Conformational states of the kinase Lck regulate clustering in early T cell signaling

Kovács BB, Novák T, Erdélyi M. Cluster parameter-based DBSCAN maps for image characterization

Single-molecule localization microscopy techniques are one of the most powerful methods in biological studies, allowing the visualization of nanoclusters. Cluster analysis algorithms are used for quantitative evaluation, with DBSCAN being one of the most widely used. Clustering results are extremely sensitive to the initial parameters; thus, several methods including DBSCAN maps, have been developed for parameter optimization. Here, we introduce cluster parameter-based DBSCAN maps, which are directly applicable to measured datasets. These maps can be used for image characterization and parameter optimization through sensitivity studies. We show the applicability of these maps to simulated and measured datasets and compare our results with the recently implemented lacunarity analysis for SMLM measurements.

Isobavachin attenuates FcεRI-mediated inflammatory allergic responses by regulating SHP-1-dependent Fyn/Lyn/Syk/Lck signaling

Isobavachin, isolated from Psoralea corylifolia L. exhibits therapeutic potential for osteoporosis or skin disease. Here, we evaluated the pharmacological effects of isobavachin on IgE-dependent inflammatory allergic reactions, as well as the underlying mechanisms, in bone marrow-derived mast cells and a mouse model of passive cutaneous anaphylaxis (PCA). Isobavachin reduced IgE/Ag-stimulated degranulation, eicosanoid (leukotriene C4 and prostaglandin D2) generation, and release of pro-inflammatory cytokines (tumor necrosis factor-α (TNF-α) and interleukin (IL)-6). Mechanistic studies revealed that isobavachin suppressed activation of Fyn, Lyn, spleen tyrosine kinase (Syk), and lymphocyte-specific-protein-kinase (Lck), receptor-proximal tyrosine kinases that initiate and play a central role in FcɛRI-mediated mast cell activation, as well as their common downstream signaling molecules including linker for activation of T cells, phospholipase Cγ1, AKT, mitogen-activated protein kinases (MAPKs), and intracellular Ca2+. Additionally, isobavachin increased phosphorylation of Src homology region 2 domain-containing phosphatase-1 (SHP-1), thereby strengthening its interaction with Syk and Lck as well as Fyn and Lyn, resulting in de-phosphorylation of these proximal tyrosine kinases. Genetic knockdown of SHP-1 reversed the inhibitory effects of isobavachin on mast cell activation, as well as the related signaling pathways, indicating that the inhibitory effects of isobavachin are mediated by negative regulation of SHP-1-dependent Fyn, Lyn, Syk and Lck. The anti-inflammatory properties of isobavachin were also examined in macrophages. Isobavachin suppressed production of lipopolysaccharide-stimulated production of pro-inflammatory cytokines and nitric oxide. Furthermore, oral administration of isobavachin attenuated mast cell-mediated PCA reactions in mice. These results suggest that isobavachin is a potential treatment for mast cell-mediated allergic inflammatory diseases.

Mechanoimmunology of T-Cell Activation

T-cell activation, a pivotal process in the adaptive immune response, is initiated when the T cell receptor (TCR) recognises and binds to antigenic peptide-major histocompatibility complex (pMHC) molecules on the cell membrane. Emerging evidence indicates that mechanical cues regulate T-cell activation by modulating TCR signalling and mechanotransduction pathways, although the precise underlying mechanisms remain elusive. This review highlights recent findings suggesting that the TCR functions as a mechanosensor, capable of sensing and transmitting mechanical forces through conformational changes. Key steps in T-cell mechanotransduction are discussed, including the roles of the cytoskeleton, mechanosensitive channels such as Piezo 1 and microvilli in facilitating activation. Additionally, we analyse the mechanical responses of chimeric antigen receptor T cells. Understanding the mechanobiological mechanisms underlying T-cell activation offers novel insights and potential strategies for advancing immunotherapies and treating immune-related disorders.

Trafficking in cancer: from gene deregulation to altered organelles and emerging biophysical properties

Intracellular trafficking supports all cell functions maintaining the exchange of material between membrane-bound organelles and the plasma membrane during endocytosis, cargo sorting, and exocytosis/secretion. Several proteins of the intracellular trafficking machinery are deregulated in diseases, particularly cancer. This complex and deadly disease stays a heavy burden for society, despite years of intense research activity. Here, we give an overview about trafficking proteins and highlight that in addition to their molecular functions, they contribute to the emergence of intracellular organelle landscapes. We review recent evidence of organelle landscape alterations in cancer. We argue that focusing on organelles, which represent the higher-order, cumulative behavior of trafficking regulators, could help to better understand, describe and fight cancer. In particular, we propose adopting a physical framework to describe the organelle landscape, with the goal of identifying the key parameters that are crucial for a stable and non-random organelle organization characteristic of healthy cells. By understanding these parameters, we may gain insights into the mechanisms that lead to a pathological organelle spatial organization, which could help explain the plasticity of cancer cells.

Recent Advancements in Imaging Techniques for Individual Extracellular Vesicles

Extracellular vesicles (EVs), secreted from most cells, are small lipid membranes of vesicles of 30 to 1000 nm in diameter and contain nucleic acids, proteins, and intracellular organelles originating from donor cells. EVs play pivotal roles in intercellular communication, particularly in forming niches for cancer cell metastasis. However, EVs derived from donor cells exhibit significant heterogeneity, complicating the investigation of EV subtypes using ensemble averaging methods. In this context, we highlight recent studies that characterize individual EVs using advanced techniques, including single-fluorescent-particle tracking, single-metal-nanoparticle tracking, single-non-label-particle tracking, super-resolution microscopy, and atomic force microscopy. These techniques have facilitated high-throughput analyses of the properties of individual EV particles such as their sizes, compositions, and physical properties. Finally, we address the challenges that need to be resolved via single-particle (-molecule) imaging and super-resolution microscopy in future research.

