Live Imaging Data Research Articles

Deep Learning-driven Automatic Nuclei Segmentation of Label-free Live Cell Chromatin-sensitive Partial Wave Spectroscopic Microscopy Imaging.

Chromatin-sensitive Partial Wave Spectroscopic (csPWS) microscopy offers a non-invasive glimpse into the mass density distribution of cellular structures at the nanoscale, leveraging the spectroscopic information. Such capability allows us to analyze the chromatin structure and organization and the global transcriptional state of the cell nuclei for the study of its role in carcinogenesis. Accurate segmentation of the nuclei in csPWS microscopy images is an essential step in isolating them for further analysis. However, manual segmentation is error-prone, biased, time-consuming, and laborious, resulting in disrupted nuclear boundaries with partial or over-segmentation. Here, we present an innovative deep-learning-driven approach to automate the accurate nuclei segmentation of label-free live cell csPWS microscopy imaging data. Our approach, csPWS-seg, harnesses the Convolutional Neural Networks-based U-Net model with an attention mechanism to automate the accurate cell nuclei segmentation of csPWS microscopy images. We leveraged the structural, physical, and biological differences between the cytoplasm, nucleus, and nuclear periphery to construct three distinct csPWS feature images for nucleus segmentation. Using these images of HCT116 cells, csPWS-seg achieved superior performance with a median Intersection over Union (IoU) of 0.80 and a Dice Similarity Coefficient (DSC) score of 0.88. The csPWS-seg overcame the segmentation performance over the baseline U-Net model and another attention-based model, SE-U-Net, marking a significant improvement in segmentation accuracy. Further, we analyzed the performance of our proposed model with four loss functions: binary cross-entropy loss, focal loss, dice loss, and Jaccard loss. The csPWS-seg with focal loss provided the best results compared to other loss functions. The automatic and accurate nuclei segmentation offered by the csPWS-seg not only automates, accelerates, and streamlines csPWS data analysis but also enhances the reliability of subsequent chromatin analysis research, paving the way for more accurate diagnostics, treatment, and understanding of cellular mechanisms for carcinogenesis.

Multi-detector fusion and Bayesian smoothing for tracking viral and chromatin structures

Automatic tracking of viral and intracellular structures displayed as spots with varying sizes in fluorescence microscopy images is an important task to quantify cellular processes. We propose a novel probabilistic tracking approach for multiple particle tracking based on multi-detector and multi-scale data fusion as well as Bayesian smoothing. The approach integrates results from multiple detectors using a novel intensity-based covariance intersection method which takes into account information about the image intensities, positions, and uncertainties. The method ensures a consistent estimate of multiple fused particle detections and does not require an optimization step. Our probabilistic tracking approach performs data fusion of detections from classical and deep learning methods as well as exploits single-scale and multi-scale detections. In addition, we use Bayesian smoothing to fuse information of predictions from both past and future time points. We evaluated our approach using image data of the Particle Tracking Challenge and achieved state-of-the-art results or outperformed previous methods. Our method was also assessed on challenging live cell fluorescence microscopy image data of viral and cellular proteins expressed in hepatitis C virus-infected cells and chromatin structures in non-infected cells, acquired at different spatial–temporal resolutions. We found that the proposed approach outperforms existing methods.

Free-breathing high-resolution respiratory-gated radial stack-of-stars magnetic resonance imaging of the upper abdomen at 7 T.

