Light Microscopy Images

The purpose of this study is to evaluate the various control parameters of a modeled fast non-local means (FNLM) noise reduction algorithm which can separate color channels in light microscopy (LM) images. To achieve this objective, the tendency of image characteristics with changes in parameters, such as smoothing factors and kernel and search window sizes for the FNLM algorithm, was analyzed. To quantitatively assess image characteristics, the coefficient of variation (COV), blind/referenceless image spatial quality evaluator (BRISQUE), and natural image quality evaluator (NIQE) were employed. When high smoothing factors and large search window sizes were applied, excellent COV and unsatisfactory BRISQUE and NIQE results were obtained. In addition, all three evaluation parameters improved as the kernel size increased. However, the kernel and search window sizes of the FNLM algorithm were shown to be dependent on the image processing time (time resolution). In conclusion, this work has demonstrated that the FNLM algorithm can effectively reduce noise in LM images, and parameter optimization is important to achieve the algorithm's appropriate application.

DVDeconv: An Open-Source MATLAB Toolbox for Depth-Variant Asymmetric Deconvolution of Fluorescence Micrographs

To investigate the cellular structure, biomedical researchers often obtain three-dimensional images by combining two-dimensional images taken along the z axis. However, these images are blurry in all directions due to diffraction limitations. This blur becomes more severe when focusing further inside the specimen as photons in deeper focus must traverse a longer distance within the specimen. This type of blur is called depth-variance. Moreover, due to lens imperfection, the blur has asymmetric shape. Most deconvolution solutions for removing blur assume depth-invariant or x-y symmetric blur, and presently, there is no open-source for depth-variant asymmetric deconvolution. In addition, existing datasets for deconvolution microscopy also assume invariant or x-y symmetric blur, which are insufficient to reflect actual imaging conditions. DVDeconv, that is a set of MATLAB functions with a user-friendly graphical interface, has been developed to address depth-variant asymmetric blur. DVDeconv includes dataset, depth-variant asymmetric point spread function generator, and deconvolution algorithms. Experimental results using DVDeconv reveal that depth-variant asymmetric deconvolution using DVDeconv removes blurs accurately. Furthermore, the dataset in DVDeconv constructed can be used to evaluate the performance of microscopy deconvolution to be developed in the future.

Three-dimensional volumetric deconvolution in coherent optics and holography

Methods of three-dimensional deconvolution (3DD) or volumetric deconvolution of optical complex-valued wavefronts diffracted by 3D samples with the 3D point spread function are presented. Particularly, the quantitative correctness of the recovered 3D sample distributions is addressed. Samples consisting of point-like objects can be retrieved from their 3D diffracted wavefronts with non-iterative (Wiener filter) 3DD. Continuous extended samples, including complex-valued (phase) samples, can be retrieved with iterative (Gold and Richardson-Lucy) 3DD algorithms. It is shown that quantitatively correct 3D sample distribution can be recovered only with iterative 3DD, and with the optimal protocols provided. It is demonstrated that 3DD can improve the lateral resolution to the resolution limit, and the axial resolution can be at least four times better than the resolution limit. The presented 3DD methods of complex-valued optical fields can be applied for 3D optical imaging and holography.

Effective image visualization for publications - a workflow using open access tools and concepts

Today, 25% of figures in biomedical publications contain images of various types, e.g. photos, light or electron microscopy images, x-rays, or even sketches or drawings. Despite being widely used, published images may be ineffective or illegible since details are not visible, information is missing or they have been inappropriately processed. The vast majority of such imperfect images can be attributed to the lack of experience of the authors as undergraduate and graduate curricula lack courses on image acquisition, ethical processing, and visualization.  Here we present a step-by-step image processing workflow for effective and ethical image presentation. The workflow is aimed to allow novice users with little or no prior experience in image processing to implement the essential steps towards publishing images. The workflow is based on the open source software Fiji, but its principles can be applied with other software packages. All image processing steps discussed here, and complementary suggestions for image presentation, are shown in an accessible "cheat sheet"-style format, enabling wide distribution, use, and adoption to more specific needs.

