A Flexible Chamber for Time-Lapse Live-Cell Imaging with Stimulated Raman Scattering Microscopy.

Stimulated Raman scattering (SRS) microscopy is a label-free chemical imaging technology. Live-cell imaging with SRS has been demonstrated for many biological and biomedical applications. However, long-term time-lapse SRS imaging of live cells has not been widely adopted. SRS microscopy often uses a high numerical aperture (NA) water-immersion objective and a high NA oil-immersion condenser to achieve high-resolution imaging. In this case, the gap between the objective and the condenser is only a few millimeters. Therefore, most commercial stage-top environmental chambers cannot be used for SRS imaging because of their large thickness with a rigid glass cover. This paper describes the design and fabrication of a flexible chamber that can be used for time-lapse live-cell imaging with transmitted SRS signal detection on an upright microscope frame. The flexibility of the chamber is achieved by using a soft material - a thin natural rubber film. The new enclosure and chamber design can be easily added to an existing SRS imaging setup. The testing and preliminary results demonstrate that the flexible chamber system enables stable, long-term, time-lapse SRS imaging of live cells, which can be used for various bioimaging applications in the future.

Development of Planar Illumination Strategies for Solving Mysteries in the Sub-Cellular Realm.

Optical microscopy has vastly expanded the frontiers of structural and functional biology, due to the non-invasive probing of dynamic volumes in vivo. However, traditional widefield microscopy illuminating the entire field of view (FOV) is adversely affected by out-of-focus light scatter. Consequently, standard upright or inverted microscopes are inept in sampling diffraction-limited volumes smaller than the optical system's point spread function (PSF). Over the last few decades, several planar and structured (sinusoidal) illumination modalities have offered unprecedented access to sub-cellular organelles and 4D (3D + time) image acquisition. Furthermore, these optical sectioning systems remain unaffected by the size of biological samples, providing high signal-to-noise (SNR) ratios for objective lenses (OLs) with long working distances (WDs). This review aims to guide biologists regarding planar illumination strategies, capable of harnessing sub-micron spatial resolution with a millimeter depth of penetration.

STED and parallelized RESOLFT optical nanoscopy of the tubular endoplasmic reticulum and its mitochondrial contacts in neuronal cells.

The classic view of organelle cell biology is undergoing a constant revision fueled by the new insights unraveled by fluorescence nanoscopy, which enable sensitive, faster and gentler observation of specific proteins in situ. The endoplasmic reticulum (ER) is one of the most challenging structure to capture due the rapid and constant restructuring of fine sheets and tubules across the full 3D cell volume. Here we apply STED and parallelized 2D and 3D RESOLFT live imaging to uncover the tubular ER organization in the fine processes of neuronal cells with focus on mitochondria-ER contacts, which recently gained medical attention due to their role in neurodegeneration. Multi-color STED nanoscopy enables the simultaneous visualization of small transversal ER tubules crossing and constricting mitochondria all along axons and dendrites. Parallelized RESOLFT allows for dynamic studies of multiple contact sites within seconds and minutes with prolonged time-lapse imaging at ~50 nm spatial resolution. When operated in 3D super resolution mode it enables a new isotropic visualization of such contacts extending our understanding of the three-dimensional architecture of these packed structures in axons and dendrites.

3DeeCellTracker, a deep learning-based pipeline for segmenting and tracking cells in 3D time lapse images.

Despite recent improvements in microscope technologies, segmenting and tracking cells in three-dimensional time-lapse images (3D + T images) to extract their dynamic positions and activities remains a considerable bottleneck in the field. We developed a deep learning-based software pipeline, 3DeeCellTracker, by integrating multiple existing and new techniques including deep learning for tracking. With only one volume of training data, one initial correction, and a few parameter changes, 3DeeCellTracker successfully segmented and tracked ~100 cells in both semi-immobilized and 'straightened' freely moving worm's brain, in a naturally beating zebrafish heart, and ~1000 cells in a 3D cultured tumor spheroid. While these datasets were imaged with highly divergent optical systems, our method tracked 90-100% of the cells in most cases, which is comparable or superior to previous results. These results suggest that 3DeeCellTracker could pave the way for revealing dynamic cell activities in image datasets that have been difficult to analyze.

