Dynamic super-resolution structured illumination imaging in the living brain

Extended-depth of field random illumination microscopy, EDF-RIM, provides super-resolved projective imaging

The ultimate aim of fluorescence microscopy is to achieve high-resolution imaging of increasingly larger biological samples. Extended depth of field presents a potential solution to accelerate imaging of large samples when compression of information along the optical axis is not detrimental to the interpretation of images. We have implemented an extended depth of field (EDF) approach in a random illumination microscope (RIM). RIM uses multiple speckled illuminations and variance data processing to double the resolution. It is particularly adapted to the imaging of thick samples as it does not require the knowledge of illumination patterns. We demonstrate highly-resolved projective images of biological tissues and cells. Compared to a sequential scan of the imaged volume with conventional 2D-RIM, EDF-RIM allows an order of magnitude improvement in speed and light dose reduction, with comparable resolution. As the axial information is lost in an EDF modality, we propose a method to retrieve the sample topography for samples that are organized in cell sheets.

OpenSTED: open-source dynamic intensity minimum system for stimulated emission depletion microscopy

Significance

Stimulated emission depletion (STED) is a powerful super-resolution microscopy technique that can be used for imaging live cells. However, the high STED laser powers can cause significant photobleaching and sample damage in sensitive biological samples. The dynamic intensity minimum (DyMIN) technique turns on the STED laser only in regions of the sample where there is fluorescence signal, thus saving significant sample photobleaching. The reduction in photobleaching allows higher resolution images to be obtained and longer time-lapse imaging of live samples. A stand-alone module to perform DyMIN is not available commercially.

Aim

In this work, we developed an open-source design to implement three-step DyMIN on a STED microscope and demonstrated reduced photobleaching for timelapse imaging of beads, cells, and tissue.

Approach

The DyMIN system uses a fast multiplexer circuit and inexpensive field-programmable gate array controlled by Labview software that operates as a stand-alone module for a STED microscope. All software and circuit diagrams are freely available.

Results

We compared time-lapse images of bead samples using our custom DyMIN system to conventional STED and recorded a ∼ 46 % higher signal when using DyMIN after a 50-image sequence. We further demonstrated the DyMIN system for time-lapse STED imaging of live cells and brain tissue slices.

Conclusions

Our open-source DyMIN system is an inexpensive add-on to a conventional STED microscope that can reduce photobleaching. The system can significantly improve signal to noise for dynamic time-lapse STED imaging of live samples.

Three-photon excited fluorescence microscopy enables imaging of blood flow, neural structure and inflammatory response deep into mouse spinal cord in vivo

Nonlinear optical microscopy enables non-invasive imaging in scattering samples with cellular resolution. The spinal cord connects the brain with the periphery and governs fundamental behaviors such as locomotion and somatosensation. Because of dense myelination on the dorsal surface, imaging to the spinal grey matter is challenging, even with two-photon microscopy. Here we show that three-photon excited fluorescence (3PEF) microscopy enables multicolor imaging at depths of up to ~550 μm into the mouse spinal cord, in vivo. We quantified blood flow across vessel types along the spinal vascular network. We then followed the response of neurites and microglia after occlusion of a surface venule, where we observed depth-dependent structural changes in neurites and interactions of perivascular microglia with vessel branches upstream from the clot. This work establishes that 3PEF imaging enables studies of functional dynamics and cell type interactions in the top 550 μm of the murine spinal cord, in vivo.

Tandem aberration correction optics (TACO) in wide-field structured illumination microscopy

Structured illumination microscopy (SIM) is a powerful super-resolution imaging technique that uses patterned illumination to down-modulate high spatial-frequency information of samples. However, the presence of spatially-dependent aberrations can severely disrupt the illumination pattern, limiting the quality of SIM imaging. Conventional adaptive optics (AO) techniques that employ wavefront correctors at the pupil plane are not capable of effectively correcting these spatially-dependent aberrations. We introduce the Tandem Aberration Correction Optics (TACO) approach that combines both pupil AO and conjugate AO for aberration correction in SIM. TACO incorporates a deformable mirror (DM) for pupil AO in the detection path to correct for global aberrations, while a spatial light modulator (SLM) is placed at the plane conjugate to the aberration source near the sample plane, termed conjugate AO, to compensate spatially-varying aberrations in the illumination path. Our numerical simulations and experimental results show that the TACO approach can recover the illumination pattern close to an ideal condition, even when severely misshaped by aberrations, resulting in high-quality super-resolution SIM reconstruction. The TACO approach resolves a critical traditional shortcoming of aberration correction for structured illumination. This advance significantly expands the application of SIM imaging in the study of complex, particularly biological, samples and should be effective in other wide-field microscopies.

Roadmap on Label-Free Super-Resolution Imaging

Label-free super-resolution (LFSR) imaging relies on light-scattering processes in nanoscale objects without a need for fluorescent (FL) staining required in super-resolved FL microscopy. The objectives of this Roadmap are to present a comprehensive vision of the developments, the state-of-the-art in this field, and to discuss the resolution boundaries and hurdles which need to be overcome to break the classical diffraction limit of the LFSR imaging. The scope of this Roadmap spans from the advanced interference detection techniques, where the diffraction-limited lateral resolution is combined with unsurpassed axial and temporal resolution, to techniques with true lateral super-resolution capability which are based on understanding resolution as an information science problem, on using novel structured illumination, near-field scanning, and nonlinear optics approaches, and on designing superlenses based on nanoplasmonics, metamaterials, transformation optics, and microsphere-assisted approaches. To this end, this Roadmap brings under the same umbrella researchers from the physics and biomedical optics communities in which such studies have often been developing separately. The ultimate intent of this paper is to create a vision for the current and future developments of LFSR imaging based on its physical mechanisms and to create a great opening for the series of articles in this field.