Effective image visualization for publications - a workflow using open access tools and concepts

Today, 25% of figures in biomedical publications contain images of various types, e.g. photos, light or electron microscopy images, x-rays, or even sketches or drawings. Despite being widely used, published images may be ineffective or illegible since details are not visible, information is missing or they have been inappropriately processed. The vast majority of such imperfect images can be attributed to the lack of experience of the authors as undergraduate and graduate curricula lack courses on image acquisition, ethical processing, and visualization.  Here we present a step-by-step image processing workflow for effective and ethical image presentation. The workflow is aimed to allow novice users with little or no prior experience in image processing to implement the essential steps towards publishing images. The workflow is based on the open source software Fiji, but its principles can be applied with other software packages. All image processing steps discussed here, and complementary suggestions for image presentation, are shown in an accessible "cheat sheet"-style format, enabling wide distribution, use, and adoption to more specific needs.

Biosynthesis of medicinal tropane alkaloids in yeast

Tropane alkaloids from nightshade plants are neurotransmitter inhibitors that are used for treating neuromuscular disorders and are classified as essential medicines by the World Health Organization1,2. Challenges in global supplies have resulted in frequent shortages of these drugs3,4. Further vulnerabilities in supply chains have been revealed by events such as the Australian wildfires5 and the COVID-19 pandemic6. Rapidly deployable production strategies that are robust to environmental and socioeconomic upheaval7,8 are needed. Here we engineered baker's yeast to produce the medicinal alkaloids hyoscyamine and scopolamine, starting from simple sugars and amino acids. We combined functional genomics to identify a missing pathway enzyme, protein engineering to enable the functional expression of an acyltransferase via trafficking to the vacuole, heterologous transporters to facilitate intracellular routing, and strain optimization to improve titres. Our integrated system positions more than twenty proteins adapted from yeast, bacteria, plants and animals across six sub-cellular locations to recapitulate the spatial organization of tropane alkaloid biosynthesis in plants. Microbial biosynthesis platforms can facilitate the discovery of tropane alkaloid derivatives as new therapeutic agents for neurological disease and, once scaled, enable robust and agile supply of these essential medicines.

3D Correlative Cryo-Structured Illumination Fluorescence and Soft X-ray Microscopy Elucidates Reovirus Intracellular Release Pathway

Imaging of biological matter across resolution scales entails the challenge of preserving the direct and unambiguous correlation of subject features from the macroscopic to the microscopic level. Here, we present a correlative imaging platform developed specifically for imaging cells in 3D under cryogenic conditions by using X-rays and visible light. Rapid cryo-preservation of biological specimens is the current gold standard in sample preparation for ultrastructural analysis in X-ray imaging. However, cryogenic fluorescence localization methods are, in their majority, diffraction-limited and fail to deliver matching resolution. We addressed this technological gap by developing an integrated, user-friendly platform for 3D correlative imaging of cells in vitreous ice by using super-resolution structured illumination microscopy in conjunction with soft X-ray tomography. The power of this approach is demonstrated by studying the process of reovirus release from intracellular vesicles during the early stages of infection and identifying intracellular virus-induced structures.

Pushing the boundaries of optoacoustic microscopy by total impulse response characterization

Optical microscopy improves in resolution and signal-to-noise ratio by correcting for the system’s point spread function; a measure of how a point source is resolved, typically determined by imaging nanospheres. Optical-resolution optoacoustic (photoacoustic) microscopy could be similarly corrected, especially to account for the spatially-dependent signal distortions induced by the acoustic detection and the time-resolved and bi-polar nature of optoacoustic signals. Correction algorithms must therefore include the spatial dependence of signals’ origins and profiles in time, i.e. the four-dimensional total impulse response (TIR). However, such corrections have been so far impeded by a lack of efficient TIR-characterization methods. We introduce high-quality TIR determination based on spatially-distributed optoacoustic point sources (SOAPs), produced by scanning an optical focus on an axially-translatable 250 nm gold layer. Using a spatially-dependent TIR-correction improves the signal-to-noise ratio by >10 dB and the axial resolution by ~30%. This accomplishment displays a new performance paradigm for optoacoustic microscopy.