Microscopes have been used to decrypt the tiny details of life since the 17th century. Now, the advent of 3D microscopy allows scientists to build up detailed pictures of living cells and tissues. In that effort, automation is becoming increasingly important so that scientists can analyze the resulting images and understand how bodies grow, heal and respond to changes such as drug therapies. In particular, algorithms can help to spot cells in the picture (called cell segmentation), and then to follow these cells over time across multiple images (known as cell tracking). However, performing these analyses on 3D images over a given period has been quite challenging. In addition, the algorithms that have already been created are often not user-friendly, and they can only be applied to a specific dataset gathered through a particular scientific method. As a response, Wen et al. developed a new program called 3DeeCellTracker, which runs on a desktop computer and uses a type of artificial intelligence known as deep learning to produce consistent results. Crucially, 3DeeCellTracker can be used to analyze various types of images taken using different types of cutting-edge microscope systems. And indeed, the algorithm was then harnessed to track the activity of nerve cells in moving microscopic worms, of beating heart cells in a young small fish, and of cancer cells grown in the lab. This versatile tool can now be used across biology, medical research and drug development to help monitor cell activities.

Visualizing three-dimensional fungal growth using light sheet fluorescence microscopy.

The evaluation of morphology is fundamental to comprehend how fungi grow, develop, and interact with the environment. Although fungal growth has been extensively studied associated to two-dimensional geometries, lack of appropriate experimental tools has limited exploration of the complex three-dimensional (3D) structures exhibited by mycelia in more general contexts. In this paper, we report the construction of a light-sheet fluorescence microscope (LSFM) capable of performing time-lapse visualization of 3D biological structures (4D microscopy), and the use of this instrument to follow the dynamics of fungal growth. LSFM uses scanning of selective plane illumination and digital reconstruction to provide 3D images of the specimen. We describe the optical, electronic, and computational means to implement two-color LSFM, and provide detailed procedures for aligning and testing the setup. We successfully demonstrate use of both autofluorescence and specific tagging to image Trichoderma atroviride and Neurospora crassa strains growing in liquid media, over extended times (~12 h) and volumes (~400 × 1500 × 800 µm3) at single-hypha resolution. The excellent image contrast provided by LSFM enables us to visualize the dynamics of mycelial architecture, interactions among hyphae, and measure rates of 3D apical extension. Altogether, our work shows a powerful imaging tool to perform 3D morphological analysis of fungi, from hyphae to mycelium.

Analyzing the Roles of Rho GTPases in Cancer Cell Adhesion to Endothelial Cells Under Flow Conditions.

Adhesion between cancer cells and endothelial cells, lining the blood vessels, is an important event in tumor progression and metastasis formation. The expression of Rho GTPases is frequently altered in cancers, and they are known to regulate cell migration through their effects on adhesion and cytoskeletal dynamics. Several different types of assays are used to investigate how cancer cells attach to and cross the endothelium. Here, we describe an in vitro technique to study the effects of Rho GTPases on human cancer cell adhesion to endothelial cells under shear stress coupled to live cell imaging.

A simple automated approach to measure mouse whole gut transit.

BACKGROUND: Gastrointestinal (GI) motility is a complex physiological process that is critical for normal GI function. Disruption of GI motility frequently occurs in GI diseases or as side effects of therapeutics. Whole gut transit measurements, like carmine red leading-edge transit, in mice form the cornerstone of in vivo preclinical GI motility studies. METHOD: We have developed an easily achievable, labor-saving method to measure whole gut transit time in mice. This approach uses inexpensive, commercially available materials to monitor pellet production over time via high definition cameras capturing time-lapse video for offline analysis. KEY RESULT: We describe the assembly of our automated gut transit setup and validate this approach by comparing the results with loperamide to delay transit and conventional transit measurements. We demonstrate that compared to the control group, the loperamide group had slowed transit, evidenced by a decrease in total pellet production and prolonged whole gut transit time. The control group had an extended transit time compared with the results reported in the literature. Whole gut transit rates accelerated to times comparable to the literature by disrupting cages every 10-15 min to imitate the conventional approach, suggesting that disruption affects the assay and supports the use of an automated approach. CONCLUSION & INFERENCES: A novel automated, inexpensive, and easily assembled whole gut transit setup is labor-saving and allows minimal disruption to animal behavior compared with the conventional approach.

In vivo biomolecular imaging of zebrafish embryos using confocal Raman spectroscopy.

Zebrafish embryos provide a unique opportunity to visualize complex biological processes, yet conventional imaging modalities are unable to access intricate biomolecular information without compromising the integrity of the embryos. Here, we report the use of confocal Raman spectroscopic imaging for the visualization and multivariate analysis of biomolecular information extracted from unlabeled zebrafish embryos. We outline broad applications of this method in: (i) visualizing the biomolecular distribution of whole embryos in three dimensions, (ii) resolving anatomical features at subcellular spatial resolution, (iii) biomolecular profiling and discrimination of wild type and ΔRD1 mutant Mycobacterium marinum strains in a zebrafish embryo model of tuberculosis and (iv) in vivo temporal monitoring of the wound response in living zebrafish embryos. Overall, this study demonstrates the application of confocal Raman spectroscopic imaging for the comparative bimolecular analysis of fully intact and living zebrafish embryos.