Deep learning-driven adaptive optics for single-molecule localization microscopy

The inhomogeneous refractive indices of biological tissues blur and distort single-molecule emission patterns generating image artifacts and decreasing the achievable resolution of single-molecule localization microscopy (SMLM). Conventional sensorless adaptive optics methods rely on iterative mirror changes and image-quality metrics. However, these metrics result in inconsistent metric responses and thus fundamentally limit their efficacy for aberration correction in tissues. To bypass iterative trial-then-evaluate processes, we developed deep learning-driven adaptive optics for SMLM to allow direct inference of wavefront distortion and near real-time compensation. Our trained deep neural network monitors the individual emission patterns from single-molecule experiments, infers their shared wavefront distortion, feeds the estimates through a dynamic filter and drives a deformable mirror to compensate sample-induced aberrations. We demonstrated that our method simultaneously estimates and compensates 28 wavefront deformation shapes and improves the resolution and fidelity of three-dimensional SMLM through >130-µm-thick brain tissue specimens.

Scanning single molecule localization microscopy (scanSMLM) for super-resolution volume imaging

Over the last decade, single-molecule localization microscopy (SMLM) has developed into a set of powerful techniques that have improved spatial resolution over diffraction-limited microscopy and demonstrated the ability to resolve biological features down to a few tens of nanometers. We introduce a single molecule-based scanning SMLM (scanSMLM) system that enables rapid volume imaging. Along with epi-illumination, the system employs a scanning-based 4f detection for volume imaging. The 4f system comprises a combination of an electrically-tunable lens and high NA detection objective lens. By rapidly changing the aperture (or equivalently the focus) of an electrically-tunable lens (ETL) in a 4f detection system, the selectivity of the axial object plane is achieved, for which the image forms in the image/detector plane. So, in principle, one can scan the object volume by just altering the aperture of ETL. Two schemes were adopted to carry out volume imaging: cyclic scan and conventional scan. The cyclic scheme scans the volume in each scan cycle, whereas plane-wise scanning is performed in the conventional scheme. Hence, the cyclic scan ensures uniform dwell time on each frame during data collection, thereby evenly distributing photobleaching throughout the cell volume. With a minimal change in the system hardware (requiring the addition of an ETL lens and related electronics for step-voltage generation) in the existing SMLM system, volume scanning (along the z-axis) can be achieved. To calibrate and derive critical system parameters, we imaged fluorescent beads embedded in a gel-matrix 3D block as a test sample. Subsequently, scanSMLM is employed to visualize the architecture of actin-filaments and the distribution of Meos-Tom20 molecules on the mitochondrial membrane. The technique is further exploited to understand the clustering of Hemagglutinin (HA) protein single molecules in a transfected cell for studying Influenza-A disease progression. The system, for the first time, enabled 3D visualization of HA distribution that revealed HA cluster formation spanning the entire cell volume, post 24 hrs of transfection. Critical biophysical parameters related to HA clusters (density, the number of HA molecules per cluster, axial span, fraction of clustered molecules, and others) are also determined, giving an unprecedented insight into Influenza-A disease progression at the single-molecule level.

Optical coherence tomography-based design for a real-time motion corrected scanning microscope

While two-photon fluorescence microscopy is a powerful platform for the study of functional dynamics in living cells and tissues, the bulk motion inherent to these applications causes distortions. We have designed a motion tracking module based on spectral domain optical coherence tomography which compliments a laser scanning two-photon microscope with real-time corrective feedback. The module can be added to fluorescent imaging microscopes using a single dichroic and without additional contrast agents. We demonstrate that the system can track lateral displacements as large as 10 μm at 5 Hz with latency under 14 ms and propose a scheme to extend the system to 3D correction with the addition of a remote focusing module. We also propose several ways to improve the module's performance by reducing the feedback latency. We anticipate that this design can be adapted to other imaging modalities, enabling the study of samples subject to motion artifacts at higher resolution.

Label-free adaptive optics single-molecule localization microscopy for whole zebrafish

Specimen-induced aberration has been a major factor limiting the imaging depth of single-molecule localization microscopy (SMLM). Here, we report the application of label-free wavefront sensing adaptive optics to SMLM for deep-tissue super-resolution imaging. The proposed system measures complex tissue aberrations from intrinsic reflectance rather than fluorescence emission and physically corrects the wavefront distortion more than three-fold stronger than the previous limit. This enables us to resolve sub-diffraction morphologies of cilia and oligodendrocytes in whole zebrafish as well as dendritic spines in thick mouse brain tissues at the depth of up to 102 μm with localization number enhancement by up to 37 times and localization precision comparable to aberration-free samples. The proposed approach can expand the application range of SMLM to whole zebrafish that cause the loss of localization number owing to severe tissue aberrations.

Superresolution structured illumination microscopy reconstruction algorithms: a review

Structured illumination microscopy (SIM) has become the standard for next-generation wide-field microscopy, offering ultrahigh imaging speed, superresolution, a large field-of-view, and long-term imaging. Over the past decade, SIM hardware and software have flourished, leading to successful applications in various biological questions. However, unlocking the full potential of SIM system hardware requires the development of advanced reconstruction algorithms. Here, we introduce the basic theory of two SIM algorithms, namely, optical sectioning SIM (OS-SIM) and superresolution SIM (SR-SIM), and summarize their implementation modalities. We then provide a brief overview of existing OS-SIM processing algorithms and review the development of SR-SIM reconstruction algorithms, focusing primarily on 2D-SIM, 3D-SIM, and blind-SIM. To showcase the state-of-the-art development of SIM systems and assist users in selecting a commercial SIM system for a specific application, we compare the features of representative off-the-shelf SIM systems. Finally, we provide perspectives on the potential future developments of SIM.

Conjugated Polymeric Materials in Biological Imaging and Cancer Therapy

Conjugated polymers (CPs) have attracted much attention in the fields of chemistry, medicine, life science, and material science. Researchers have carried out a series of innovative researches and have made significant research progress regarding the unique photochemical and photophysical properties of CPs, expanding the application range of polymers. CPs are polymers formed by the conjugation of multiple repeating light-emitting units. Through precise control of their structure, functional molecules with different properties can be obtained. Fluorescence probes with different absorption and emission wavelengths can be obtained by changing the main chain structure. By modifying the side chain structure with water-soluble groups or selective recognition molecules, electrostatic interaction or specific binding with specific targets can be achieved; subsequently, the purpose of selective recognition can be achieved. This article reviews the research work of CPs in cell imaging, tumor diagnosis, and treatment in recent years, summarizes the latest progress in the application of CPs in imaging, tumor diagnosis, and treatment, and discusses the future development direction of CPs in cell imaging, tumor diagnosis, and treatment.

