Isotropic imaging across spatial scales with axially swept light-sheet microscopy

Photonic neural probe enabled microendoscopes for light-sheet light-field computational fluorescence brain imaging

Significance

Light-sheet fluorescence microscopy is widely used for high-speed, high-contrast, volumetric imaging. Application of this technique to in vivo brain imaging in non-transparent organisms has been limited by the geometric constraints of conventional light-sheet microscopes, which require orthogonal fluorescence excitation and collection objectives. We have recently demonstrated implantable photonic neural probes that emit addressable light sheets at depth in brain tissue, miniaturizing the excitation optics. Here, we propose a microendoscope consisting of a light-sheet neural probe packaged together with miniaturized fluorescence collection optics based on an image fiber bundle for lensless, light-field, computational fluorescence imaging.

Aim

Foundry-fabricated, silicon-based, light-sheet neural probes can be packaged together with commercially available image fiber bundles to form microendoscopes for light-sheet light-field fluorescence imaging at depth in brain tissue.

Approach

Prototype microendoscopes were developed using light-sheet neural probes with five addressable sheets and image fiber bundles. Fluorescence imaging with the microendoscopes was tested with fluorescent beads suspended in agarose and fixed mouse brain tissue.

Results

Volumetric light-sheet light-field fluorescence imaging was demonstrated using the microendoscopes. Increased imaging depth and enhanced reconstruction accuracy were observed relative to epi-illumination light-field imaging using only a fiber bundle.

Conclusions

Our work offers a solution toward volumetric fluorescence imaging of brain tissue with a compact size and high contrast. The proof-of-concept demonstrations herein illustrate the operating principles and methods of the imaging approach, providing a foundation for future investigations of photonic neural probe enabled microendoscopes for deep-brain fluorescence imaging in vivo.

Axially swept open-top light-sheet microscopy for densely labeled clinical specimens

Open-top light-sheet (OTLS) microscopy offers rapid 3D imaging of large optically cleared specimens. This enables nondestructive 3D pathology, which provides key advantages over conventional slide-based histology including comprehensive sampling without tissue sectioning/destruction and visualization of diagnostically important 3D structures. With 3D pathology, clinical specimens are often labeled with small-molecule stains that broadly target nucleic acids and proteins, mimicking conventional hematoxylin and eosin (H&E) dyes. Tight optical sectioning helps to minimize out-of-focus fluorescence for high-contrast imaging in these densely labeled tissues but has been challenging to achieve in OTLS systems due to trade-offs between optical sectioning and field of view. Here we present an OTLS microscope with voice-coil-based axial sweeping to circumvent this trade-off, achieving 2 µm axial resolution over a 750 × 375 µm field of view. We implement our design in a non-orthogonal dual-objective (NODO) architecture, which enables a 10-mm working distance with minimal sensitivity to refractive index mismatches, for high-contrast 3D imaging of clinical specimens.

Proteolysis-free amoeboid migration of melanoma cells through crowded environments via bleb-driven worrying

In crowded microenvironments, migrating cells must find or make a path. Amoeboid cells are thought to find a path by deforming their bodies to squeeze through tight spaces. Yet, some amoeboid cells seem to maintain a near-spherical morphology as they move. To examine how they do so, we visualized amoeboid human melanoma cells in dense environments and found that they carve tunnels via bleb-driven degradation of extracellular matrix components without the need for proteolytic degradation. Interactions between adhesions and collagen at the cell front induce a signaling cascade that promotes bleb enlargement via branched actin polymerization. Large blebs abrade collagen, creating feedback between extracellular matrix structure, cell morphology, and polarization that enables both path generation and persistent movement.