Motion magnification analysis of microscopy videos of biological cells.

It is well recognized that isolated cardiac muscle cells beat in a periodic manner. Recently, evidence indicates that other, non-muscle cells, also perform periodic motions that are either imperceptible under conventional lab microscope lens or practically not easily amenable for analysis of oscillation amplitude, frequency, phase of movement and its direction. Here, we create a real-time video analysis tool to visually magnify and explore sub-micron rhythmic movements performed by biological cells and the induced movements in their surroundings. Using this tool, we suggest that fibroblast cells perform small fluctuating movements with a dominant frequency that is dependent on their surrounding substrate and its stiffness.

In Vivo Calcium Imaging During Axon Degeneration in Zebrafish.

In vivo calcium imaging in zebrafish provides the ability to investigate calcium dynamics within neurons. Utilizing genetically encoded calcium sensors it is possible to monitor calcium signals within a single axon during axon injury and degeneration with high temporal and spatial resolution. Here we will describe in vivo, time-lapse confocal imaging methods of calcium imaging. Imaging of calcium dynamics with genetically encoded calcium sensors (GECS) within living axons can serve as a method to assess axonal physiology and effects of pharmacologic and genetic manipulation, as well as characterize responses to different injury models.

Compact and reflective light-sheet microscopy for long-term imaging of living embryos.

The development of light-sheet fluorescence microscopy has been a revolution for developmental biology as it allows long-term imaging during embryonic development. An important reason behind the quick adoption has been the availability of open hardware alternatives. In this work, we present a robust and compact version of a light-sheet fluorescence microscope that is easy to assemble and requires little to no maintenance. An important aspect of the design is that the illumination unit consists of reflective elements, thereby reducing chromatic aberrations an order of magnitude as compared to refractive counterparts.

Time-lapse technology for embryo culture and selection.

Culturing of human embryos in optimal conditions is crucial for a successful in vitro fertilisation (IVF) programme. In addition, the capacity to assess and rank embryos correctly for quality will allow for transfer of the potentially 'best' embryo first, thereby shortening the time to pregnancy, although not improving cumulative pregnancy and live birth rates. It will also encourage and facilitate the implementation of single embryo transfers, thereby increasing safety for mother and offspring. Time-lapse technology introduces the concept of stable culture conditions, in connection with the possibility of continuous viewing and documenting of the embryo throughout development. However, so far, even when embryo quality scoring is based on large datasets, or when using the time-lapse technology, the morphokinetic scores are still mainly based on subjective and intermittent annotations of morphology and timings. Also, the construction of powerful algorithms for widespread use is hampered by large variations in culture conditions between individual IVF laboratories. New methodology, involving machine learning, where every image from the time-lapse documentation is analysed by a computer programme, looking for patterns that link to outcome, may in the future provide a more accurate and non-biased embryo selection.

Isolating live cells after high-throughput, long-term, time-lapse microscopy.

Single-cell genetic screens can be incredibly powerful, but current high-throughput platforms do not track dynamic processes, and even for non-dynamic properties they struggle to separate mutants of interest from phenotypic outliers of the wild-type population. Here we introduce SIFT, single-cell isolation following time-lapse imaging, to address these limitations. After imaging and tracking individual bacteria for tens of consecutive generations under tightly controlled growth conditions, cells of interest are isolated and propagated for downstream analysis, free of contamination and without genetic or physiological perturbations. This platform can characterize tens of thousands of cell lineages per day, making it possible to accurately screen complex phenotypes without the need for barcoding or genetic modifications. We applied SIFT to identify a set of ultraprecise synthetic gene oscillators, with circuit variants spanning a 30-fold range of average periods. This revealed novel design principles in synthetic biology and demonstrated the power of SIFT to reliably screen diverse dynamic phenotypes.

Spatiotemporal Characterizations of Spontaneously Beating Cardiomyocytes with Adaptive Reference Digital Image Correlation.

We developed an Adaptive Reference-Digital Image Correlation (AR-DIC) method that enables unbiased and accurate mechanics measurements of moving biological tissue samples. We applied the AR-DIC analysis to a spontaneously beating cardiomyocyte (CM) tissue, and could provide correct quantifications of tissue displacement and strain for the beating CMs utilizing physiologically-relevant, sarcomere displacement length-based contraction criteria. The data were further synthesized into novel spatiotemporal parameters of CM contraction to account for the CM beating homogeneity, synchronicity, and propagation as holistic measures of functional myocardial tissue development. Our AR-DIC analyses may thus provide advanced non-invasive characterization tools for assessing the development of spontaneously contracting CMs, suggesting an applicability in myocardial regenerative medicine.

Distinguishing perforin-mediated lysis and granzyme-dependent apoptosis.