Imaging Approaches to Investigate Pathophysiological Mechanisms of Brain Disease in Zebrafish

Zebrafish has become an essential model organism in modern biomedical research. Owing to its distinctive features and high grade of genomic homology with humans, it is increasingly employed to model diverse neurological disorders, both through genetic and pharmacological intervention. The use of this vertebrate model has recently enhanced research efforts, both in the optical technology and in the bioengineering fields, aiming at developing novel tools for high spatiotemporal resolution imaging. Indeed, the ever-increasing use of imaging methods, often combined with fluorescent reporters or tags, enable a unique chance for translational neuroscience research at different levels, ranging from behavior (whole-organism) to functional aspects (whole-brain) and down to structural features (cellular and subcellular). In this work, we present a review of the imaging approaches employed to investigate pathophysiological mechanisms underlying functional, structural, and behavioral alterations of human neurological diseases modeled in zebrafish.

Rapid, artifact-reduced, image reconstruction for super-resolution structured illumination microscopy

Super-resolution structured illumination microscopy (SR-SIM) is finding increasing application in biomedical research due to its superior ability to visualize subcellular dynamics in living cells. However, during image reconstruction artifacts can be introduced and when coupled with time-consuming postprocessing procedures, limits this technique from becoming a routine imaging tool for biologists. To address these issues, an accelerated, artifact-reduced reconstruction algorithm termed joint space frequency reconstruction-based artifact reduction algorithm (JSFR-AR-SIM) was developed by integrating a high-speed reconstruction framework with a high-fidelity optimization approach designed to suppress the sidelobe artifact. Consequently, JSFR-AR-SIM produces high-quality, super-resolution images with minimal artifacts, and the reconstruction speed is increased. We anticipate this algorithm to facilitate SR-SIM becoming a routine tool in biomedical laboratories.

Adaptive optics for optical microscopy [Invited]

Optical microscopy is widely used to visualize fine structures. When applied to bioimaging, its performance is often degraded by sample-induced aberrations. In recent years, adaptive optics (AO), originally developed to correct for atmosphere-associated aberrations, has been applied to a wide range of microscopy modalities, enabling high- or super-resolution imaging of biological structure and function in complex tissues. Here, we review classic and recently developed AO techniques and their applications in optical microscopy.

Super-resolution fluorescence microscopic imaging in pathogenesis and drug treatment of neurological disease

Since super-resolution fluorescence microscopic technology breaks the diffraction limit that has existed for a long time in optical imaging, it can observe the process of synapses formed between nerve cells and the protein aggregation related to neurological disease. Thus, super-resolution fluorescence microscopic imaging has significantly impacted several industries, including drug development and pathogenesis research, and it is anticipated that it will significantly alter the future of life science research. Here, we focus on several typical super-resolution fluorescence microscopic technologies, introducing their benefits and drawbacks, as well as applications in several common neurological diseases, in the hope that their services will be expanded and improved in the pathogenesis and drug treatment of neurological diseases.

Motion-resistant structured illumination microscopy based on principal component analysis

Structured illumination microscopy (SIM) has become one of the most significant super-resolution techniques in bioscience for observing live-cell dynamics, thanks to fast full-field imaging and low photodamage. However, artifact-free SIM super-resolution reconstruction requires precise knowledge about variable environment-sensitive illumination parameters. Conventional algorithms typically, under the premise of known and reliable constant phase shifts, compensate for residual parameters, which will be easily broken by motion factors such as environment and medium perturbations, and sample offsets. In this Letter, we propose a robust motion-resistant SIM algorithm based on principal component analysis (mrPCA-SIM), which can efficiently compensate for nonuniform pixel shifts and phase errors in each raw illumination image. Experiments demonstrate that mrPCA-SIM achieves more robust imaging quality in complex, unstable conditions compared with conventional methods, promising a more compatible and flexible imaging tool for live cells.

Introduction: What Are Dendritic Spines?

Dendritic spines are cellular specializations that greatly increase the connectivity of neurons and modulate the "weight" of most postsynaptic excitatory potentials. Spines are found in very diverse animal species providing neural networks with a high integrative and computational possibility and plasticity, enabling the perception of sensorial stimuli and the elaboration of a myriad of behavioral displays, including emotional processing, memory, and learning. Humans have trillions of spines in the cerebral cortex, and these spines in a continuum of shapes and sizes can integrate the features that differ our brain from other species. In this chapter, we describe (1) the discovery of these small neuronal protrusions and the search for the biological meaning of dendritic spines; (2) the heterogeneity of shapes and sizes of spines, whose structure and composition are associated with the fine-tuning of synaptic processing in each nervous area, as well as the findings that support the role of dendritic spines in increasing the wiring of neural circuits and their functions; and (3) within the intraspine microenvironment, the integration and activation of signaling biochemical pathways, the compartmentalization of molecules or their spreading outside the spine, and the biophysical properties that can affect parent dendrites. We also provide (4) examples of plasticity involving dendritic spines and neural circuits relevant to species survival and comment on (5) current research advancements and challenges in this exciting research field.

Recent advances in optical imaging through deep tissue: imaging probes and techniques

Optical imaging has been essential for scientific observations to date, however its biomedical applications has been restricted due to its poor penetration through tissues. In living tissue, signal attenuation and limited imaging depth caused by the wave distortion occur because of scattering and absorption of light by various molecules including hemoglobin, pigments, and water. To overcome this, methodologies have been proposed in the various fields, which can be mainly categorized into two stategies: developing new imaging probes and optical techniques. For example, imaging probes with long wavelength like NIR-II region are advantageous in tissue penetration. Bioluminescence and chemiluminescence can generate light without excitation, minimizing background signals. Afterglow imaging also has high a signal-to-background ratio because excitation light is off during imaging. Methodologies of adaptive optics (AO) and studies of complex media have been established and have produced various techniques such as direct wavefront sensing to rapidly measure and correct the wave distortion and indirect wavefront sensing involving modal and zonal methods to correct complex aberrations. Matrix-based approaches have been used to correct the high-order optical modes by numerical post-processing without any hardware feedback. These newly developed imaging probes and optical techniques enable successful optical imaging through deep tissue. In this review, we discuss recent advances for multi-scale optical imaging within deep tissue, which can provide reseachers multi-disciplinary understanding and broad perspectives in diverse fields including biophotonics for the purpose of translational medicine and convergence science.