Characterizing the total impulse response (TIR) of photoacoustic microscopes has been challenging due to difficulties distributing appropriate point sources. Here, the authors present a method for 3D generation of spatially-distributed optoacoustic point sources and show that subsequent TIR correction results in improved image quality.

Deep learning-enhanced fluorescence microscopy via degeneration decoupling

Deep learning-based reconstruction has emerged as an effective tool in fluorescence microscopy, with the potential to resolve diffraction-limited structures. However, most deep-learning reconstruction methods employed an end-to-end strategy, which ignored physical laws in the imaging process and made the preparation of training data highly challenging as well. In this study, we have proposed a novel deconvolution algorithm based on an imaging model, deep-learning priors and the alternating direction method of multipliers. This scheme decouples the reconstruction into two separate sub-problems, one for deblurring and one for restraining noise and artifacts. As a result of the decoupling, we are able to introduce deep-learning image priors and a variance stabilizing transform against targeted image degeneration due to the low photon budget. Deep-learning priors are learned from the general image dataset, in which biological images do not have to be involved, and are more powerful than hand-designed ones. Moreover, the use of the imaging model ensures high fidelity and generalization. Experiments on various kinds of measurement data show that the proposed algorithm outperforms existing state-of-the-art deconvolution algorithms in resolution enhancement and generalization.

Tutorial: guidance for quantitative confocal microscopy

When used appropriately, a confocal fluorescence microscope is an excellent tool for making quantitative measurements in cells and tissues. The confocal microscope's ability to block out-of-focus light and thereby perform optical sectioning through a specimen allows the researcher to quantify fluorescence with very high spatial precision. However, generating meaningful data using confocal microscopy requires careful planning and a thorough understanding of the technique. In this tutorial, the researcher is guided through all aspects of acquiring quantitative confocal microscopy images, including optimizing sample preparation for fixed and live cells, choosing the most suitable microscope for a given application and configuring the microscope parameters. Suggestions are offered for planning unbiased and rigorous confocal microscope experiments. Common pitfalls such as photobleaching and cross-talk are addressed, as well as several troubling instrumentation problems that may prevent the acquisition of quantitative data. Finally, guidelines for analyzing and presenting confocal images in a way that maintains the quantitative nature of the data are presented, and statistical analysis is discussed. A visual summary of this tutorial is available as a poster (https://doi.org/10.1038/s41596-020-0307-7).

Imaging Platelet Processes and Function-Current and Emerging Approaches for Imaging in vitro and in vivo

Platelets are small anucleate cells that are essential for many biological processes including hemostasis, thrombosis, inflammation, innate immunity, tumor metastasis, and wound healing. Platelets circulate in the blood and in order to perform all of their biological roles, platelets must be able to arrest their movement at an appropriate site and time. Our knowledge of how platelets achieve this has expanded as our ability to visualize and quantify discreet platelet events has improved. Platelets are exquisitely sensitive to changes in blood flow parameters and so the visualization of rapid intricate platelet processes under conditions found in flowing blood provides a substantial challenge to the platelet imaging field. The platelet's size (~2 μm), rapid activation (milliseconds), and unsuitability for genetic manipulation, means that appropriate imaging tools are limited. However, with the application of modern imaging systems to study platelet function, our understanding of molecular events mediating platelet adhesion from a single-cell perspective, to platelet recruitment and activation, leading to thrombus (clot) formation has expanded dramatically. This review will discuss current platelet imaging techniques in vitro and in vivo, describing how the advancements in imaging have helped answer/expand on platelet biology with a particular focus on hemostasis. We will focus on platelet aggregation and thrombus formation, and how platelet imaging has enhanced our understanding of key events, highlighting the knowledge gained through the application of imaging modalities to experimental models in vitro and in vivo. Furthermore, we will review the limitations of current imaging techniques, and questions in thrombosis research that remain to be addressed. Finally, we will speculate how the same imaging advancements might be applied to the imaging of other vascular cell biological functions and visualization of dynamic cell-cell interactions.

