Distinct single-component adjuvants steer human DC-mediated T-cell polarization via Toll-like receptor signaling toward a potent antiviral immune response.

The COVID-19 pandemic highlights the importance of efficient and safe vaccine development. Vaccine adjuvants are essential to boost and tailor the immune response to the corresponding pathogen. To allow for an educated selection, we assessed the effect of different adjuvants on human monocyte-derived dendritic cells (DCs) and their ability to polarize innate and adaptive immune responses. In contrast to commonly used adjuvants, such as aluminum hydroxide, Toll-like receptor (TLR) agonists induced robust phenotypic and functional DC maturation. In a DC-lymphocyte coculture system, we investigated the ensuing immune reactions. While monophosphoryl lipid A synthetic, a TLR4 ligand, induced checkpoint inhibitors indicative for immune exhaustion, the TLR7/8 agonist Resiquimod (R848) induced prominent type-1 interferon and interleukin 6 responses and robust CTL, B-cell, and NK-cell proliferation, which is particularly suited for antiviral immune responses. The recently licensed COVID-19 vaccines, BNT162b and mRNA-1273, are both based on single-stranded RNA. Indeed, we could confirm that the cytokine profile induced by lipid-complexed RNA was almost identical to the pattern induced by R848. Although this awaits further investigation, our results suggest that their efficacy involves the highly efficient antiviral response pattern stimulated by the RNAs' TLR7/8 activation.

LocalZProjector and DeProj: a toolbox for local 2D projection and accurate morphometrics of large 3D microscopy images.

BACKGROUND: Quantitative imaging of epithelial tissues requires bioimage analysis tools that are widely applicable and accurate. In the case of imaging 3D tissues, a common preprocessing step consists of projecting the acquired 3D volume on a 2D plane mapping the tissue surface. While segmenting the tissue cells is amenable on 2D projections, it is still very difficult and cumbersome in 3D. However, for many specimen and models used in developmental and cell biology, the complex content of the image volume surrounding the epithelium in a tissue often reduces the visibility of the biological object in the projection, compromising its subsequent analysis. In addition, the projection may distort the geometry of the tissue and can lead to strong artifacts in the morphology measurement. RESULTS: Here we introduce a user-friendly toolbox built to robustly project epithelia on their 2D surface from 3D volumes and to produce accurate morphology measurement corrected for the projection distortion, even for very curved tissues. Our toolbox is built upon two components. LocalZProjector is a configurable Fiji plugin that generates 2D projections and height-maps from potentially large 3D stacks (larger than 40 GB per time-point) by only incorporating signal of the planes with local highest variance/mean intensity, despite a possibly complex image content. DeProj is a MATLAB tool that generates correct morphology measurements by combining the height-map output (such as the one offered by LocalZProjector) and the results of a cell segmentation on the 2D projection, hence effectively deprojecting the 2D segmentation in 3D. In this paper, we demonstrate their effectiveness over a wide range of different biological samples. We then compare its performance and accuracy against similar existing tools. CONCLUSIONS: We find that LocalZProjector performs well even in situations where the volume to project also contains unwanted signal in other layers. We show that it can process large images without a pre-processing step. We study the impact of geometrical distortions on morphological measurements induced by the projection. We measured very large distortions which are then corrected by DeProj, providing accurate outputs.

TrackMate: An open and extensible platform for single-particle tracking.