Ultrahigh field magnetic resonance imaging (MRI) (≥ 7 T) has the potential to provide superior spatial resolution and unique image contrast. Apart from radiofrequency transmit inhomogeneities in the body at this field strength, imaging of the upper abdomen faces additional challenges associated with motion-induced ghosting artifacts. To address these challenges, the goal of this work was to develop a technique for high-resolution free-breathing upper abdominal MRI at 7 T with a large field of view. Free-breathing 3D gradient-recalled echo (GRE) water-excited radial stack-of-stars data were acquired in seven healthy volunteers (five males/two females, body mass index: 19.6-24.8 kg/m2) at 7 T using an eight-channel transceive array coil. Two volunteers were also examined at 3 T. In each volunteer, the liver and kidney regions were scanned in two separate acquisitions. To homogenize signal excitation, the time-interleaved acquisition of modes (TIAMO) method was used with personalized pairs of B1 shims, based on a 23-s Cartesian fast low angle shot(FLASH) acquisition. Utilizing free-induction decay navigator signals, respiratory-gated images were reconstructed at a spatial resolution of 0.8 × 0.8 × 1.0 mm3. Two experienced radiologists rated the image quality and the impact of B1 inhomogeneity and motion-related artifacts on multipoint scales. The images of all volunteers showcased effective water excitation and were accurately corrected for respiratory motion. The impact of B1 inhomogeneity on image quality was minimal, underscoring the efficacy of the multitransmit TIAMO shim. The high spatial resolution allowed excellent depiction of small structures such as the adrenal glands, the proximal ureter, the diaphragm, and small blood vessels, although some streaking artifacts persisted in liver image data. In direct comparisons with 3 T performed for two volunteers, 7-T acquisitions demonstrated increases in signal-to-noise ratio of 77% and 58%. Overall, this work demonstrates the feasibility of free-breathing MRI in the upper abdomen at submillimeter spatial resolution at a magnetic field strength of 7 T.

Harnessing artificial intelligence to reduce phototoxicity in live imaging.

Fluorescence microscopy is essential for studying living cells, tissues and organisms. However, the fluorescent light that switches on fluorescent molecules also harms the samples, jeopardizing the validity of results - particularly in techniques such as super-resolution microscopy, which demands extended illumination. Artificial intelligence (AI)-enabled software capable of denoising, image restoration, temporal interpolation or cross-modal style transfer has great potential to rescue live imaging data and limit photodamage. Yet we believe the focus should be on maintaining light-induced damage at levels that preserve natural cell behaviour. In this Opinion piece, we argue that a shift in role for AIs is needed - AI should be used to extract rich insights from gentle imaging rather than recover compromised data from harsh illumination. Although AI can enhance imaging, our ultimate goal should be to uncover biological truths, not just retrieve data. It is essential to prioritize minimizing photodamage over merely pushing technical limits. Our approach is aimed towards gentle acquisition and observation of undisturbed living systems, aligning with the essence of live-cell fluorescence microscopy.

Image restoration of degraded time-lapse microscopy data mediated by near-infrared imaging.

Time-lapse fluorescence microscopy is key to unraveling biological development and function; however, living systems, by their nature, permit only limited interrogation and contain untapped information that can only be captured by more invasive methods. Deep-tissue live imaging presents a particular challenge owing to the spectral range of live-cell imaging probes/fluorescent proteins, which offer only modest optical penetration into scattering tissues. Herein, we employ convolutional neural networks to augment live-imaging data with deep-tissue images taken on fixed samples. We demonstrate that convolutional neural networks may be used to restore deep-tissue contrast in GFP-based time-lapse imaging using paired final-state datasets acquired using near-infrared dyes, an approach termed InfraRed-mediated Image Restoration (IR2). Notably, the networks are remarkably robust over a wide range of developmental times. We employ IR2 to enhance the information content of green fluorescent protein time-lapse images of zebrafish and Drosophila embryo/larval development and demonstrate its quantitative potential in increasing the fidelity of cell tracking/lineaging in developing pescoids. Thus, IR2 is poised to extend live imaging to depths otherwise inaccessible.

Identifying Chromosome Movement Patterns During Meiosis Using ChroMo.

During meiosis, transient associations between the nuclear envelope and telomeres transmit nuclear movements to chromosomes, enabling their pairing and recombination. Recent advances in the field of quantitative cell biology allow a large volume of information about the kinetics of these chromosome movements to be extracted and analyzed with the aim of identifying biologically relevant movement patterns. To this end, we have developed ChroMo, a freely available application for the unsupervised study of chromosome movements in fission yeast meiosis. ChroMo contains a set of time series algorithms to identify chromosome movement motifs that are not easily observable by direct human visualization and to establish causal relationships between phenotypes. In this chapter, we present a detailed protocol for the processing of raw live imaging data from fission yeast and its subsequent analysis in ChroMo.

