Surprises from Intravital Imaging of the Innate Immune Response.

Successful immune responses depend on the spatiotemporal coordination of immune cell migration, interactions, and effector functions in lymphoid and parenchymal tissues. Real-time intravital microscopy has revolutionized our understanding of the dynamic behavior of many immune cell types in the living tissues of several species. Observing immune cells in their native environment has revealed many unanticipated facets of their biology, which were not expected from experiments outside a living organism. Here we highlight both classic and more recent examples of surprising discoveries that critically relied on the use of live in vivo imaging. In particular, we focus on five major cell types of the innate immune response (macrophages, microglia, neutrophils, dendritic cells, and mast cells), and how studying their dynamics in mouse tissues has helped us advance our current knowledge of immune cell-mediated tissue homeostasis, host defense, and inflammation.

Intravital three-photon microscopy allows visualization over the entire depth of mouse lymph nodes.

Intravital confocal microscopy and two-photon microscopy are powerful tools to explore the dynamic behavior of immune cells in mouse lymph nodes (LNs), with penetration depth of ~100 and ~300 µm, respectively. Here, we used intravital three-photon microscopy to visualize the popliteal LN through its entire depth (600-900 µm). We determined the laser average power and pulse energy that caused measurable perturbation in lymphocyte migration. Long-wavelength three-photon imaging within permissible parameters was able to image the entire LN vasculature in vivo and measure CD8+ T cells and CD4+ T cell motility in the T cell zone over the entire depth of the LN. We observed that the motility of naive CD4+ T cells in the T cell zone during lipopolysaccharide-induced inflammation was dependent on depth. As such, intravital three-photon microscopy had the potential to examine immune cell behavior in the deeper regions of the LN in vivo.

CXCR1 and CXCR2 Chemokine Receptor Agonists Produced by Tumors Induce Neutrophil Extracellular Traps that Interfere with Immune Cytotoxicity.

Neutrophils are expanded and abundant in cancer-bearing hosts. Under the influence of CXCR1 and CXCR2 chemokine receptor agonists and other chemotactic factors produced by tumors, neutrophils, and granulocytic myeloid-derived suppressor cells (MDSCs) from cancer patients extrude their neutrophil extracellular traps (NETs). In our hands, CXCR1 and CXCR2 agonists proved to be the major mediators of cancer-promoted NETosis. NETs wrap and coat tumor cells and shield them from cytotoxicity, as mediated by CD8+ T cells and natural killer (NK) cells, by obstructing contact between immune cells and the surrounding target cells. Tumor cells protected from cytotoxicity by NETs underlie successful cancer metastases in mice and the immunotherapeutic synergy of protein arginine deiminase 4 (PAD4) inhibitors, which curtail NETosis with immune checkpoint inhibitors. Intravital microscopy provides evidence of neutrophil NETs interfering cytolytic cytotoxic T lymphocytes (CTLs) and NK cell contacts with tumor cells.

Skinny deeping: Uncovering immune cell behavior and function through imaging techniques.

As the largest organ of the body, the skin is a key barrier tissue with specialized structures where ongoing immune surveillance is critical for protecting the body from external insults. The innate immune system acts as first-responders in a coordinated manner to react to injury or infections, and recent developments in intravital imaging techniques have made it possible to delineate dynamic immune cell responses in a spatiotemporal manner. We review here key studies involved in understanding neutrophil, dendritic cell and macrophage behavior in skin and further discuss how this knowledge collectively highlights the importance of interactions and cellular functions in a systems biology manner. Furthermore, we will review emerging imaging technologies such as high-content proteomic screening, spatial transcriptomics and three-dimensional volumetric imaging and how these techniques can be integrated to provide a systems overview of the immune system that will further our current knowledge and lead to potential exciting discoveries in the upcoming decades.

Imaging viral infection in vivo to gain unique perspectives on cellular antiviral immunity.