We present TrackMate, an open source Fiji plugin for the automated, semi-automated, and manual tracking of single-particles. It offers a versatile and modular solution that works out of the box for end users, through a simple and intuitive user interface. It is also easily scriptable and adaptable, operating equally well on 1D over time, 2D over time, 3D over time, or other single and multi-channel image variants. TrackMate provides several visualization and analysis tools that aid in assessing the relevance of results. The utility of TrackMate is further enhanced through its ability to be readily customized to meet specific tracking problems. TrackMate is an extensible platform where developers can easily write their own detection, particle linking, visualization or analysis algorithms within the TrackMate environment. This evolving framework provides researchers with the opportunity to quickly develop and optimize new algorithms based on existing TrackMate modules without the need of having to write de novo user interfaces, including visualization, analysis and exporting tools. The current capabilities of TrackMate are presented in the context of three different biological problems. First, we perform Caenorhabditis-elegans lineage analysis to assess how light-induced damage during imaging impairs its early development. Our TrackMate-based lineage analysis indicates the lack of a cell-specific light-sensitive mechanism. Second, we investigate the recruitment of NEMO (NF-κB essential modulator) clusters in fibroblasts after stimulation by the cytokine IL-1 and show that photodamage can generate artifacts in the shape of TrackMate characterized movements that confuse motility analysis. Finally, we validate the use of TrackMate for quantitative lifetime analysis of clathrin-mediated endocytosis in plant cells.

Bioimage analysis of Shigella infection reveals targeting of colonic crypts.

Few studies within the pathogenic field have used advanced imaging and analytical tools to quantitatively measure pathogenicity in vivo. In this work, we present a novel approach for the investigation of host-pathogen processes based on medium-throughput 3D fluorescence imaging. The guinea pig model for Shigella flexneri invasion of the colonic mucosa was used to monitor the infectious process over time with GFP-expressing S. flexneri. A precise quantitative imaging protocol was devised to follow individual S. flexneri in a large tissue volume. An extensive dataset of confocal images was obtained and processed to extract specific quantitative information regarding the progression of S. flexneri infection in an unbiased and exhaustive manner. Specific parameters included the analysis of S. flexneri positions relative to the epithelial surface, S. flexneri density within the tissue, and volume of tissue destruction. In particular, at early time points, there was a clear association of S. flexneri with crypts, key morphological features of the colonic mucosa. Numerical simulations based on random bacterial entry confirmed the bias of experimentally measured S. flexneri for early crypt targeting. The application of a correlative light and electron microscopy technique adapted for thick tissue samples further confirmed the location of S. flexneri within colonocytes at the mouth of crypts. This quantitative imaging approach is a novel means to examine host-pathogen systems in a tailored and robust manner, inclusive of the infectious agent.

Objective comparison of particle tracking methods.

Particle tracking is of key importance for quantitative analysis of intracellular dynamic processes from time-lapse microscopy image data. Because manually detecting and following large numbers of individual particles is not feasible, automated computational methods have been developed for these tasks by many groups. Aiming to perform an objective comparison of methods, we gathered the community and organized an open competition in which participating teams applied their own methods independently to a commonly defined data set including diverse scenarios. Performance was assessed using commonly defined measures. Although no single method performed best across all scenarios, the results revealed clear differences between the various approaches, leading to notable practical conclusions for users and developers.

Phenotypic clustering: a novel method for microglial morphology analysis.

BACKGROUND: Microglial cells are tissue-resident macrophages of the central nervous system. They are extremely dynamic, sensitive to their microenvironment and present a characteristic complex and heterogeneous morphology and distribution within the brain tissue. Many experimental clues highlight a strong link between their morphology and their function in response to aggression. However, due to their complex "dendritic-like" aspect that constitutes the major pool of murine microglial cells and their dense network, precise and powerful morphological studies are not easy to realize and complicate correlation with molecular or clinical parameters. METHODS: Using the knock-in mouse model CX3CR1(GFP/+), we developed a 3D automated confocal tissue imaging system coupled with morphological modelling of many thousands of microglial cells revealing precise and quantitative assessment of major cell features: cell density, cell body area, cytoplasm area and number of primary, secondary and tertiary processes. We determined two morphological criteria that are the complexity index (CI) and the covered environment area (CEA) allowing an innovative approach lying in (i) an accurate and objective study of morphological changes in healthy or pathological condition, (ii) an in situ mapping of the microglial distribution in different neuroanatomical regions and (iii) a study of the clustering of numerous cells, allowing us to discriminate different sub-populations. RESULTS: Our results on more than 20,000 cells by condition confirm at baseline a regional heterogeneity of the microglial distribution and phenotype that persists after induction of neuroinflammation by systemic injection of lipopolysaccharide (LPS). Using clustering analysis, we highlight that, at resting state, microglial cells are distributed in four microglial sub-populations defined by their CI and CEA with a regional pattern and a specific behaviour after challenge. CONCLUSIONS: Our results counteract the classical view of a homogenous regional resting state of the microglial cells within the brain. Microglial cells are distributed in different defined sub-populations that present specific behaviour after pathological challenge, allowing postulating for a cellular and functional specialization. Moreover, this new experimental approach will provide a support not only to neuropathological diagnosis but also to study microglial function in various disease models while reducing the number of animals needed to approach the international ethical statements.