Dynamics of macrophage tumor infiltration

Long-term remission in cancer patients treated with ex vivo bona fide M1-induced macrophages has been poor, and the reasons behind this are not understood. Injected M1 macrophages must physically migrate to tumors to execute their role that leads to a therapeutic benefit. However, the trafficking of macrophages to tumors has not been rigorously studied. We hypothesized that trafficking capabilities of macrophages are impacted when naïve M0 macrophages are converted into an M1 phenotype for macrophage therapy. To test this, we developed a three-dimensional assay comprising a tumor spheroid and macrophages to quantify macrophage tumor transport. Cell migration, permeability, and kinetics of tumor entry were quantitatively defined and compared between macrophage phenotypes. Our results demonstrate that compared to M0 macrophages, M1 macrophages migrate less efficiently toward the tumor spheroid and exhibit a fivefold lower tumor permeability. Live imaging data combined with unsupervised machine learning algorithms reveal that macrophage migration correlates with their shape transitions. Our studies highlight the importance of transport considerations in determining the efficacy of cell therapies. This study quantitatively demonstrates that the transport properties of macrophages in tumors depend on their phenotype.

Human Embryo Live Imaging Reveals Nuclear DNA Shedding During Blastocyst Expansion and Biopsy

ABSTRACT The proportion of babies born from in vitro fertilization (IVF) is rising at an exponential rate, highlighting the importance that we have a comprehensive understanding of human preimplantation development and determinants of embryo quality. The early divisions of the embryo after fertilization but before implantation and resulting mitotic errors have been studied primarily in the mouse embryo; however, thus far we have lacked the technology to characterize these critical steps in humans. Establishing an approach that can bypass genetic manipulation and microinjections of DNA or mRNA into human embryos would allow us to better uncover the processes patterning preimplantation human development. This study aimed to evaluate human blastocyst preimplantation development with noninvasive imaging using membrane permeable fluorescent dyes. First, the dyes SPY650-DNA, which labels genomic DNA, and SPY555-actin, which labels F-actin, were validated in the mouse embryo where they produced high contrast labelling with similar results to microinjection of fluorescent mRNAs and produced offspring at a similar rate to nondyed control embryos. Live imaging data using these dyes enabled 3-dimensional scans of the embryo at 5- to 10-minute intervals of the following central events during preimplantation development: the main phases of mitosis, visualizing the major changes in cell shape that characterize embryo compaction at the 8-cell stage, detecting cell polarization at the 8-cell stage, establishing apical F-actin rings at the 16-cell stage, tracking the expansion and zippering of F-actin rings, detecting the first internalized cells within the 16-cell embryo, and visualizing blastocyst expansion and hatching from the zona pellucida. Cleavage-stage human IVF embryos were then studied using the fluorescent dyes to track early cellular and morphogenetic processes. Early cell-cycle dynamics and mitotic stages revealed that the duration of human mitosis is similar to that of mice, but interphase is 27% ± 4% longer in humans (16.1 ± 0.9 vs 12.7 ± 0.4 hours; P < 0.01). Using live imaging, compaction dynamics such as increased cell-cell contact and angle between apical membranes with a decrease in cell sphericity were observed beginning at the 12-cell stage and differed significantly from development in mice. In comparison to mice, human compaction was found to be more asynchronous and did not have clear links to apical polarization or inner-outer segregation. Next, chromosomal segregation was analyzed to determine if this approach allowed detection of segregation errors in the human embryo leading to aneuploidy. Lagging chromosomes detected in human embryos using SPY-DNA appeared morphologically similar to those found in mouse embryos and had similar segregation dynamics. During blastocyst expansion, a subset of trophectoderm cell nuclei forms protruding bud-like that is shed into cytoplasm producing cytoplasmic DNA structures (cytDNA), suggesting an additional process of DNA loss different from chromosome segregation errors during mitosis. A perinuclear keratin network developing at the early cavitation stage appears to protect from formation of cytDNA structures, and the mechanical stress of blastocyst expansion appeared to disrupt the keratin network in certain cells, increasing DNA shedding. Next, trophectoderm biopsy was conducted in mouse, and human embryos to determine if the mechanical stress would increase DNA shedding. Biopsy of human blastocysts resulted in a significant increase in nuclear budding (6.0% vs 0.70%; P = 0.0022), suggesting a link between mechanical stress and DNA shedding. This study demonstrates the use of fluorescent dyes and live imaging in characterization of key cellular and morphogenetic processes patterning the preimplantation human embryo and describes a process of DNA shedding in response to mechanical stressors that warrants future research.