The past decade has seen near continual global public health crises caused by emerging viral infections. Extraordinary increases in our knowledge of the mechanisms underlying successful antiviral immune responses in animal models and during human infection have accompanied these viral outbreaks. Keeping pace with the rapidly advancing field of viral immunology, innovations in microscopy have afforded a previously unseen view of viral infection occurring in real-time in living animals. Here, we review the contribution of intravital imaging to our understanding of cell-mediated immune responses to viral infections, with a particular focus on studies that visualize the antiviral effector cells responding to infection as well as virus-infected cells. We discuss methods to visualize viral infection in vivo using intravital microscopy (IVM) and significant findings arising through the application of IVM to viral infection. Collectively, these works underscore the importance of developing a comprehensive spatial understanding of the relationships between immune effectors and virus-infected cells and how this has enabled unique discoveries about virus/host interactions and antiviral effector cell biology.

Imaging reveals novel innate immune responses in lung, liver, and beyond.

Highly dynamic immune responses are generated toward pathogens or injuries, in vivo. Multiple immune cell types participate in various facets of the response which leads to a concerted effort in the removal and clearance of pathogens or injured tissue and a return to homeostasis. Intravital microscopy (IVM) has been extensively utilized to unravel the dynamics of immune responses, visualizing immune cell behavior in intact living tissues, within a living organism. For instance, the phenomenon of leukocyte recruitment cascade. Importantly, IVM has led to a deep appreciation that immune cell behavior and responses in individual organs are distinct, but also can influence one another. In this review, we discuss how IVM as a tool has been used to study the innate immune responses in various tissues during homeostasis, injury, and infection.

Moving beyond velocity: Opportunities and challenges to quantify immune cell behavior.

The analysis of cellular behavior using intravital multi-photon microscopy has contributed substantially to our understanding of the priming and effector phases of immune responses. Yet, many questions remain unanswered and unexplored. Though advancements in intravital imaging techniques and animal models continue to drive new discoveries, continued improvements in analysis methods are needed to extract detailed information about cellular behavior. Focusing on dendritic cell (DC) and T cell interactions as an exemplar, here we discuss key limitations for intravital imaging studies and review and explore alternative approaches to quantify immune cell behavior. We touch upon current developments in deep learning models, as well as established methods from unrelated fields such as ecology to detect and track objects over time. As developments in open-source software make it possible to process and interactively view larger datasets, the challenge for the field will be to determine how best to combine intravital imaging with multi-parameter imaging of larger tissue regions to discover new facets of leukocyte dynamics and how these contribute to immune responses.

Imaging innate immunity.

Innate immunity is the first line of defense against infectious intruders and also plays a major role in the development of sterile inflammation. Direct microscopic imaging of the involved immune cells, especially neutrophil granulocytes, monocytes, and macrophages, has been performed since more than 150 years, and we still obtain novel insights on a frequent basis. Initially, intravital microscopy was limited to small-sized animal species, which were often invertebrates. In this review, we will discuss recent results on the biology of neutrophils and macrophages that have been obtained using confocal and two-photon microscopy of individual cells or subcellular structures as well as light-sheet microscopy of entire organs. This includes the role of these cells in infection defense and sterile inflammation in mammalian disease models relevant for human patients. We discuss their protective but also disease-enhancing activities during tumor growth and ischemia-reperfusion damage of the heart and brain. Finally, we provide two visions, one experimental and one applied, how our knowledge on the function of innate immune cells might be further enhanced and also be used in novel ways for disease diagnostics in the future.

Immunomodulation under the lens of real-time in vivo imaging.

Modulation of cells and molecules of the immune system not only represents a major opportunity to treat a variety of diseases including infections, cancer, autoimmune, and inflammatory disorders but could also help understand the intricacies of immune responses. A detailed mechanistic understanding of how a specific immune intervention may provide clinical benefit is essential for the rational design of efficient immunomodulators. Visualizing the impact of immunomodulation in real-time and in vivo has emerged as an important approach to achieve this goal. In this review, we aim to illustrate how multiphoton intravital imaging has helped clarify the mode of action of immunomodulatory strategies such as antibodies or cell therapies. We also discuss how optogenetics combined with imaging will further help manipulate and precisely understand immunomodulatory pathways. Combined with other single-cell technologies, in vivo dynamic imaging has therefore a major potential for guiding preclinical development of immunomodulatory drugs.

Modeling the Drug delivery Lifecycle of PLG Nanoparticles Using Intravital Microscopy.