In vivo super-resolution of the brain - How to visualize the hidden nanoplasticity?

Super-resolution fluorescence microscopy has entered most biological laboratories worldwide and its benefit is undisputable. Its application to brain imaging, for example in living mice, enables the study of sub-cellular structural plasticity and brain function directly in a living mammal. The demands of brain imaging on the different super-resolution microscopy techniques (STED, RESOLFT, SIM, ISM) and labeling strategies are discussed here as well as the challenges of the required cranial window preparation. Applications of super-resolution in the anesthetized mouse brain enlighten the stability and plasticity of synaptic nanostructures. These studies show the potential of in vivo super-resolution imaging and justify its application more widely in vivo to investigate the role of nanostructures in memory and learning.

Detection of fortunate molecules induce particle resolution shift (PAR-shift) toward single-molecule limit in SMLM: A technique for resolving molecular clusters in cellular system

Molecules capable of emitting a large number of photons (also known as fortunate molecules) are crucial for achieving a resolution close to single molecule limit (the actual size of a single molecule). We propose a long-exposure single molecule localization microscopy (leSMLM) technique that enables detection of fortunate molecules, which is based on the fact that detecting a relatively small subset of molecules with large photon emission increases its localization precision (∼r₀/N). Fortunate molecules have the ability to emit a large burst of photons over a prolonged time (> average blinking lifetime). So, a long exposure time allows the time window necessary to detect these elite molecules. The technique involves the detection of fortunate molecules to generate enough statistics for a quality reconstruction of the target protein distribution in a cellular system. Studies show a significant PArticle Resolution Shift (PAR-shift) of about 6 and 11 nm toward single-molecule-limit (far from diffraction-limit) for an exposure time window of 60 and 90 ms, respectively. In addition, a significant decrease in the fraction of fortunate molecules (single molecules with small localization precision) is observed. Specifically, 8.33% and 3.43% molecules are found to emit in 30-60  ms and >60 ms, respectively, when compared to single molecule localization microscopy (SMLM). The long exposure has enabled better visualization of the Dendra2HA molecular cluster, resolving sub-clusters within a large cluster. Thus, the proposed technique leSMLM facilitates a better study of cluster formation in fixed samples. Overall, leSMLM technique offers a spatial resolution improvement of ~ 10 nm compared to traditional SMLM at the cost of marginally poor temporal resolution.

Active Aberration Correction with Adaptive Coefficient SPGD Algorithm for Laser Scanning Confocal Microscope

A laser scanning confocal microscope (LSCM) is an effective scientific instrument for studying sub-micron structures, and it has been widely used in the field of biological detection. However, the illumination depth of LSCMs is limited due to the optical aberrations introduced by living biological tissue, which acts as an optical medium with a non-uniform refractive index, resulting in a significant dispersion of the focus of LSCM illumination light and, hence, a loss in the resolution of the image. In this study, to minimize the effect of optical aberrations, an image-based adaptive optics technology using an optimized stochastic parallel gradient descent (SPGD) algorithm with an adaptive coefficient is applied to the optical path of an LSCM system. The effectiveness of the proposed aberration correction approach is experimentally evaluated in the LSCM system. The results illustrate that the proposed adaptive optics system with an adaptive coefficient SPGD algorithm can effectively reduce the interference caused by aberrations during depth imaging.

Answering some questions about structured illumination microscopy

Structured illumination microscopy (SIM) provides images of fluorescent objects at an enhanced resolution greater than that of conventional epifluorescence wide-field microscopy. Initially demonstrated in 1999 to enhance the lateral resolution twofold, it has since been extended to enhance axial resolution twofold (2008), applied to live-cell imaging (2009) and combined with myriad other techniques, including interferometric detection (2008), confocal microscopy (2010) and light sheet illumination (2012). Despite these impressive developments, SIM remains, perhaps, the most poorly understood 'super-resolution' method. In this article, we provide answers to the 13 questions regarding SIM proposed by Prakash et al. along with answers to a further three questions. After providing a general overview of the technique and its developments, we explain why SIM as normally used is still diffraction-limited. We then highlight the necessity for a non-polynomial, and not just nonlinear, response to the illuminating light in order to make SIM a true, diffraction-unlimited, super-resolution technique. In addition, we present a derivation of a real-space SIM reconstruction approach that can be used to process conventional SIM and image scanning microscopy (ISM) data and extended to process data with quasi-arbitrary illumination patterns. Finally, we provide a simple bibliometric analysis of SIM development over the past two decades and provide a short outlook on potential future work. This article is part of the Theo Murphy meeting issue 'Super-resolution structured illumination microscopy (part 2)'.

Miniature structured illumination microscope for in vivo 3D imaging of brain structures with optical sectioning

We present a high-resolution miniature, light-weight fluorescence microscope with electrowetting lens and onboard CMOS for high resolution volumetric imaging and structured illumination for rejection of out-of-focus and scattered light. The miniature microscope (SIMscope3D) delivers structured light using a coherent fiber bundle to obtain optical sectioning with an axial resolution of 18 µm. Volumetric imaging of eGFP labeled cells in fixed mouse brain tissue at depths up to 260 µm is demonstrated. The functionality of SIMscope3D to provide background free 3D imaging is shown by recording time series of microglia dynamics in awake mice at depths up to 120 µm in the brain.