Quantitative Analysis of the Coordinated Movement of Cells in a Freely Moving Cell Population

Coordinated movement of self-propelled agents has been well studied in collectives or swarms that display directional movement. Self-propelled agents also develop stable spatial patterns in which the agents do not necessarily exhibit directional collective movement. However, quantitative measures that are required to analyze the local and temporal coordinated movements during pattern formation processes have not been well established. Here, we study the coordinated movement of individual pairs of two different types of cells in a freely moving cell population. We introduced three criteria to evaluate coordinated movement in live imaging data obtained from the abdomen of the fruit fly, Drosophila melanogaster, at the pupal stage. All three criteria were able to reasonably identify coordinated movement. Our analysis indicates that the combined usage of these criteria can improve the evaluation of whether a pair of cells exhibits coordinated movement or not by excluding false positives. Quantitative approaches to identifying coordinated movement in a population of freely moving agents constitute a key foundational methodology to study pattern formations by self-propelled agents.

Schrödinger Dynamics and Berry Phase of Undulatory Locomotion.

Spectral mode representations play an essential role in various areas of physics, from quantum mechanics to fluid turbulence, but they are not yet extensively used to characterize and describe the behavioral dynamics of living systems. Here, we show that mode-based linear models inferred from experimental live-imaging data can provide an accurate low-dimensional description of undulatory locomotion in worms, centipedes, robots, and snakes. By incorporating physical symmetries and known biological constraints into the dynamical model, we find that the shape dynamics are generically governed by Schrödinger equations in mode space. The eigenstates of the effective biophysical Hamiltonians and their adiabatic variations enable the efficient classification and differentiation of locomotion behaviors in natural, simulated, and robotic organisms using Grassmann distances and Berry phases. While our analysis focuses on a widely studied class of biophysical locomotion phenomena, the underlying approach generalizes to other physical or living systems that permit a mode representation subject to geometric shape constraints.

Using Zebrafish to Dissect the Interaction of Mycobacteria with the Autophagic Machinery in Macrophages.

Existing drug treatment against tuberculosis is no match against the increasing number of multi-drug resistant strains of its causative agent, Mycobacterium tuberculosis (Mtb). A better understanding of how mycobacteria subvert the host immune defenses is crucial for developing novel therapeutic strategies. A potential approach is enhancing the activity of the autophagy machinery, which can direct bacteria to autophagolysosomal degradation. However, the interplay specifics between mycobacteria and the autophagy machinery must be better understood. Here, we analyzed live imaging data from the zebrafish model of tuberculosis to characterize mycobacteria-autophagy interactions during the early stages of infection in vivo. For high-resolution imaging, we microinjected fluorescent Mycobacterium marinum (Mm) into the tail fin tissue of zebrafish larvae carrying the GFP-LC3 autophagy reporter. We detected phagocytosed Mm clusters and LC3-positive Mm-containing vesicles within the first hour of infection. LC3 associations with these vesicles were transient and heterogeneous, ranging from simple vesicles to complex compound structures, dynamically changing shape by fusions between Mm-containing and empty vesicles. LC3-Mm-vesicles could adopt elongated shapes during cell migration or alternate between spacious and compact morphologies. LC3-Mm-vesicles were also observed in cells reverse migrating from the infection site, indicating that the autophagy machinery fails to control infection before tissue dissemination.

Quantifying Single and Dual Channel Live Imaging Data: Kymograph Analysis of Organelle Motility in Neurons.

Live imaging is commonly used to study dynamic processes in cells. Many labs carrying out live imaging in neurons use kymographs as a tool. Kymographs display time-dependent microscope data (time-lapsed images) in two-dimensional representations showing position vs. time. Extraction of quantitative data from kymographs, often done manually, is time-consuming and not standardized across labs. We describe here our recent methodology for quantitatively analyzing single color kymographs. We discuss the challenges and solutions of reliably extracting quantifiable data from single-channel kymographs. When acquiring in two fluorescent channels, the challenge becomes analyzing two objects that may co-traffic together. One must carefully examine the kymographs from both channels and decide which tracks are the same or try to identify the coincident tracks from an overlay of the two channels. This process is laborious and time consuming. The difficulty in finding an available tool for such analysis has led us to create a program to do so, called KymoMerge. KymoMerge semi-automates the process of identifying co-located tracks in multi-channel kymographs and produces a co-localized output kymograph that can be analyzed further. We describe our analysis, caveats, and challenges of two-color imaging using KymoMerge.