A general algorithm for consensus 3D cell segmentation from 2D segmented stacks

Cell segmentation is the fundamental task. Only by segmenting, can we define the quantitative spatial unit for collecting measurements to draw biological conclusions. Deep learning has revolutionized 2D cell segmentation, enabling generalized solutions across cell types and imaging modalities. This has been driven by the ease of scaling up image acquisition, annotation and computation. However 3D cell segmentation, which requires dense annotation of 2D slices still poses significant challenges. Labelling every cell in every 2D slice is prohibitive. Moreover it is ambiguous, necessitating cross-referencing with other orthoviews. Lastly, there is limited ability to unambiguously record and visualize 1000's of annotated cells. Here we develop a theory and toolbox, u-Segment3D for 2D-to-3D segmentation, compatible with any 2D segmentation method. Given optimal 2D segmentations, u-Segment3D generates the optimal 3D segmentation without data training, as demonstrated on 11 real life datasets, >70,000 cells, spanning single cells, cell aggregates and tissue.

Mechanically Sheared Axially Swept Light-Sheet Microscopy

We present a mechanically sheared image acquisition format for upright and open-top light-sheet microscopes that automatically places data in its proper spatial context. This approach, which reduces computational post-processing and eliminates unnecessary interpolation or duplication of the data, is demonstrated on an upright variant of Axially Swept Light-Sheet Microscopy (ASLM) that achieves a field of view, measuring 774 x 435 microns, that is 3.2-fold larger than previous models and a raw and isotropic resolution of ∼420 nm. Combined, we demonstrate the power of this approach by imaging sub-diffraction beads, cleared biological tissues, and expanded specimens.

Light-Sheet Imaging to Reveal Cardiac Structure in Rodent Hearts

Light-sheet microscopy (LSM) plays a pivotal role in comprehending the intricate three-dimensional (3D) structure of the heart, providing crucial insights into fundamental cardiac physiology and pathologic responses. We hereby delve into the development and implementation of the LSM technique to elucidate the micro-architecture of the heart in mouse models. The methodology integrates a customized LSM system with tissue clearing techniques, mitigating light scattering within cardiac tissues for volumetric imaging. The combination of conventional LSM with image stitching and multiview deconvolution approaches allows for the capture of the entire heart. To address the inherent trade-off between axial resolution and field of view (FOV), we further introduce an axially swept light-sheet microscopy (ASLM) method to minimize out-of-focus light and uniformly illuminate the heart across the propagation direction. In the meanwhile, tissue clearing methods such as iDISCO enhance light penetration, facilitating the visualization of deep structures and ensuring a comprehensive examination of the myocardium throughout the entire heart. The combination of the proposed LSM and tissue clearing methods presents a promising platform for researchers in resolving cardiac structures in rodent hearts, holding great potential for the understanding of cardiac morphogenesis and remodeling.

Benchtop mesoSPIM: a next-generation open-source light-sheet microscope for cleared samples

In 2015, we launched the mesoSPIM initiative, an open-source project for making light-sheet microscopy of large cleared tissues more accessible. Meanwhile, the demand for imaging larger samples at higher speed and resolution has increased, requiring major improvements in the capabilities of such microscopes. Here, we introduce the next-generation mesoSPIM ("Benchtop") with a significantly increased field of view, improved resolution, higher throughput, more affordable cost, and simpler assembly compared to the original version. We develop an optical method for testing detection objectives that enables us to select objectives optimal for light-sheet imaging with large-sensor cameras. The improved mesoSPIM achieves high spatial resolution (1.5 µm laterally, 3.3 µm axially) across the entire field of view, magnification up to 20×, and supports sample sizes ranging from sub-mm up to several centimeters while being compatible with multiple clearing techniques. The microscope serves a broad range of applications in neuroscience, developmental biology, pathology, and even physics.