Imaging the endocannabinoid signaling system

The endocannabinoid (eCB) system is one of the most widespread neuromodulatory systems in the mammalian brain, with a multifaceted role in functions ranging from development to synaptic plasticity. Endocannabinoids are synthesized on demand from membrane lipid precursors, and act primarily on a single G-protein coupled receptor type, CB1, to carry out diverse functions. Despite the importance of the eCB system both in healthy brain function and in disease, critically important details of eCB signaling remained unknown. How eCBs are released from the membrane, how these lipid molecules are transported between cells, and how the distribution of their receptors is controlled, remained elusive. Recent advances in optical microscopy methods and biosensor engineering may open up new avenues for studying eCB signaling. We summarize applications of superresolution microscopy using single molecule localization to reveal distinct patterns of nanoscale CB1 distribution in neuronal axons and axon terminals. We review single particle tracking studies using quantum dots that allowed visualizing CB1 trajectories. We highlight the recent development of fluorescent eCB biosensors, that revealed spatiotemporally specific eCB release in live cells and live animals. Finally, we discuss future directions where method development may help to advance a precise understanding of eCB signaling.

Microscope-Cockpit: Python-based bespoke microscopy for bio-medical science

We have developed “Microscope-Cockpit” (Cockpit), a highly adaptable open source user-friendly Python-based Graphical User Interface (GUI) environment for precision control of both simple and elaborate bespoke microscope systems. The user environment allows next-generation near instantaneous navigation of the entire slide landscape for efficient selection of specimens of interest and automated acquisition without the use of eyepieces. Cockpit uses “Python-Microscope” (Microscope) for high-performance coordinated control of a wide range of hardware devices using open source software. Microscope also controls complex hardware devices such as deformable mirrors for aberration correction and spatial light modulators for structured illumination via abstracted device models. We demonstrate the advantages of the Cockpit platform using several bespoke microscopes, including a simple widefield system and a complex system with adaptive optics and structured illumination. A key strength of Cockpit is its use of Python, which means that any microscope built with Cockpit is ready for future customisation by simply adding new libraries, for example machine learning algorithms to enable automated microscopy decision making while imaging.

In sickness and in health: The functional role of extracellular vesicles in physiology and pathology in vivo: Part I: Health and Normal Physiology: Part I: Health and Normal Physiology

Previously thought to be nothing more than cellular debris, extracellular vesicles (EVs) are now known to mediate physiological and pathological functions throughout the body. We now understand more about their capacity to transfer nucleic acids and proteins between distant organs, the interaction of their surface proteins with target cells, and the role of vesicle-bound lipids in health and disease. To date, most observations have been made in reductionist cell culture systems, or as snapshots from patient cohorts. The heterogenous population of vesicles produced in vivo likely act in concert to mediate both beneficial and detrimental effects. EVs play crucial roles in both the pathogenesis of diseases, from cancer to neurodegenerative disease, as well as in the maintenance of system and organ homeostasis. This two-part review draws on the expertise of researchers working in the field of EV biology and aims to cover the functional role of EVs in physiology and pathology. Part I will outline the role of EVs in normal physiology.

Neurophotonic tools for microscopic measurements and manipulation: status report

Neurophotonics was launched in 2014 coinciding with the launch of the BRAIN Initiative focused on development of technologies for advancement of neuroscience. For the last seven years, Neurophotonics' agenda has been well aligned with this focus on neurotechnologies featuring new optical methods and tools applicable to brain studies. While the BRAIN Initiative 2.0 is pivoting towards applications of these novel tools in the quest to understand the brain, this status report reviews an extensive and diverse toolkit of novel methods to explore brain function that have emerged from the BRAIN Initiative and related large-scale efforts for measurement and manipulation of brain structure and function. Here, we focus on neurophotonic tools mostly applicable to animal studies. A companion report, scheduled to appear later this year, will cover diffuse optical imaging methods applicable to noninvasive human studies. For each domain, we outline the current state-of-the-art of the respective technologies, identify the areas where innovation is needed, and provide an outlook for the future directions.

Single-Molecule Clustering for Super-Resolution Optical Fluorescence Microscopy

Molecular assembly in a complex cellular environment is vital for understanding underlying biological mechanisms. Biophysical parameters (such as single-molecule cluster density, cluster-area, pairwise distance, and number of molecules per cluster) related to molecular clusters directly associate with the physiological state (healthy/diseased) of a cell. Using super-resolution imaging along with powerful clustering methods (K-means, Gaussian mixture, and point clustering), we estimated these critical biophysical parameters associated with dense and sparse molecular clusters. We investigated Hemaglutinin (HA) molecules in an Influenza type A disease model. Subsequently, clustering parameters were estimated for transfected NIH3T3 cells. Investigations on test sample (randomly generated clusters) and NIH3T3 cells (expressing Dendra2-Hemaglutinin (Dendra2-HA) photoactivable molecules) show a significant disparity among the existing clustering techniques. It is observed that a single method is inadequate for estimating all relevant biophysical parameters accurately. Thus, a multimodel approach is necessary in order to characterize molecular clusters and determine critical parameters. The proposed study involving optical system development, photoactivable sample synthesis, and advanced clustering methods may facilitate a better understanding of single molecular clusters. Potential applications are in the emerging field of cell biology, biophysics, and fluorescence imaging.

Volumetric interferometric lattice light-sheet imaging

Live-cell imaging with high spatiotemporal resolution and high detection sensitivity facilitates the study of the dynamics of cellular structure and function. However, extracting high-resolution 4D (3D space plus time) information from live cells remains challenging, because current methods are slow, require high peak excitation intensities or suffer from high out-of-focus background. Here we present 3D interferometric lattice light-sheet (3D-iLLS) imaging, a technique that requires low excitation light levels and provides high background suppression and substantially improved volumetric resolution by combining 4Pi interferometry with selective plane illumination. We demonstrate that 3D-iLLS has an axial resolution and single-particle localization precision of 100 nm (FWHM) and <10 nm (1σ), respectively. We illustrate the performance of 3D-iLLS in a range of systems: single messenger RNA molecules, nanoscale assemblies of transcription regulators in the nucleus, the microtubule cytoskeleton, and mitochondria organelles. The enhanced 4D resolution and increased signal-to-noise ratio (SNR) of 3D-iLLS will facilitate the analysis of biological processes at the sub-cellular level.