Collision avoidance and adaptive path planning in machine tools by matching live image data with a geometric simulation

Collision avoidance and adaptive path planning in machine tools by matching live image data with a geometric simulation

The effect of stiffness and hole size on nipple compression in infant suckling.

During infant feeding, the nipple is an important source of sensory information that affects motor outputs, including ones dealing with compression of the nipple, suction, milk bolus movement, and swallowing. Despite known differences in behavior across commercially available nipples, little is known about the in vivo effects of nipple property variation. Here we quantify the effect of differences in nipple stiffness and hole size on an easily measured metric representing infant feeding behavior: nipple compression. We bottle-fed 7-day old infant pigs (n = 6) on four custom fabricated silicone nipples. We recorded live X-ray fluoroscopic imaging data of feeding on nipples of two levels of hardness/stiffness and two hole sizes. We tested for differences in nipple compression at the nipple's maximum compression across different nipple types using a mixed model analysis of variance. Stiffer nipples and those with smaller holes were compressed less than compliant nipples and nipples with larger holes (p < 0.001). We also estimated the force applied on the nipple during feeding and found that more force was applied to the compliant nipple with disproportionately larger strains. Our results suggest that infant pigs' nipple compression depends on material type and hole size, which is likely detected by the infant pigs' initial assessment of compressibility and flow. By isolating nipple properties, we demonstrated a relationship between properties and suckling behavior. Our results suggest that sensory information affects feeding behaviors and may also inform clinical treatment of poor feeding performance.

A missense mutation in the proprotein convertase gene furinb causes hepatic cystogenesis during liver development in zebrafish.

Hepatic cysts are fluid‐filled lesions in the liver that are estimated to occur in 5% of the population. They may cause hepatomegaly and abdominal pain. Progression to secondary fibrosis, cirrhosis, or cholangiocarcinoma can lead to morbidity and mortality. Previous studies of patients and rodent models have associated hepatic cyst formation with increased proliferation and fluid secretion in cholangiocytes, which are partially due to impaired primary cilia. Congenital hepatic cysts are thought to originate from faulty bile duct development, but the underlying mechanisms are not fully understood. In a forward genetic screen, we identified a zebrafish mutant that developed hepatic cysts during larval stages. The cyst formation was not due to changes in biliary cell proliferation, bile secretion, or impairment of primary cilia. Instead, time‐lapse live imaging data showed that the mutant biliary cells failed to form interconnecting bile ducts because of defects in motility and protrusive activity. Accordingly, immunostaining revealed a disorganized actin and microtubule cytoskeleton in the mutant biliary cells. By whole‐genome sequencing, we determined that the cystic phenotype in the mutant was caused by a missense mutation in the furinb gene, which encodes a proprotein convertase. The mutation altered Furinb localization and caused endoplasmic reticulum (ER) stress. The cystic phenotype could be suppressed by treatment with the ER stress inhibitor 4‐phenylbutyric acid and exacerbated by treatment with the ER stress inducer tunicamycin. The mutant liver also exhibited increased mammalian target of rapamycin (mTOR) signaling. Treatment with mTOR inhibitors halted cyst formation at least partially through reducing ER stress. Conclusion: Our study has established a vertebrate model for studying hepatic cystogenesis and illustrated the contribution of ER stress in the disease pathogenesis.

4Dia: A tool for automated 4D microscope image alignment

<h2>Abstract</h2> Recent advances in microscopy enable three-dimensional live imaging at a high resolution. Long-term live imaging of a multicellular organism requires immobilization of the organism under stable physiological conditions. Despite proper immobilization, challenges remain within live imaging data analysis due to other intrinsic and extrinsic dynamics, which can result in misalignments of an image series over time. 4Dia, an ImageJ/Fiji macro script, aligns 3D timelapse images through Z-stacks as well as over time using any user selected channel. 4Dia can be used for essentially any tissue sample with no limit on the size of Z-stack or the number of timepoints.