In vitro characterization of Fluorescence by Unbound Excitation from Luminescence: broadening the scope of energy transfer.

Energy transfer mechanisms represent the basis for an array of valuable tools to infer interactions in vitro and in vivo, enhance detection or resolve interspecies distances such as with resonance. Based upon our own previously published studies and new results shown here we present a novel framework describing for the first time a model giving a view of the biophysical relationship between Fluorescence by Unbound Excitation from Luminescence (FUEL), a conventional radiative excitation-emission process, and bioluminescence resonance energy transfer. We show here that in homogeneous solutions and in fluorophore-targeted bacteria, FUEL is the dominant mechanism responsible for the production of red-shifted photons. The minor resonance contribution was ascertained by comparing the intensity of the experimental signal to its theoretical resonance counterpart. Distinctive features of the in vitro FUEL signal include a macroscopic depth dependency, a lack of enhancement upon targeting at a constant fluorophore concentration cf and a non-square dependency on cf. Significantly, FUEL is an important, so far overlooked, component of all resonance phenomena which should guide the design of appropriate controls when elucidating interactions. Last, our results highlight the potential for FUEL as a means to enhance in vivo and in vitro detection through complex media while alleviating the need for targeting.

In vivo excitation of nanoparticles using luminescent bacteria.

The lux operon derived from Photorhabdus luminescens incorporated into bacterial genomes, elicits the production of biological chemiluminescence typically centered on 490 nm. The light-producing bacteria are widely used for in vivo bioluminescence imaging. However, in living samples, a common difficulty is the presence of blue-green absorbers such as hemoglobin. Here we report a characterization of fluorescence by unbound excitation from luminescence, a phenomenon that exploits radiating luminescence to excite nearby fluorophores by epifluorescence. We show that photons from bioluminescent bacteria radiate over mesoscopic distances and induce a red-shifted fluorescent emission from appropriate fluorophores in a manner distinct from bioluminescence resonance energy transfer. Our results characterizing fluorescence by unbound excitation from luminescence, both in vitro and in vivo, demonstrate how the resulting blue-to-red wavelength shift is both necessary and sufficient to yield contrast enhancement revealing mesoscopic proximity of luminescent and fluorescent probes in the context of living biological tissues.

Deep learning in image-based phenotypic drug discovery.

Modern drug discovery approaches often use high-content imaging to systematically study the effect on cells of large libraries of chemical compounds. By automatically screening thousands or millions of images to identify specific drug-induced cellular phenotypes, for example, altered cellular morphology, these approaches can reveal 'hit' compounds offering therapeutic promise. In the past few years, artificial intelligence (AI) methods based on deep learning (DL) [a family of machine learning (ML) techniques] have disrupted virtually all image analysis tasks, from image classification to segmentation. These powerful methods also promise to impact drug discovery by accelerating the identification of effective drugs and their modes of action. In this review, we highlight applications and adaptations of ML, especially DL methods for cell-based phenotypic drug discovery (PDD).

MuscleJ2: a rebuilding of MuscleJ with new features for high-content analysis of skeletal muscle immunofluorescence slides.