Polylactide-co-glycolide (PLG) nanoparticles hold immense promise for cancer therapy due to their enhanced efficacy and biodegradable matrix structure. Understanding their interactions with blood cells and subsequent biodistribution kinetics is crucial for optimizing their therapeutic potential. In this study, three doxorubicin-loaded PLG nanoparticle systems are synthesized and characterized, analyzing their size, zeta potential, morphology, and in vitro release behavior. Employing intravital microscopy in 4T1-tumor-bearing mice, real-time blood and tumor distribution kinetics are investigated. A mechanistic pharmacokinetic model is used to analyze biodistribution kinetics. Additionally, flow cytometry is utilized to identify cells involved in nanoparticle hitchhiking. Following intravenous injection, PLG nanoparticles exhibit an initial burst release (<1 min) and rapidly adsorb to blood cells (<5 min), hindering extravasation. Agglomeration leads to the clearance of one carrier species within 3 min. In stable dispersions, drug release rather than extravasation remains the dominant pathway for drug elimination from circulation. This comprehensive investigation provides valuable insights into the interplay between competing kinetics that influence the lifecycle of PLG nanoparticles post-injection. The findings advance the understanding of nanoparticle behavior and lay the foundation for improved cancer therapy strategies using nanoparticle-based drug delivery systems.

Revealing spatio-temporal dynamics with long-term trypanosomatid live-cell imaging.

Trypanosoma brucei, the causative agent of human African trypanosomiasis, is highly motile and must be able to move in all three dimensions for reliable cell division. These characteristics make long-term microscopic imaging of live T. brucei cells challenging, which has limited our understanding of important cellular events. To address this issue, we devised an imaging approach that confines cells in small volumes within cast agarose microwells that can be imaged continuously for up to 24 h. Individual T. brucei cells were imaged through multiple rounds of cell division with high spatial and temporal resolution. We developed a strategy that employs in-well "sentinel" cells to monitor potential imaging toxicity during loss-of-function experiments such as small-molecule inhibition and RNAi. Using our approach, we show that the asymmetric daughter cells produced during T. brucei division subsequently divide at different rates, with the old-flagellum daughter cell dividing first. The flagellar detachment phenotype that appears during inhibition of the Polo-like kinase homolog TbPLK occurs in a stepwise fashion, with the new flagellum initially linked by its tip to the old, attached flagellum. We probe the feasibility of a previously proposed "back-up" cytokinetic mechanism and show that cells that initiate this process do not appear to complete cell division. This live-cell imaging method will provide a novel avenue for studying a wide variety of cellular events in trypanosomatids that have previously been inaccessible.

CANCOL, a Computer-Assisted Annotation Tool to Facilitate Colocalization and Tracking of Immune Cells in Intravital Microscopy.

Two-photon intravital microscopy (2P-IVM) has become a widely used technique to study cell-to-cell interactions in living organisms. Four-dimensional imaging data obtained via 2P-IVM are classically analyzed by performing automated cell tracking, a procedure that computes the trajectories followed by each cell. However, technical artifacts, such as brightness shifts, the presence of autofluorescent objects, and channel crosstalking, affect the specificity of imaging channels for the cells of interest, thus hampering cell detection. Recently, machine learning has been applied to overcome a variety of obstacles in biomedical imaging. However, existing methods are not tailored for the specific problems of intravital imaging of immune cells. Moreover, results are highly dependent on the quality of the annotations provided by the user. In this study, we developed CANCOL, a tool that facilitates the application of machine learning for automated tracking of immune cells in 2P-IVM. CANCOL guides the user during the annotation of specific objects that are problematic for cell tracking when not properly annotated. Then, it computes a virtual colocalization channel that is specific for the cells of interest. We validated the use of CANCOL on challenging 2P-IVM videos from murine organs, obtaining a significant improvement in the accuracy of automated tracking while reducing the time required for manual track curation.

Deep learning for in vivo near-infrared imaging.