Current approaches to fate mapping and lineage tracing using image data.

Visualizing, tracking and reconstructing cell lineages in developing embryos has been an ongoing effort for well over a century. Recent advances in light microscopy, labelling strategies and computational methods to analyse complex image datasets have enabled detailed investigations into the fates of cells. Combined with powerful new advances in genomics and single-cell transcriptomics, the field of developmental biology is able to describe the formation of the embryo like never before. In this Review, we discuss some of the different strategies and applications to lineage tracing in live-imaging data and outline software methodologies that can be applied to various cell-tracking challenges.

Direct visualization of local activities of long DNA strands via image\u2013time correlation

Bacteriophages with long DNA genomes are of interest due to their diverse mutations dependent on environmental factors. By lowering the ionic strength of a hydrophobic (PPh4Cl) antagonistic salt (at 1 mM), single long T4 DNA strand fluctuations were clearly observed, while condensed states of T4 DNA globules were formed above 5–10 mM salt. These long DNA strands were treated with fluorescently labeled probes, for which photo bleaching is often unavoidable over a short time of measurement. In addition, long (few tens of upmu m) length scales are required to have larger fields of view for better sampling, with shorter temporal resolutions. Thus, an optimization between length and time is crucial to obtain useful information. To facilitate the challenge of detecting large biomacromolecules, we here introduce an effective method of live image data analysis for direct visualization and quantification of local thermal fluctuations. The motions of various conformations for the motile long DNA strands were examined for the single- and multi-T4 DNA strands. We find that the unique correlation functions exhibit a relatively high-frequency oscillatory behavior superimposed on the overall slower decay of the correlation function with a splitting of amplitudes deriving from local activities of the long DNA strands. This work shows not only the usefulness of an image–time correlation for analyzing large biomacromolecules, but also provides insight into the effects of a hydrophobic antagonistic salt on active T4 bacteriophage long DNA strands, including thermal translocations in their electrostatic interactions.

Cell fate coordinates mechano-osmotic forces in intestinal crypt formation.

Intestinal organoids derived from single cells undergo complex crypt-villus patterning and morphogenesis. However, the nature and coordination of the underlying forces remains poorly characterized. Through light-sheet microscopy and large-scale imaging quantification, we demonstrate that crypt formation coincides with stark lumen volume reduction. We develop a 3D biophysical model to computationally screen different mechanical scenarios of crypt morphogenesis. Combining this with live-imaging data and multiple mechanical perturbations, we show that actomyosin-driven crypt apical contraction and villus basal tension work synergistically with lumen volume reduction to drive crypt morphogenesis, and demonstrate the existence of a critical point in differential tensions above which crypt morphology becomes robust to volume changes. Finally, we identified a sodium/glucose cotransporter specific to differentiated enterocytes that modulates lumen volume reduction via cell swelling in villus region. Altogether, our study uncovers the cellular basis of how cell fate modulates osmotic and actomyosin forces to coordinate robust morphogenesis.

Modeling poliovirus replication dynamics from live time-lapse single-cell imaging data

Viruses experience selective pressure on the timing and order of events during infection to maximize the number of viable offspring they produce. Additionally, they may experience variability in cellular environments encountered, as individual eukaryotic cells can display variation in gene expression among cells. This leads to a dynamic phenotypic landscape that viruses must face to replicate. To examine replication dynamics displayed by viruses faced with this variable landscape, we have developed a method for fitting a stochastic mechanistic model of viral infection to time-lapse imaging data from high-throughput single-cell poliovirus infection experiments. The model’s mechanistic parameters provide estimates of several aspects associated with the virus’s intracellular dynamics. We examine distributions of parameter estimates and assess their variability to gain insight into the root causes of variability in viral growth dynamics. We also fit our model to experiments performed under various drug treatments and examine which parameters differ under these conditions. We find that parameters associated with translation and early stage viral replication processes are essential for the model to capture experimentally observed dynamics. In aggregate, our results suggest that differences in viral growth data generated under different treatments can largely be captured by steps that occur early in the replication process.