Super-Resolution Microscopy: Shedding New Light on In Vivo Imaging

Over the past two decades, super-resolution microscopy (SRM), which offered a significant improvement in resolution over conventional light microscopy, has become a powerful tool to visualize biological activities in both fixed and living cells. However, completely understanding biological processes requires studying cells in a physiological context at high spatiotemporal resolution. Recently, SRM has showcased its ability to observe the detailed structures and dynamics in living species. Here we summarized recent technical advancements in SRM that have been successfully applied to in vivo imaging. Then, improvements in the labeling strategies are discussed together with the spectroscopic and chemical demands of the fluorophores. Finally, we broadly reviewed the current applications for super-resolution techniques in living species and highlighted some inherent challenges faced in this emerging field. We hope that this review could serve as an ideal reference for researchers as well as beginners in the relevant field of in vivo super resolution imaging.

Adaptive optics in super-resolution microscopy

Fluorescence microscopy has become a routine tool in biology for interrogating life activities with minimal perturbation. While the resolution of fluorescence microscopy is in theory governed only by the diffraction of light, the resolution obtainable in practice is also constrained by the presence of optical aberrations. The past two decades have witnessed the advent of super-resolution microscopy that overcomes the diffraction barrier, enabling numerous biological investigations at the nanoscale. Adaptive optics, a technique borrowed from astronomical imaging, has been applied to correct for optical aberrations in essentially every microscopy modality, especially in super-resolution microscopy in the last decade, to restore optimal image quality and resolution. In this review, we briefly introduce the fundamental concepts of adaptive optics and the operating principles of the major super-resolution imaging techniques. We highlight some recent implementations and advances in adaptive optics for active and dynamic aberration correction in super-resolution microscopy.

Super-Resolution Imaging with Graphene

Super-resolution optical imaging is a consistent research hotspot for promoting studies in nanotechnology and biotechnology due to its capability of overcoming the diffraction limit, which is an intrinsic obstacle in pursuing higher resolution for conventional microscopy techniques. In the past few decades, a great number of techniques in this research domain have been theoretically proposed and experimentally demonstrated. Graphene, a special two-dimensional material, has become the most meritorious candidate and attracted incredible attention in high-resolution imaging domain due to its distinctive properties. In this article, the working principle of graphene-assisted imaging devices is summarized, and recent advances of super-resolution optical imaging based on graphene are reviewed for both near-field and far-field applications.

Intravital fluorescence microscopy with negative contrast

Advances in intravital microscopy (IVM) have enabled the studies of cellular organization and dynamics in the native microenvironment of intact organisms with minimal perturbation. The abilities to track specific cell populations and monitor their interactions have opened up new horizons for visualizing cell biology in vivo, yet the success of standard fluorescence cell labeling approaches for IVM comes with a "dark side" in that unlabeled cells are invisible, leaving labeled cells or structures to appear isolated in space, devoid of their surroundings and lacking proper biological context. Here we describe a novel method for "filling in the void" by harnessing the ubiquity of extracellular (interstitial) fluid and its ease of fluorescence labelling by commonly used vascular and lymphatic tracers. We show that during routine labeling of the vasculature and lymphatics for IVM, commonly used fluorescent tracers readily perfuse the interstitial spaces of the bone marrow (BM) and the lymph node (LN), outlining the unlabeled cells and forming negative contrast images that complement standard (positive) cell labeling approaches. The method is simple yet powerful, offering a comprehensive view of the cellular landscape such as cell density and spatial distribution, as well as dynamic processes such as cell motility and transmigration across the vascular endothelium. The extracellular localization of the dye and the interstitial flow provide favorable conditions for prolonged Intravital time lapse imaging with minimal toxicity and photobleaching.

High-resolution light-field microscopy with patterned illumination

Light-field fluorescence microscopy can record large-scale population activity of neurons expressing genetically-encoded fluorescent indicators within volumes of tissue. Conventional light-field microscopy (LFM) suffers from poor lateral resolution when using wide-field illumination. Here, we demonstrate a structured-illumination light-field microscopy (SI-LFM) modality that enhances spatial resolution over the imaging volume. This modality increases resolution by illuminating sample volume with grating patterns that are invariant over the axial direction. The size of the SI-LFM point-spread-function (PSF) was approximately half the size of the conventional LFM PSF when imaging fluorescent beads. SI-LFM also resolved fine spatial features in lens tissue samples and fixed mouse retina samples. Finally, SI-LFM reported neural activity with approximately three times the signal-to-noise ratio of conventional LFM when imaging live zebrafish expressing a genetically encoded calcium sensor.

Seeing beyond the limit: A guide to choosing the right super-resolution microscopy technique

Super-resolution microscopy has become an increasingly popular and robust tool across the life sciences to study minute cellular structures and processes. However, with the increasing number of available super-resolution techniques has come an increased complexity and burden of choice in planning imaging experiments. Choosing the right super-resolution technique to answer a given biological question is vital for understanding and interpreting biological relevance. This is an often-neglected and complex task that should take into account well-defined criteria (e.g., sample type, structure size, imaging requirements). Trade-offs in different imaging capabilities are inevitable; thus, many researchers still find it challenging to select the most suitable technique that will best answer their biological question. This review aims to provide an overview and clarify the concepts underlying the most commonly available super-resolution techniques as well as guide researchers through all aspects that should be considered before opting for a given technique.

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)'.

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)'.