Numerical approach for reducing out-of-focus light in bright-field fluorescence microscopy and superresolution speckle microscopy

The standard two-dimensional (2D) image recorded in bright-field fluorescence microscopy is rigorously modeled by a convolution process involving a three-dimensional (3D) sample and a 3D point spread function. We show on synthetic and experimental data that deconvolving the 2D image using the appropriate 3D point spread function reduces the contribution of the out-of-focus fluorescence, resulting in a better image contrast and resolution. This approach is particularly interesting for superresolution speckle microscopy, in which the resolution gain stems directly from the efficiency of the deconvolution of each speckle image.

Live-Cell Fluorescence Microscopy to Investigate Subcellular Protein Localization and Cell Morphology Changes in Bacteria

Investigations of factors influencing cell division and cell shape in bacteria are commonly performed in conjunction with high-resolution fluorescence microscopy as observations made at a population level may not truly reflect what occurs at a single cell level. Live-cell timelapse microscopy allows investigators to monitor the changes in cell division or cell morphology which provide valuable insights regarding subcellular localization of proteins and timing of gene expression, as it happens, to potentially aid in answering important biological questions. Here, we describe our protocol to monitor phenotypic changes in Bacillus subtilis and Staphylococcus aureus using a high-resolution deconvolution microscope. The objective of this report is to provide a simple and clear protocol that can be adopted by other investigators interested in conducting fluorescence microscopy experiments to study different biological processes in bacteria as well as other organisms.

Fluorescence anisotropy imaging in drug discovery

Non-invasive measurement of drug-target engagement can provide critical insights in the molecular pharmacology of small molecule drugs. Fluorescence polarization/fluorescence anisotropy measurements are commonly employed in protein/cell screening assays. However, the expansion of such measurements to the in vivo setting has proven difficult until recently. With the advent of high-resolution fluorescence anisotropy microscopy it is now possible to perform kinetic measurements of intracellular drug distribution and target engagement in commonly used mouse models. In this review we discuss the background, current advances and future perspectives in intravital fluorescence anisotropy measurements to derive pharmacokinetic and pharmacodynamic measurements in single cells and whole organs.

Soft X-ray tomography: virtual sculptures from cell cultures

Cellular complexity is represented best in high-spatial resolution, three-dimensional (3D) reconstructions. Soft X-ray tomography (SXT) generates detailed volumetric reconstructions of cells preserved in a near-to-native, frozen-hydrated state. SXT is broadly applicable and can image specimens ranging from bacteria to large mammalian cells. As a reference, we summarize light and electron microscopic methods. We then present an overview of SXT and discuss its role in cellular imaging. We detail the methods used to image biological specimens and present recent highlights that illustrate the capabilities of the technique. We conclude by discussing correlative imaging, specifically the combination of SXT and fluorescence microscopy performed on the same specimen. This correlated approach combines the structural morphology of a cell with its physiological characteristics to build a deeply informative composite view.

Quantitative Analysis of Nuclear Lamins Imaged by Super-Resolution Light Microscopy

The nuclear lamina consists of a dense fibrous meshwork of nuclear lamins, Type V intermediate filaments, and is ~14 nm thick according to recent cryo-electron tomography studies. Recent advances in light microscopy have extended the resolution to a scale allowing for the fine structure of the lamina to be imaged in the context of the whole nucleus. We review quantitative approaches to analyze the imaging data of the nuclear lamina as acquired by structured illumination microscopy (SIM) and single molecule localization microscopy (SMLM), as well as the requisite cell preparation techniques. In particular, we discuss the application of steerable filters and graph-based methods to segment the structure of the four mammalian lamin isoforms (A, C, B1, and B2) and extract quantitative information.

Improving the performance of computational ghost imaging by using a quadrant detector and digital micro-scanning

Computational ghost imaging systems reconstruct images using a single element detector, which measures the level of correlation between the scene and a set of projected patterns. The sequential nature of these measurements means that increasing the system frame-rate reduces the signal-to-noise ratio (SNR) of the captured images. Furthermore, a higher spatial resolution requires the projection of more patterns, and so both frame-rate and SNR suffer from the increase of the spatial resolution. In this work, we combat these limitations by developing a hybrid few-pixel imaging system that combines structured illumination with a quadrant photodiode detector. To further boost the SNR of our system, we employ digital micro-scanning of the projected patterns. Experimental results show that our proposed imaging system is capable of reconstructing images 4 times faster and with ~33% higher SNR than a conventional single-element computational ghost imaging system utilizing orthogonal Hadamard pattern projection. Our work demonstrates a computational imaging system in which there is a flexible trade-off between frame-rate, SNR and spatial resolution, and this trade-off can be optimized to match the requirements of different applications.