Histological analysis of skeletal muscle is of major interest for understanding its behavior in different pathophysiological conditions, such as the response to different environments or myopathies. In this context, many software programs have been developed to perform automated high-content analysis. We created MuscleJ, a macro that runs in ImageJ/Fiji on batches of images. MuscleJ is a multianalysis tool that initially allows the analysis of muscle fibers, capillaries, and satellite cells. Since its creation, it has been used in many studies, and we have further developed the software and added new features, which are presented in this article. We converted the macro into a Java-language plugin with an improved user interface. MuscleJ2 provides quantitative analysis of fibrosis, vascularization, and cell phenotype in whole muscle sections. It also performs analysis of the peri-myonuclei, the individual capillaries, and any staining in the muscle fibers, providing accurate quantification within regional sublocalizations of the fiber. A multicartography option allows users to visualize multiple results simultaneously. The plugin is freely available to the muscle science community.

Corrigendum: Unveiling Interindividual Variability of Human Fibroblast Innate Immune Response Using Robust Cell-Based Protocols.

[This corrects the article DOI: 10.3389/fimmu.2020.569331.].

Unveiling Interindividual Variability of Human Fibroblast Innate Immune Response Using Robust Cell-Based Protocols.

The LabEx Milieu Interieur (MI) project is a clinical study centered on the detailed characterization of the baseline and induced immune responses in blood samples from 1,000 healthy donors. Analyses of these samples has lay ground for seminal studies on the genetic and environmental determinants of immunologic variance in a healthy cohort population. In the current study we developed in vitro methods enabling standardized quantification of MI-cohort-derived primary fibroblasts responses. Our results show that in vitro human donor cohort fibroblast responses to stimulation by different MAMPs analogs allows to characterize individual donor immune-phenotype variability. The results provide proof-of-concept foundation to a new experimental framework for such studies. A bio-bank of primary fibroblast lines was generated from 323 out of 1,000 healthy individuals selected from the MI-study cohort. To study inter-donor variability of innate immune response in primary human dermal fibroblasts we chose to measure the TLR3 and TLR4 response pathways, both receptors being expressed and previously studied in fibroblasts. We established high-throughput automation compatible methods for standardized primary fibroblast cell activation, using purified MAMPS analogs, poly I:C and LPS that stimulate TLR3 and TLR4 pathways respectively. These results were in turn compared with a stimulation method using infection by HSV-1 virus. Our "Add-only" protocol minimizes high-throughput automation system variability facilitating whole process automation from cell plating through stimulation to recovery of cell supernatants, and fluorescent labeling. Images were acquired automatically by high-throughput acquisition on an automated high-content imaging microscope. Under these methodological conditions standardized image acquisition provided for quantification of cellular responses allowing biological variability to be measured with low system noise and high biological signal fidelity. Optimal for automated analysis of immuno-phenotype of primary human cell responses our method and experimental framework as reported here is highly compatible to high-throughput screening protocols like those necessary for chemo-genomic screening. In context of primary fibroblasts derived from donors enrolled to the MI-clinical-study our results open the way to assert the utility of studying immune-phenotype characteristics relevant to a human clinical cohort.

Next-Generation Phenotypic Screening in Early Drug Discovery for Infectious Diseases.

Cell-based phenotypic screening has proven to be valuable, notably in recapitulating relevant biological conditions, for example, the host cell/pathogen niche. However, the corresponding methodological complexity is not readily compatible with high-throughput pipelines, and fails to inform either molecular target or mechanism of action, which frustrates conventional drug-discovery roadmaps. We review the state-of-the-art and emerging technologies that suggest new strategies for harnessing value from the complexity of phenotypic screening and augmenting powerful utility for translational drug discovery. Advances in cellular, molecular, and bioinformatics technologies are converging at a cutting edge where the complexity of phenotypic screening may no longer be considered a hinderance but rather a catalyst to chemotherapeutic discovery for infectious diseases.

Imaging of Red-Shifted Light From Bioluminescent Tumors Using Fluorescence by Unbound Excitation From Luminescence.