Current and future applications of light-sheet imaging for identifying molecular and developmental processes in autism spectrum disorders

Autism spectrum disorder (ASD) is identified by a set of neurodevelopmental divergences that typically affect the social communication domain. ASD is also characterized by heterogeneous cognitive impairments and is associated with cooccurring physical and medical conditions. As behaviors emerge as the brain matures, it is particularly essential to identify any gaps in neurodevelopmental trajectories during early perinatal life. Here, we introduce the potential of light-sheet imaging for studying developmental biology and cross-scale interactions among genetic, cellular, molecular and macroscale levels of circuitry and connectivity. We first report the core principles of light-sheet imaging and the recent progress in studying brain development in preclinical animal models and human organoids. We also present studies using light-sheet imaging to understand the development and function of other organs, such as the skin and gastrointestinal tract. We also provide information on the potential of light-sheet imaging in preclinical drug development. Finally, we speculate on the translational benefits of light-sheet imaging for studying individual brain-body interactions in advancing ASD research and creating personalized interventions.

Full-aperture extended-depth oblique plane microscopy through dynamic remote focusing

Significance

The reprojection setup typical of oblique plane microscopy (OPM) limits the effective aperture of the imaging system, and therefore its efficiency and resolution. Large aperture system is only possible through the use of custom specialized optics. A full-aperture OPM made with off the shelf components would both improve the performance of the method and encourage its widespread adoption.

Aim

To prove the feasibility of an OPM without a conventional reprojection setup, retaining the full aperture of the primary objective employed.

Approach

A deformable lens based remote focusing setup synchronized with the rolling shutter of a complementary metal-oxide semiconductor detector is used instead of a traditional reprojection system.

Results

The system was tested on microbeads, prepared slides, and zebrafish embryos. Resolution and pixel throughput were superior to conventional OPM with cropped apertures, and comparable with OPM implementations with custom made optical components.

Conclusions

An easily reproducible approach to OPM imaging is presented, eliminating the conventional reprojection setup and exploiting the full aperture of the employed objective.

The Vps13-like protein BLTP2 is pro-survival and regulates phosphatidylethanolamine levels in the plasma membrane to maintain its fluidity and function

Lipid transport proteins (LTPs) facilitate nonvesicular lipid exchange between cellular compartments and have critical roles in lipid homeostasis1. A new family of bridge-like LTPs (BLTPs) is thought to form lipid-transporting conduits between organelles2. One, BLTP2, is conserved across species but its function is not known. Here, we show that BLTP2 and its homolog directly regulate plasma membrane (PM) fluidity by increasing the phosphatidylethanolamine (PE) level in the PM. BLTP2 localizes to endoplasmic reticulum (ER)-PM contact sites34, 5, suggesting it transports PE from the ER to the PM. We find BLTP2 works in parallel with another pathway that regulates intracellular PE distribution and PM fluidity6, 7. BLTP2 expression correlates with breast cancer aggressiveness8-10. We found BLTP2 facilitates growth of a human cancer cell line and sustains its aggressiveness in an in vivo model of metastasis, suggesting maintenance of PM fluidity by BLTP2 may be critical for tumorigenesis in humans.

The Benchtop mesoSPIM: a next-generation open-source light-sheet microscope for large cleared samples

In 2015, we launched the mesoSPIM initiative (www.mesospim.org), an open-source project for making light-sheet microscopy of large cleared tissues more accessible. Meanwhile, the demand for imaging larger samples at higher speed and resolution has increased, requiring major improvements in the capabilities of light-sheet microscopy. Here, we introduce the next-generation mesoSPIM ("Benchtop") with significantly increased field of view, improved resolution, higher throughput, more affordable cost and simpler assembly compared to the original version. We developed a new method for testing objectives, enabling us to select detection objectives optimal for light-sheet imaging with large-sensor sCMOS cameras. The new mesoSPIM achieves high spatial resolution (1.5 μm laterally, 3.3 μm axially) across the entire field of view, a magnification up to 20x, and supports sample sizes ranging from sub-mm up to several centimetres, while being compatible with multiple clearing techniques. The new microscope serves a broad range of applications in neuroscience, developmental biology, and even physics.