A cell-permeant small molecule for the super-resolution imaging of the endoplasmic reticulum in live cells

A simple BODIPY-based small molecule has been identified to selectively label the endoplasmic reticulum for high-resolution imaging with negligible cytotoxicity.

Which Elements to Build Co-localization Workflows? From Metrology to Analysis

Co-localization analysis is one of the main interests of users entering a facility with slides in hands and nice analysis perspectives in mind. While being available through most, if not all, analysis software, co-localization tools are mainly perceived as black boxes, fed with images, that will, hopefully, return (the expected) numbers.In this chapter, we will aim at deconstructing existing generic co-localization workflows, extracting elementary tools that may be reused and recombined to generate new workflows. By differentiating work cases, identifying co-localization reporters and the metrics others have been using, we aim at providing the audience with the elementary bricks and methods to build their really own co-localization workflows. A special emphasis is given on the preparatory phase where the acquisition system is assessed, using basic metrological tests.

On-the-fly estimation of a microscopy point spread function

A proper estimation of realistic point-spread function (PSF) in optical microscopy can significantly improve the deconvolution performance and assist the microscope calibration process. In this work, by exemplifying 3D wide-field fluorescence microscopy, we propose an approach for estimating the spherically aberrated PSF of a microscope, directly from the observed samples. The PSF, expressed as a linear combination of 4 basis functions, is obtained directly from the acquired image by minimizing a novel criterion, which is derived from the noise statistics in the microscope. We demonstrate the effectiveness of the PSF approximation model and of our estimation method using both simulations and real experiments that were carried out on quantum dots. The principle of our PSF estimation approach is sufficiently flexible to be generalized non-spherical aberrations and other microscope modalities.

Seh1 targets GATOR2 and Nup153 to mitotic chromosomes

In metazoa, the Nup107 complex (also known as the nucleoporin Y-complex) plays a major role in formation of the nuclear pore complex in interphase and is localised to kinetochores in mitosis. The Nup107 complex shares a single highly conserved subunit, Seh1 (also known as SEH1L in mammals) with the GATOR2 complex, an essential activator of mTORC1 kinase. mTORC1/GATOR2 has a central role in the coordination of cell growth and proliferation. Here, we use chemical genetics and quantitative chromosome proteomics to study the role of the Seh1 protein in mitosis. Surprisingly, Seh1 is not required for the association of the Nup107 complex with mitotic chromosomes, but it is essential for the association of both the GATOR2 complex and nucleoporin Nup153 with mitotic chromosomes. Our analysis also reveals a role for Seh1 at human centromeres, where it is required for efficient localisation of the chromosomal passenger complex (CPC). Furthermore, this analysis detects a functional interaction between the Nup107 complex and the small kinetochore protein SKAP (also known as KNSTRN).

Highlighted Article: The nucleoporin Seh1 is essential for the association of both the GATOR2 complex and the nucleoporin Nup153, but not the Nup107 complex, with mitotic chromosomes.

Analysing magnetism using scanning SQUID microscopy

Scanning superconducting quantum interference device microscopy (SSM) is a scanning probe technique that images local magnetic flux, which allows for mapping of magnetic fields with high field and spatial accuracy. Many studies involving SSM have been published in the last few decades, using SSM to make qualitative statements about magnetism. However, quantitative analysis using SSM has received less attention. In this work, we discuss several aspects of interpreting SSM images and methods to improve quantitative analysis. First, we analyse the spatial resolution and how it depends on several factors. Second, we discuss the analysis of SSM scans and the information obtained from the SSM data. Using simulations, we show how signals evolve as a function of changing scan height, SQUID loop size, magnetization strength, and orientation. We also investigated 2-dimensional autocorrelation analysis to extract information about the size, shape, and symmetry of magnetic features. Finally, we provide an outlook on possible future applications and improvements.