Detecting fluorescence in the second near-infrared window (NIR-II) up to ∼1,700 nm has emerged as a novel in vivo imaging modality with high spatial and temporal resolution through millimeter tissue depths. Imaging in the NIR-IIb window (1,500-1,700 nm) is the most effective one-photon approach to suppressing light scattering and maximizing imaging penetration depth, but relies on nanoparticle probes such as PbS/CdS containing toxic elements. On the other hand, imaging the NIR-I (700-1,000 nm) or NIR-IIa window (1,000-1,300 nm) can be done using biocompatible small-molecule fluorescent probes including US Food and Drug Administration-approved dyes such as indocyanine green (ICG), but has a caveat of suboptimal imaging quality due to light scattering. It is highly desired to achieve the performance of NIR-IIb imaging using molecular probes approved for human use. Here, we trained artificial neural networks to transform a fluorescence image in the shorter-wavelength NIR window of 900-1,300 nm (NIR-I/IIa) to an image resembling an NIR-IIb image. With deep-learning translation, in vivo lymph node imaging with ICG achieved an unprecedented signal-to-background ratio of >100. Using preclinical fluorophores such as IRDye-800, translation of ∼900-nm NIR molecular imaging of PD-L1 or EGFR greatly enhanced tumor-to-normal tissue ratio up to ∼20 from ∼5 and improved tumor margin localization. Further, deep learning greatly improved in vivo noninvasive NIR-II light-sheet microscopy (LSM) in resolution and signal/background. NIR imaging equipped with deep learning could facilitate basic biomedical research and empower clinical diagnostics and imaging-guided surgery in the clinic.

Objective Analysis of Corneal Nerves and Dendritic Cells. / Objektive Analyse von Hornhautnerven und dendritischen Zellen.

Corneal nerves and dendritic cells are increasingly being visualised to serve as clinical parameters in the diagnosis of ocular surface diseases using intravital confocal microscopy. In this review, different methods of image analysis are presented. The use of deep learning algorithms, which enable automated pattern recognition, is explained in detail using our own developments and compared with other established methods.

Bellymount enables longitudinal, intravital imaging of abdominal organs and the gut microbiota in adult Drosophila.

Cell- and tissue-level processes often occur across days or weeks, but few imaging methods can capture such long timescales. Here, we describe Bellymount, a simple, noninvasive method for longitudinal imaging of the Drosophila abdomen at subcellular resolution. Bellymounted animals remain live and intact, so the same individual can be imaged serially to yield vivid time series of multiday processes. This feature opens the door to longitudinal studies of Drosophila internal organs in their native context. Exploiting Bellymount's capabilities, we track intestinal stem cell lineages and gut microbial colonization in single animals, revealing spatiotemporal dynamics undetectable by previously available methods.

Computationally enhanced quantitative phase microscopy reveals autonomous oscillations in mammalian cell growth.

The fine balance of growth and division is a fundamental property of the physiology of cells, and one of the least understood. Its study has been thwarted by difficulties in the accurate measurement of cell size and the even greater challenges of measuring growth of a single cell over time. We address these limitations by demonstrating a computationally enhanced methodology for quantitative phase microscopy for adherent cells, using improved image processing algorithms and automated cell-tracking software. Accuracy has been improved more than twofold and this improvement is sufficient to establish the dynamics of cell growth and adherence to simple growth laws. It is also sufficient to reveal unknown features of cell growth, previously unmeasurable. With these methodological and analytical improvements, in several cell lines we document a remarkable oscillation in growth rate, occurring throughout the cell cycle, coupled to cell division or birth yet independent of cell cycle progression. We expect that further exploration with this advanced tool will provide a better understanding of growth rate regulation in mammalian cells.

Functional characterization of 67 endocytic accessory proteins using multiparametric quantitative analysis of CCP dynamics.