An arginine-rich nuclear localization signal (ArgiNLS) strategy for streamlined image segmentation of single-cells

High-throughput volumetric fluorescent microscopy pipelines can spatially integrate whole-brain structure and function at the foundational level of single-cells. However, conventional fluorescent protein (FP) modifications used to discriminate single-cells possess limited efficacy or are detrimental to cellular health. Here, we introduce a synthetic and non-deleterious nuclear localization signal (NLS) tag strategy, called 'Arginine-rich NLS' (ArgiNLS), that optimizes genetic labeling and downstream image segmentation of single-cells by restricting FP localization near-exclusively in the nucleus through a poly-arginine mechanism. A single N-terminal ArgiNLS tag provides modular nuclear restriction consistently across spectrally separate FP variants. ArgiNLS performance in vivo displays functional conservation across major cortical cell classes, and in response to both local and systemic brain wide AAV administration. Crucially, the high signal-to-noise ratio afforded by ArgiNLS enhances ML-automated segmentation of single-cells due to rapid classifier training and enrichment of labeled cell detection within 2D brain sections or 3D volumetric whole-brain image datasets, derived from both staining-amplified and native signal. This genetic strategy provides a simple and flexible basis for precise image segmentation of genetically labeled single-cells at scale and paired with behavioral procedures.

Fluorescence Microscopy: a statistics-optics perspective

Fundamental properties of light unavoidably impose features on images collected using fluorescence microscopes. Modeling these features is ever more important in quantitatively interpreting microscopy images collected at scales on par or smaller than light's wavelength. Here we review the optics responsible for generating fluorescent images, fluorophore properties, microscopy modalities leveraging properties of both light and fluorophores, in addition to the necessarily probabilistic modeling tools imposed by the stochastic nature of light and measurement.

Deep self-learning enables fast, high-fidelity isotropic resolution restoration for volumetric fluorescence microscopy

One intrinsic yet critical issue that troubles the field of fluorescence microscopy ever since its introduction is the unmatched resolution in the lateral and axial directions (i.e., resolution anisotropy), which severely deteriorates the quality, reconstruction, and analysis of 3D volume images. By leveraging the natural anisotropy, we present a deep self-learning method termed Self-Net that significantly improves the resolution of axial images by using the lateral images from the same raw dataset as rational targets. By incorporating unsupervised learning for realistic anisotropic degradation and supervised learning for high-fidelity isotropic recovery, our method can effectively suppress the hallucination with substantially enhanced image quality compared to previously reported methods. In the experiments, we show that Self-Net can reconstruct high-fidelity isotropic 3D images from organelle to tissue levels via raw images from various microscopy platforms, e.g., wide-field, laser-scanning, or super-resolution microscopy. For the first time, Self-Net enables isotropic whole-brain imaging at a voxel resolution of 0.2 × 0.2 × 0.2 μm3, which addresses the last-mile problem of data quality in single-neuron morphology visualization and reconstruction with minimal effort and cost. Overall, Self-Net is a promising approach to overcoming the inherent resolution anisotropy for all classes of 3D fluorescence microscopy.

Signal Improved ultra-Fast Light-sheet Microscope (SIFT) for large tissue imaging

Light-sheet fluorescence microscopy (LSFM) in conjunction with tissue clearing techniques enables morphological investigation of large tissues faster and with excellent optical sectioning. Recently, cleared tissue axially swept light-sheet microscope (ctASLM) demonstrated three-dimensional isotropic resolution in millimeter-scaled tissues. But ASLM based microscopes suffer from low detection signal and slow imaging speed. Here we report a simple and efficient imaging platform that employs precise control of two fixed distant light-sheet foci to carry out ASLM. This allowed us to carry out full field of view (FOV) imaging at 40 frames per second (fps) which is a four-fold improvement compared to the current state-of-the-art. In addition, in a particular frame rate, our method doubles the signal compared to the current ASLM technique. To augment the overall imaging performance, we also developed a deep learning based tissue information classifier that enables faster determination of tissue boundary. We demonstrated the performance of our imaging platform on various cleared tissue samples and demonstrated its robustness over a wide range of clearing protocols.