Resolution enhancement method for lensless in-line holographic microscope with spatially-extended light source

We propose a resolution enhancement method for lensless in-line holographic microscope (LIHM) with spatially-extended light source, where the resolution is normally deteriorated by the insufficient spatial coherence of the illumination. In our LIHM setup, a light-emitting diode (LED), which was a spatially-extended light source, directly illuminated the sample, and the in-line hologram were recorded by a CMOS imaging sensor located behind the sample. In our holographic reconstruction process, the in-line hologram was first deconvoled with a properly resized image of the LED illumination area, and then back-propagated with scalar diffraction formula to reconstruct the sample image. We studied the hologram forming process and showed that the additional deconvolution process besides normal scalar diffraction reconstruction in LIHM can effectively enhance the imaging resolution. The resolution enhancements capability was calibrated by numerical simulations and imaging experiments with the U.S. air force target as the sample. We also used our LIHM to image the wing of a green lacewing to further demonstrate the capability of our methods for practical imaging applications. Our methods provide a way for LIHM to achieve satisfactory resolution with less stringent requirement for spatial coherence of the source and could reduce the cost for compact imaging system.

Three-dimensional flame measurements with large field angle

A system for three-dimensional computed tomography of chemiluminescence was developed to measure flames over a large field angle. Nine gradient-index rods, with a 9 × 1 endoscope and only one camera are used. Its large field of view, simplicity, and low cost make it attractive for inner flow field diagnostics. To study the bokeh effect caused by the imaging system on reconstruction solutions, fluorescent beads were used to determine the blurring function. Experiments using a steady diffusion flame were conducted to validate the system. Three models, namely the clear-imaging, out-of-focus imaging, and deconvolution models, were utilized. Taking the bokeh effect into account, the results suggest that based on run-times the deconvolution model provides the best reconstruction accuracy without increasing computational time.

DeconvolutionLab2: An open-source software for deconvolution microscopy

Images in fluorescence microscopy are inherently blurred due to the limit of diffraction of light. The purpose of deconvolution microscopy is to compensate numerically for this degradation. Deconvolution is widely used to restore fine details of 3D biological samples. Unfortunately, dealing with deconvolution tools is not straightforward. Among others, end users have to select the appropriate algorithm, calibration and parametrization, while potentially facing demanding computational tasks. To make deconvolution more accessible, we have developed a practical platform for deconvolution microscopy called DeconvolutionLab. Freely distributed, DeconvolutionLab hosts standard algorithms for 3D microscopy deconvolution and drives them through a user-oriented interface. In this paper, we take advantage of the release of DeconvolutionLab2 to provide a complete description of the software package and its built-in deconvolution algorithms. We examine several standard algorithms used in deconvolution microscopy, notably: Regularized inverse filter, Tikhonov regularization, Landweber, Tikhonov-Miller, Richardson-Lucy, and fast iterative shrinkage-thresholding. We evaluate these methods over large 3D microscopy images using simulated datasets and real experimental images. We distinguish the algorithms in terms of image quality, performance, usability and computational requirements. Our presentation is completed with a discussion of recent trends in deconvolution, inspired by the results of the Grand Challenge on deconvolution microscopy that was recently organized.

Designing Image Analysis Pipelines in Light Microscopy: A Rational Approach

With the progress of microscopy techniques and the rapidly growing amounts of acquired imaging data, there is an increased need for automated image processing and analysis solutions in biological studies. Each new application requires the design of a specific image analysis pipeline, by assembling a series of image processing operations. Many commercial or free bioimage analysis software are now available and several textbooks and reviews have presented the mathematical and computational fundamentals of image processing and analysis. Tens, if not hundreds, of algorithms and methods have been developed and integrated into image analysis software, resulting in a combinatorial explosion of possible image processing sequences. This paper presents a general guideline methodology to rationally address the design of image processing and analysis pipelines. The originality of the proposed approach is to follow an iterative, backwards procedure from the target objectives of analysis. The proposed goal-oriented strategy should help biologists to better apprehend image analysis in the context of their research and should allow them to efficiently interact with image processing specialists.