Super-resolution STED microscopy in live brain tissue

STED microscopy is one of several fluorescence microscopy techniques that permit imaging at higher spatial resolution than what the diffraction-limit of light dictates. STED imaging is unique among these super-resolution modalities in being a beam-scanning microscopy technique based on confocal or 2-photon imaging, which provides the advantage of superior optical sectioning in thick samples. Compared to the other super-resolution techniques that are based on widefield microscopy, this makes STED particularly suited for imaging inside live brain tissue, such as in slices or in vivo. Notably, the 50 nm resolution provided by STED microscopy enables analysis of neural morphologies that conventional confocal and 2-photon microscopy approaches cannot resolve, including all-important synaptic structures. Over the course of the last 20 years, STED microscopy has undergone extensive developments towards ever more versatile use, and has facilitated remarkable neurophysiological discoveries. The technique is still not widely adopted for live tissue imaging, even though one of its particular strengths is exactly in resolving the nanoscale dynamics of synaptic structures in brain tissue, as well as in addressing the complex morphologies of glial cells, and revealing the intricate structure of the brain extracellular space. Not least, live tissue STED microscopy has so far hardly been applied in settings of pathophysiology, though also here it shows great promise for providing new insights. This review outlines the technical advantages of STED microscopy for imaging in live brain tissue, and highlights key neurobiological findings brought about by the technique.

Improvement of the Similarity Spectral Unmixing Approach for Multiplexed Two-Photon Imaging by Linear Dimension Reduction of the Mixing Matrix

Two-photon microscopy enables monitoring cellular dynamics and communication in complex systems, within a genuine environment, such as living tissues and, even, living organisms. Particularly, its application to understand cellular interactions in the immune system has brought unique insights into pathophysiologic processes in vivo. Simultaneous multiplexed imaging is required to understand the dynamic orchestration of the multiple cellular and non-cellular tissue compartments defining immune responses. Here, we present an improvement of our previously developed method, which allowed us to achieve multiplexed dynamic intravital two-photon imaging, by using a synergistic strategy. This strategy combines a spectrally broad range of fluorophore emissions, a wave-mixing concept for simultaneous excitation of all targeted fluorophores, and an unmixing algorithm based on the calculation of spectral similarities with previously measured fluorophore fingerprints. The improvement of the similarity spectral unmixing algorithm here described is based on dimensionality reduction of the mixing matrix. We demonstrate its superior performance in the correct pixel-based assignment of probes to tissue compartments labeled by single fluorophores with similar spectral fingerprints, as compared to the full-dimensional similarity spectral unmixing approach.

Expansion Microscopy with Multifunctional Polymer Dots

Expansion microscopy (ExM) provides nanoscale resolution on conventional microscopes via physically enlarging specimens with swellable polyelectrolyte gels. However, challenges involving fluorophore degradation and dilution during sample expansion have yet to be overcome. Herein, sequential cellular targeting, gel anchoring, and high-fidelity fluorescence reported using multifunctional polymer dots (Pdots) designed for ExM applications are demonstrated. The impressive brightness of the Pdots facilitates multicolor ExM, thereby enabling visualization of a variety of subcellular structures and neuron synapses. The average fluorescence intensities of Pdots in ExM range from ≈3 to 6 times higher than those achieved using commercially available Alexa dyes. Moreover, the fluorescence brightness and optical fluctuation are significantly improved by a surfactant-containing expansion buffer, which enables further resolution enhancement via super-resolution optical fluctuation imaging (SOFI). The combination of ExM and SOFI allows subcellular structures of ≈30 nm to be resolved by conventional microscopes. These results highlight the immense potential of multifunctional Pdots for ExM-enhanced super-resolution imaging.

Multicolor structured illumination microscopy and quantitative control of polychromatic light with a digital micromirror device

Linear structured illumination microscopy (SIM) is a super-resolution microscopy technique that does not impose photophysics requirements on fluorescent samples. Multicolor SIM implementations typically rely on liquid crystal on silicon (LCoS) spatial light modulators (SLM's) for patterning the excitation light, but digital micromirror devices (DMD's) are a promising alternative, owing to their lower cost and higher speed. However, existing coherent DMD SIM implementations use only a single wavelength of light, limited by the lack of efficient approaches for solving the blazed grating effect for polychromatic light. We develop the requisite quantitative tools, including a closed form solution of the blaze and diffraction conditions, forward models of DMD diffraction and pattern projection, and a model of DMD aberrations. Based on these advances, we constructed a three-color DMD microscope, quantified the effect of aberrations from the DMD, developed a high-resolution optical transfer function measurement technique, and demonstrated SIM on fixed and live cells. This opens the door to applying DMD's in polychromatic applications previously restricted to LCoS SLM's.

Multicolor structured illumination microscopy and quantitative control of polychromatic light with a digital micromirror device

Linear structured illumination microscopy (SIM) is a super-resolution microscopy technique that does not impose photophysics requirements on fluorescent samples. Multicolor SIM implementations typically rely on liquid crystal on silicon (LCoS) spatial light modulators (SLM's) for patterning the excitation light, but digital micromirror devices (DMD's) are a promising alternative, owing to their lower cost and higher speed. However, existing coherent DMD SIM implementations use only a single wavelength of light, limited by the lack of efficient approaches for solving the blazed grating effect for polychromatic light. We develop the requisite quantitative tools, including a closed form solution of the blaze and diffraction conditions, forward models of DMD diffraction and pattern projection, and a model of DMD aberrations. Based on these advances, we constructed a three-color DMD microscope, quantified the effect of aberrations from the DMD, developed a high-resolution optical transfer function measurement technique, and demonstrated SIM on fixed and live cells. This opens the door to applying DMD's in polychromatic applications previously restricted to LCoS SLM's.

In vivo Functional Genomics for Undiagnosed Patients: The Impact of Small GTPases Signaling Dysregulation at Pan-Embryo Developmental Scale

While individually rare, disorders affecting development collectively represent a substantial clinical, psychological, and socioeconomic burden to patients, families, and society. Insights into the molecular mechanisms underlying these disorders are required to speed up diagnosis, improve counseling, and optimize management toward targeted therapies. Genome sequencing is now unveiling previously unexplored genetic variations in undiagnosed patients, which require functional validation and mechanistic understanding, particularly when dealing with novel nosologic entities. Functional perturbations of key regulators acting on signals' intersections of evolutionarily conserved pathways in these pathological conditions hinder the fine balance between various developmental inputs governing morphogenesis and homeostasis. However, the distinct mechanisms by which these hubs orchestrate pathways to ensure the developmental coordinates are poorly understood. Integrative functional genomics implementing quantitative in vivo models of embryogenesis with subcellular precision in whole organisms contribute to answering these questions. Here, we review the current knowledge on genes and mechanisms critically involved in developmental syndromes and pediatric cancers, revealed by genomic sequencing and in vivo models such as insects, worms and fish. We focus on the monomeric GTPases of the RAS superfamily and their influence on crucial developmental signals and processes. We next discuss the effectiveness of exponentially growing functional assays employing tractable models to identify regulatory crossroads. Unprecedented sophistications are now possible in zebrafish, i.e., genome editing with single-nucleotide precision, nanoimaging, highly resolved recording of multiple small molecules activity, and simultaneous monitoring of brain circuits and complex behavioral response. These assets permit accurate real-time reporting of dynamic small GTPases-controlled processes in entire organisms, owning the potential to tackle rare disease mechanisms.