Light-sheets and smart microscopy, an exciting future is dawning

Light-sheet fluorescence microscopy has transformed our ability to visualize and quantitatively measure biological processes rapidly and over long time periods. In this review, we discuss current and future developments in light-sheet fluorescence microscopy that we expect to further expand its capabilities. This includes smart and adaptive imaging schemes to overcome traditional imaging trade-offs, i.e., spatiotemporal resolution, field of view and sample health. In smart microscopy, a microscope will autonomously decide where, when, what and how to image. We further assess how image restoration techniques provide avenues to overcome these tradeoffs and how "open top" light-sheet microscopes may enable multi-modal imaging with high throughput. As such, we predict that light-sheet microscopy will fulfill an important role in biomedical and clinical imaging in the future.

Light sheet imaging and interactive analysis of the cardiac structure in neonatal mice

Light-sheet microscopy (LSM) enables us to strengthen the understanding of cardiac development, injury, and regeneration in mammalian models. This emerging technique decouples laser illumination and fluorescence detection to investigate cardiac micro-structure and function with a high spatial resolution while minimizing photodamage and maximizing penetration depth. To unravel the potential of volumetric imaging in cardiac development and repair, we sought to integrate our in-house LSM, Adipo-Clear, and virtual reality (VR) with neonatal mouse hearts. We demonstrate the use of Adipo-Clear to render mouse hearts transparent, the development of our in-house LSM to capture the myocardial architecture within the intact heart, and the integration of VR to explore, measure, and assess regions of interests in an interactive manner. Collectively, we have established an innovative and holistic strategy for image acquisition and interpretation, providing an entry point to assess myocardial micro-architecture throughout the entire mammalian heart for the understanding of cardiac morphogenesis.

Large-scale expanded sample imaging with tiling lattice lightsheet microscopy

The ability to observe biological nanostructures forms a vital step in understanding their functions. Thanks to the invention of expansion microscopy (ExM) technology, super-resolution features of biological samples can now be easily visualized with conventional light microscopies. However, when the sample is physically expanded, the demand for deep and precise 3D imaging increases. Lattice lightsheet microscopy (LLSM), which utilizes a planar illumination that is confined within the imaging depth of high numerical aperture (NA=1.1) detection objective, fulfils such requirements. In addition, optical tiling could be implemented to increase the field of view (FoV) by moving the lightsheet without mechanically moving the samples or the objective for high-precision 3D imaging. In this review article, we will explain the principle of the tiling lattice lightsheet microscopy (tLLSM), which combines optical tiling and lattice lightsheet, and discuss the applications of tLLSM in ExM.

Fine-grained, nonlinear registration of live cell movies reveals spatiotemporal organization of diffuse molecular processes

We present an application of nonlinear image registration to align in microscopy time lapse sequences for every frame the cell outline and interior with the outline and interior of the same cell in a reference frame. The registration relies on a subcellular fiducial marker, a cell motion mask, and a topological regularization that enforces diffeomorphism on the registration without significant loss of granularity. This allows spatiotemporal analysis of extremely noisy and diffuse molecular processes across the entire cell. We validate the registration method for different fiducial markers by measuring the intensity differences between predicted and original time lapse sequences of Actin cytoskeleton images and by uncovering zones of spatially organized GEF- and GTPase signaling dynamics visualized by FRET-based activity biosensors in MDA-MB-231 cells. We then demonstrate applications of the registration method in conjunction with stochastic time-series analysis. We describe distinct zones of locally coherent dynamics of the cytoplasmic protein Profilin in U2OS cells. Further analysis of the Profilin dynamics revealed strong relationships with Actin cytoskeleton reorganization during cell symmetry-breaking and polarization. This study thus provides a framework for extracting information to explore functional interactions between cell morphodynamics, protein distributions, and signaling in cells undergoing continuous shape changes. Matlab code implementing the proposed registration method is available at https://github.com/DanuserLab/Mask-Regularized-Diffeomorphic-Cell-Registration.