Perforin is an indispensable effector protein of primary cytotoxic lymphocytes (CTL or NK cells) that typically defend the host against virus infection, or gene-modified (chimeric antigen receptor-CAR) anticancer T cells. Perforin's pore-forming activity is necessary for the delivery of proapoptotic serine proteases, granzymes, into the cytosol of infected or cancerous target cells. The complete loss of perforin function is detrimental for the function of cytotoxic lymphocytes, and leads to fatal immune dysregulation in infants and predisposes the carriers of hypomorphic perforin mutations to various chronic inflammatory sequelae and blood cancers. Here, we describe several optimized and validated functional assays using purified effector proteins and cytotoxic lymphocytes that enable detailed analysis of perforin-mediated target cell death pathways.

Visible-wavelength two-photon excitation microscopy with multifocus scanning for volumetric live-cell imaging.

Two-photon excitation microscopy is one of the key techniques used to observe three-dimensional (3-D) structures in biological samples. We utilized a visible-wavelength laser beam for two-photon excitation in a multifocus confocal scanning system to improve the spatial resolution and image contrast in 3-D live-cell imaging. Experimental and numerical analyses revealed that the axial resolution has improved for a wide range of pinhole sizes used for confocal detection. We observed the 3-D movements of the Golgi bodies in living HeLa cells with an imaging speed of 2 s per volume. We also confirmed that the time-lapse observation up to 8 min did not cause significant cell damage in two-photon excitation experiments using wavelengths in the visible light range. These results demonstrate that multifocus, two-photon excitation microscopy with the use of a visible wavelength can constitute a simple technique for 3-D visualization of living cells with high spatial resolution and image contrast.

Ultra-sensitive digital quantification of proteins and mRNA in single cells.

Simultaneous measurement of proteins and mRNA in single cells enables quantitative understanding and modeling of cellular functions. Here, we present an automated microfluidic system for multi-parameter and ultra-sensitive protein/mRNA measurements in single cells. Our technology improves the sensitivity of digital proximity ligation assay by up to 55-fold, with a detection limit of 2277 proteins per cell and with detection efficiency of as few as 29 protein molecules. Our measurements using this system reveal higher mRNA/protein correlation in single mammalian cells than previous estimates. Furthermore, time-lapse imaging of herpes simplex virus 1 infected epithelial cells enabled by our device shows that expression of ICP4 -a major transcription factor regulating hundreds of viral genes- is only partially correlated with viral protein counts, suggesting that many cells go through abortive infection. These results highlight the importance of high-sensitivity protein/mRNA quantification for understanding fundamental molecular mechanisms in individual cells.

Coincidence Analysis of Molecular Dynamics by Raster Image Correlation Spectroscopy.

The dynamics of cellular processes is a crucial aspect to consider when trying to understand cell function, particularly with regard to the coordination of complex mechanisms involving extensive molecular networks in different cell compartments. Thus, there is an urgent demand of methodologies able to obtain accurate spatiotemporal information on molecular dynamics in live cells. Different variants based on fluorescence correlation spectroscopy have been used successfully in the analysis of protein diffusion and complex or aggregation status. However, the available approaches are limited when simultaneous spatial and temporal resolutions are required to analyze fast processes. Here we describe the use of raster image correlation spectroscopy to analyze the spatiotemporal coincidence of collaborating proteins in highly dynamic molecular mechanisms.

3D Tracking of Migrating Cells from Live Microscopy Time-Lapses.

With rapidly advancing microscopy techniques for live cell imaging, we are now able to image groups of migrating cells in many different in vivo contexts. However, as the resulting data sets become larger and more complex, following the behavior of these cells and extracting accurate quantitative data become increasingly challenging. Here we present a protocol for carrying out accurate automated tracking of cells moving over time in 3D, implemented as custom-built macro scripts for ImageJ. As opposed to many generic tracking workflows, the workflow we propose here accounts for the overall movement of the embryo, allows the selection of subgroups of cells, and includes a step for the complete assisted review of all 3D tracks. Furthermore, it is easy to add new custom track measurement to the code provided. Together, these present a reliable method for the precise tracking of cells, from which distinct subsets of cells can be selected from within a population.

2D + Time Object Tracking Using Fiji and ilastik.

Tracking cells is one of the main challenges in biology, as it often requires time-consuming annotations and the images can have a low signal-to-noise ratio while containing a large number of cells. Here we present two methods for detecting and tracking cells using the open-source Fiji and ilastik frameworks. A straightforward approach is described using Fiji, consisting of a pre-processing and segmentation phase followed by a tracking phase, based on the overlapping of objects along the image sequence. Using ilastik, a classifier is trained through manual annotations to both detect cells over the background and be able to recognize false detections and merging cells. We describe these two methods in a step-by-step fashion, using as example a time-lapse microscopy movie of HeLa cells.