Early detection of tumors is today a major challenge and requires sensitive imaging methodologies coupled with new efficient probes. In vivo optical bioluminescence imaging has been widely used in the field of preclinical oncology to visualize tumors and several cancer cell lines have been genetically modified to provide bioluminescence signals. However, the light emitted by the majority of commonly used luciferases is usually in the blue part of the visible spectrum, where tissue absorption is still very high, making deep tissue imaging non-optimal, and calling for optimized optical imaging methodologies. We have previously shown that red-shifting of bioluminescence signal by Fluorescence Unbound Excitation from Luminescence (FUEL) is a mean to increase bioluminescence signal sensitivity detection in vivo. Here, we applied FUEL to tumor detection in two different subcutaneous tumor models: the auto-luminescent human embryonic kidney (HEK293) cell line and the murine B16-F10 melanoma cell line previously transfected with a plasmid encoding the Luc2 firefly luciferase. Tumor size and bioluminescence were measured over time and tumor vascularization characterized. We then locally injected near infrared emitting Quantum Dots (NIR QDs) in the tumor site and observed a red-shifting of bioluminescence signal by (FUEL) indicating that FUEL could be used to allow deeper tumor detection in mice.

Shigella-mediated oxygen depletion is essential for intestinal mucosa colonization.

Pathogenic enterobacteria face various oxygen (O2) levels during intestinal colonization from the O2-deprived lumen to oxygenated tissues. Using Shigella flexneri as a model, we have previously demonstrated that epithelium invasion is promoted by O2 in a type III secretion system-dependent manner. However, subsequent pathogen adaptation to tissue oxygenation modulation remained unknown. Assessing single-cell distribution, together with tissue oxygenation, we demonstrate here that the colonic mucosa O2 is actively depleted by S. flexneri aerobic respiration-and not host neutrophils-during infection, leading to the formation of hypoxic foci of infection. This process is promoted by type III secretion system inactivation in infected tissues, favouring colonizers over explorers. We identify the molecular mechanisms supporting infectious hypoxia induction, and demonstrate here how enteropathogens optimize their colonization capacity in relation to their ability to manipulate tissue oxygenation during infection.

Three-dimensional FRET reconstruction microscopy for analysis of dynamic molecular interactions in live cells.

Analysis of cellular pathways requires concentration measurements of dynamically interacting molecules within the three-dimensional (3D) space of single living cells. Förster resonance energy transfer (FRET) microscopy from widefield, from confocal, and potentially from superresolution microscopes can access this information; however, these measurements are distorted by the inherent 3D blurring of optical imaging, spectral overlap of fluorophores, and detection noise. We propose a mathematical model of these processes and demonstrate, through simulation, how these distortions limit the dynamic range and sensitivity of conventional FRET microscopy. Using this model, we devise and validate a new approach (called 3D-FRET stoichiometry reconstruction, 3DFSR) for reconstructing 3D distributions of bound and free fluorescent molecules. Previous attempts to reconstruct 3D-FRET data relied on sequential spectral unmixing and deconvolution, a process that corrupts the detection statistics. We demonstrate that 3DFSR is superior to these approaches since it simultaneously models spectral mixing, optical blurring, and detection noise. To achieve the full potential of this technique, we developed an instrument capable of acquiring 3D-FRET data rapidly and sensitively from single living cells. Compared with conventional FRET microscopy, our 3D-FRET reconstruction technique and new instrumentation provides orders of magnitude gains in both sensitivity and accuracy wherein sustained high-resolution four-dimensional (x,y,z,t) imaging of molecular interactions inside living cells was achieved. These results verify previous observations that Cdc42 signaling is localized to the advancing margins of forming phagosomes in macrophages.

A Bayesian reconstruction method for micro-rotation imaging in light microscopy.

The authors present a three-dimensional (3D) reconstruction algorithm and reconstruction-based deblurring method for light microscopy using a micro-rotation device. In contrast to conventional 3D optical imaging where the focal plane is shifted along the optical axis, micro-rotation imaging employs dielectric fields to rotate the object inside a fixed optical set-up. To address this entirely new 3D-imaging modality, the authors present a reconstruction algorithm based on Bayesian inversion theory and use the total variation function as a structure prior. The spectral properties of the reconstruction by simulations that illustrate the strengths and the weaknesses of the micro-rotation approach, compared with conventional 3D optical imaging, were studied. The reconstruction from real data sets shows that this method is promising for 3D reconstruction and offers itself as a deblurring method using a reconstruction-based procedure for removing out-of-focus light from the micro-rotation image series.