Clathrin-mediated endocytosis (CME) begins with the nucleation of clathrin assembly on the plasma membrane, followed by stabilization and growth/maturation of clathrin-coated pits (CCPs) that eventually pinch off and internalize as clathrin-coated vesicles. This highly regulated process involves a myriad of endocytic accessory proteins (EAPs), many of which are multidomain proteins that encode a wide range of biochemical activities. Although domain-specific activities of EAPs have been extensively studied, their precise stage-specific functions have been identified in only a few cases. Using single-guide RNA (sgRNA)/dCas9 and small interfering RNA (siRNA)-mediated protein knockdown, combined with an image-based analysis pipeline, we have determined the phenotypic signature of 67 EAPs throughout the maturation process of CCPs. Based on these data, we show that EAPs can be partitioned into phenotypic clusters, which differentially affect CCP maturation and dynamics. Importantly, these clusters do not correlate with functional modules based on biochemical activities. Furthermore, we discover a critical role for SNARE proteins and their adaptors during early stages of CCP nucleation and stabilization and highlight the importance of GAK throughout CCP maturation that is consistent with GAK's multifunctional domain architecture. Together, these findings provide systematic, mechanistic insights into the plasticity and robustness of CME.

Intravital Microscopy of Lipopolysaccharide-Induced Inflammatory Changes in Different Organ Systems-A Scoping Review.

Intravital microscopy (IVM) is a powerful imaging tool that captures biological processes in real-time. IVM facilitates the observation of complex cellular interactions in vivo, where ex vivo and in vitro experiments lack the physiological environment. IVM has been used in a multitude of studies under healthy and pathological conditions in different organ systems. IVM has become essential in the characterization of the immune response through visualization of leukocyte-endothelial interactions and subsequent changes within the microcirculation. Lipopolysaccharide (LPS), a common inflammatory trigger, has been used to induce inflammatory changes in various studies utilizing IVM. In this review, we provide an overview of IVM imaging of LPS-induced inflammation in different models, such as the brain, intestines, bladder, and lungs.

Intravital Dynamic and Correlative Imaging of Mouse Livers Reveals Diffusion-Dominated Canalicular and Flow-Augmented Ductular Bile Flux.

BACKGROUND AND AIMS: Small-molecule flux in tissue microdomains is essential for organ function, but knowledge of this process is scant due to the lack of suitable methods. We developed two independent techniques that allow the quantification of advection (flow) and diffusion in individual bile canaliculi and in interlobular bile ducts of intact livers in living mice, namely fluorescence loss after photoactivation and intravital arbitrary region image correlation spectroscopy. APPROACH AND RESULTS: The results challenge the prevailing "mechano-osmotic" theory of canalicular bile flow. After active transport across hepatocyte membranes, bile acids are transported in the canaliculi primarily by diffusion. Only in the interlobular ducts is diffusion augmented by regulatable advection. Photoactivation of fluorescein bis-(5-carboxymethoxy-2-nitrobenzyl)-ether in entire lobules demonstrated the establishment of diffusive gradients in the bile canalicular network and the sink function of interlobular ducts. In contrast to the bile canalicular network, vectorial transport was detected and quantified in the mesh of interlobular bile ducts. CONCLUSIONS: The liver consists of a diffusion-dominated canalicular domain, where hepatocytes secrete small molecules and generate a concentration gradient and a flow-augmented ductular domain, where regulated water influx creates unidirectional advection that augments the diffusive flux.

COVID-19 detection from red blood cells using highly comparative time-series analysis (HCTSA) in digital holographic microscopy.

We present an automated method for COVID-19 screening based on reconstructed phase profiles of red blood cells (RBCs) and a highly comparative time-series analysis (HCTSA). Video digital holographic data -was obtained using a compact, field-portable shearing microscope to capture the temporal fluctuations and spatio-temporal dynamics of live RBCs. After numerical reconstruction of the digital holographic data, the optical volume is calculated at each timeframe of the reconstructed data to produce a time-series signal for each cell in our dataset. Over 6000 features are extracted on the time-varying optical volume sequences using the HCTSA to quantify the spatio-temporal behavior of the RBCs, then a linear support vector machine is used for classification of individual RBCs. Human subjects are then classified for COVID-19 based on the consensus of their cells' classifications. The proposed method is tested on a dataset of 1472 RBCs from 24 human subjects (10 COVID-19 positive, 14 healthy) collected at UConn Health Center. Following a cross-validation procedure, our system achieves 82.13% accuracy, with 92.72% sensitivity, and 73.21% specificity (area under the receiver operating characteristic curve: 0.8357). Furthermore, the proposed system resulted in 21 out of 24 human subjects correctly labeled. To the best of our knowledge this is the first report of a highly comparative time-series analysis using digital holographic microscopy data.