Non-invasive super-resolution imaging through dynamic scattering media

Super-resolution imaging has been revolutionizing technical analysis in various fields from biological to physical sciences. However, many objects are hidden by strongly scattering media such as biological tissues that scramble light paths, create speckle patterns and hinder object’s visualization, let alone super-resolution imaging. Here, we demonstrate non-invasive super-resolution imaging through scattering media based on a stochastic optical scattering localization imaging (SOSLI) technique. After capturing multiple speckle patterns of photo-switchable point sources, our computational approach utilizes the speckle correlation property of scattering media to retrieve an image with a 100-nm resolution, an eight-fold enhancement compared to the diffraction limit. More importantly, we demonstrate our SOSLI to do non-invasive super-resolution imaging through not only static scattering media, but also dynamic scattering media with strong decorrelation such as biological tissues. Our approach paves the way to non-invasively visualize various samples behind scattering media at nanometer levels of detail.

The authors introduce stochastic optical scattering localization imaging (SOSLI) for non-invasive super-resolution imaging through scattering media. They capture multiple speckle patterns of photo-switchable point sources and use the speckle correlation to retrieve images with 100 nm resolution.

Subcellular three-dimensional imaging deep through multicellular thick samples by structured illumination microscopy and adaptive optics

Structured Illumination Microscopy enables live imaging with sub-diffraction resolution. Unfortunately, optical aberrations can lead to loss of resolution and artifacts in Structured Illumination Microscopy rendering the technique unusable in samples thicker than a single cell. Here we report on the combination of Adaptive Optics and Structured Illumination Microscopy enabling imaging with 150 nm lateral and 570 nm axial resolution at a depth of 80 µm through Caenorhabditis elegans. We demonstrate that Adaptive Optics improves the three-dimensional resolution, especially along the axial direction, and reduces artifacts, successfully realizing 3D-Structured Illumination Microscopy in a variety of biological samples.

Super-resolved live-cell imaging using random illumination microscopy

Current super-resolution microscopy (SRM) methods suffer from an intrinsic complexity that might curtail their routine use in cell biology. We describe here random illumination microscopy (RIM) for live-cell imaging at super-resolutions matching that of 3D structured illumination microscopy, in a robust fashion. Based on speckled illumination and statistical image reconstruction, easy to implement and user-friendly, RIM is unaffected by optical aberrations on the excitation side, linear to brightness, and compatible with multicolor live-cell imaging over extended periods of time. We illustrate the potential of RIM on diverse biological applications, from the mobility of proliferating cell nuclear antigen (PCNA) in U2OS cells and kinetochore dynamics in mitotic S. pombe cells to the 3D motion of myosin minifilaments deep inside Drosophila tissues. RIM's inherent simplicity and extended biological applicability, particularly for imaging at increased depths, could help make SRM accessible to biology laboratories.

3D super-resolution deep-tissue imaging in living mice

Stimulated emission depletion (STED) microscopy enables the three-dimensional (3D) visualization of dynamic nanoscale structures in living cells, offering unique insights into their organization. However, 3D-STED imaging deep inside biological tissue is obstructed by optical aberrations and light scattering. We present a STED system that overcomes these challenges. Through the combination of two-photon excitation, adaptive optics, red-emitting organic dyes, and a long-working-distance water-immersion objective lens, our system achieves aberration-corrected 3D super-resolution imaging, which we demonstrate 164 µm deep in fixed mouse brain tissue and 76 µm deep in the brain of a living mouse.

Quantification of Dendritic Spines Remodeling under Physiological Stimuli and in Pathological Conditions

Numerous brain diseases are associated with abnormalities in morphology and density of dendritic spines, small membranous protrusions whose structural geometry correlates with the strength of synaptic connections. Thus, the quantitative analysis of dendritic spines remodeling in microscopic images is one of the key elements towards understanding mechanisms of structural neuronal plasticity and bases of brain pathology. In the following article, we review experimental approaches designed to assess quantitative features of dendritic spines under physiological stimuli and in pathological conditions. We compare various methodological pipelines of biological models, sample preparation, data analysis, image acquisition, sample size, and statistical analysis. The methodology and results of relevant experiments are systematically summarized in a tabular form. In particular, we focus on quantitative data regarding the number of animals, cells, dendritic spines, types of studied parameters, size of observed changes, and their statistical significance.

Microscope-Cockpit: Python-based bespoke microscopy for bio-medical science

We have developed “Microscope-Cockpit” (Cockpit), a highly adaptable open source user-friendly Python-based Graphical User Interface (GUI) environment for precision control of both simple and elaborate bespoke microscope systems. The user environment allows next-generation near instantaneous navigation of the entire slide landscape for efficient selection of specimens of interest and automated acquisition without the use of eyepieces. Cockpit uses “Python-Microscope” (Microscope) for high-performance coordinated control of a wide range of hardware devices using open source software. Microscope also controls complex hardware devices such as deformable mirrors for aberration correction and spatial light modulators for structured illumination via abstracted device models. We demonstrate the advantages of the Cockpit platform using several bespoke microscopes, including a simple widefield system and a complex system with adaptive optics and structured illumination. A key strength of Cockpit is its use of Python, which means that any microscope built with Cockpit is ready for future customisation by simply adding new libraries, for example machine learning algorithms to enable automated microscopy decision making while imaging.