Electron-multiplying charge-coupled detector-based bioluminescence recording of single-cell Ca2+.

The construction and application of genetically encoded intracellular calcium concentration ([Ca2+]i) indicators has a checkered history. Excitement raised over the creation of new probes is often followed by disappointment when it is found that the initial demonstrations of [Ca2+]i sensing capability cannot be leveraged into real scientific advances. Recombinant apo-aequorin cloned from Aequorea victoria was the first Ca2+ sensitive protein genetically targeted to subcellular compartments. In the jellyfish, bioluminescence resonance energy transfer (BRET) between Ca2+ bound aequorin and green fluorescent protein (GFP) emits green light. Similarly, Ca2+ sensitive bioluminescent reporters undergoing BRET have been constructed between aequorin and GFP, and more recently with other fluorescent protein variants. These hybrid proteins display red-shifted spectrums and have higher light intensities and stability compared to aequorin alone. We report BRET measurement of single-cell [Ca2+]i based on the use of electron-multiplying charge-coupled-detector (EMCCD) imaging camera technology, mounted on either a bioluminescence or conventional microscope. Our results show for the first time how these new technologies make facile long-term monitoring of [Ca2+]i at the single-cell level, obviating the need for expensive, fragile, and sophisticated equipment based on image-photon-detectors (IPD) that were until now the only technical recourse to dynamic BRET experiments of this type.

Imaging today's infectious animalcules.

The study of pathogens and their interactions with host cells has advanced hand-in-hand with developments in optical microscopy. Whereas microbiology benefits enormously from modern imaging technologies, for example, digital imaging and confocal microscopy, it also presents unique challenges. To overcome these, microbiologists are adept at customising imaging methods, and recently there have been studies using state-of-the-art quantitative imaging methods to probe host-pathogen interactions at the single-cell level. Of particular interest are the studies using combined light and electron microscopy methods, bi-arsenical tetra-cysteine tag labelling and automated image-acquisition and analysis for high-throughput/high-content experimentation. These applications demonstrate how imaging methodologies, adapted for microbiology, continue to open avenues for studies that previously have proven inaccessible.

Imaging Intermediate Filaments and Microtubules with 2-dimensional Direct Stochastic Optical Reconstruction Microscopy.

The cytoskeleton, composed of actin microfilaments, microtubules, and intermediate filaments (IF), plays a key role in the control of cell shape, polarity, and motility. The organization of the actin and microtubule networks has been extensively studied but that of IFs is not yet fully characterized. IFs have an average diameter of 10 nm and form a network extending throughout the cell cytoplasm. They are physically associated with actin and microtubules through molecular motors and cytoskeletal linkers. This tight association is at the heart of the regulatory mechanisms that ensure the coordinated regulation of the three cytoskeletal networks required for most cell functions. It is therefore crucial to visualize IFs alone and also together with each of the other cytoskeletal networks. However, IF networks are extremely dense in most cell types, especially in glial cells, which makes its resolution very difficult to achieve with standard fluorescence microscopy (lateral resolution of ~250 nm). Direct STochastic Optical Reconstruction Microscopy (dSTORM) is a technique allowing a gain in lateral resolution of one order of magnitude. Here, we show that lateral dSTORM resolution is sufficient to resolve the dense organization of the IF networks and, in particular, of IF bundles surrounding microtubules. Such tight association is likely to participate in the coordinated regulation of these two networks and may, explain how vimentin IFs template and stabilize microtubule organization as well as could influence microtubule dependent vesicular trafficking. More generally, we show how the observation of two cytoskeletal components with dual-color dSTORM technique brings new insight into their mutual interaction.