Key links in the physiological regulation of the immune system and disease induction: T cell receptor -CD3 complex

T cell receptor (TCR) is a kind of surface marker that are specific to T cells. The TCR regulates T cell function and participates in the body's immunological response to prevent immune dysregulation and inflammatory reactions by identifying and binding exogenous antigens. Due to its brief intracellular segment, TCR requires intracellular molecules to assist with signaling. Among these, the CD3 molecule is one of the most important. The CD3 molecule involves in TCR structural stability as well as T cell activation signaling. A TCR-CD3 complex is created when TCR and CD3 form a non-covalent bond. Antigen recognition and T cell signaling are both facilitated by the TCR-CD3 complex. When a CD3 subunit is absent, a TCR-CD3 complex cannot form, and none of the subunits is transported to the cell surface. Thus, T cells cannot develop. Consequently, research on the physiological functions and potential pathogenicity of CD3 subunits can clarify the pathogenesis of immune system diseases and can offer fresh approaches to the treatment of it. In this review, the structure and function of the TCR-CD3 complex in the immune system was summarized, the pathogenicity of each CD3 subunit and therapeutic approaches to related diseases was explored and research directions for the development of new targeted drugs was provided.

Dysregulation of cellular membrane homeostasis as a crucial modulator of cancer risk

Cellular membranes serve as an epicentre combining extracellular and cytosolic components with membranous effectors, which together support numerous fundamental cellular signalling pathways that mediate biological responses. To execute their functions, membrane proteins, lipids and carbohydrates arrange, in a highly coordinated manner, into well-defined assemblies displaying diverse biological and biophysical characteristics that modulate several signalling events. The loss of membrane homeostasis can trigger oncogenic signalling. More recently, it has been documented that select membrane active dietaries (MADs) can reshape biological membranes and subsequently decrease cancer risk. In this review, we emphasize the significance of membrane domain structure, organization and their signalling functionalities as well as how loss of membrane homeostasis can steer aberrant signalling. Moreover, we describe in detail the complexities associated with the examination of these membrane domains and their association with cancer. Finally, we summarize the current literature on MADs and their effects on cellular membranes, including various mechanisms of dietary chemoprevention/interception and the functional links between nutritional bioactives, membrane homeostasis and cancer biology.

A combined biochemical and cellular approach reveals Zn2+-dependent hetero- and homodimeric CD4 and Lck assemblies in T cells

The CD4 or CD8 co-receptors' interaction with the protein-tyrosine kinase Lck initiates the tyrosine phosphorylation cascade leading to T cell activation. A critical question is: to what extent are co-receptors and Lck coupled? Our contribution concerns Zn2+, indispensable for CD4- and CD8-Lck formation. We combined biochemical and cellular approaches to show that dynamic fluctuations of free Zn2+ in physiological ranges influence Zn(CD4)2 and Zn(CD4)(Lck) species formation and their ratio, although the same Zn(Cys)2(Cys)2 cores. Moreover, we demonstrated that the affinity of Zn2+ to CD4 and CD4-Lck species differs significantly. Increased intracellular free Zn2+ concentration in T cells causes higher CD4 partitioning in the plasma membrane. We additionally found that CD4 palmitoylation decreases the specificity of CD4-Lck formation in the reconstituted membrane model. Our findings help elucidate co-receptor-Lck coupling stoichiometry and demonstrate that intracellular free Zn2+ has a major role in the interplay between CD4 dimers and CD4-Lck assembly.

Nanoscale CAR Organization at the Immune Synapse Correlates with CAR-T Effector Functions

T cells expressing chimeric antigen receptors (CARs) are at the forefront of clinical treatment of cancers. Still, the nanoscale organization of CARs at the interface of CAR-Ts with target cells, which is essential for TCR-mediated T cell activation, remains poorly understood. Here, we studied the nanoscale organization of CARs targeting CD138 proteoglycans in such fixed and live interfaces, generated optimally for single-molecule localization microscopy. CARs showed significant self-association in nanoclusters that was enhanced in interfaces with on-target cells (SKOV-3, CAG, FaDu) relative to negative cells (OVCAR-3). CARs also segregated more efficiently from the abundant membrane phosphatase CD45 in CAR-T cells forming such interfaces. CAR clustering and segregation from CD45 correlated with the effector functions of Ca++ influx and target cell killing. Our results shed new light on the nanoscale organization of CARs on the surfaces of CAR-Ts engaging on- and off-target cells, and its potential significance for CAR-Ts' efficacy and safety.

A framework for evaluating the performance of SMLM cluster analysis algorithms

Single-molecule localization microscopy (SMLM) generates data in the form of coordinates of localized fluorophores. Cluster analysis is an attractive route for extracting biologically meaningful information from such data and has been widely applied. Despite a range of cluster analysis algorithms, there exists no consensus framework for the evaluation of their performance. Here, we use a systematic approach based on two metrics to score the success of clustering algorithms in simulated conditions mimicking experimental data. We demonstrate the framework using seven diverse analysis algorithms: DBSCAN, ToMATo, KDE, FOCAL, CAML, ClusterViSu and SR-Tesseler. Given that the best performer depended on the underlying distribution of localizations, we demonstrate an analysis pipeline based on statistical similarity measures that enables the selection of the most appropriate algorithm, and the optimized analysis parameters for real SMLM data. We propose that these standard simulated conditions, metrics and analysis pipeline become the basis for future analysis algorithm development and evaluation.

Recent development of computational cluster analysis methods for single-molecule localization microscopy images

With the development of super-resolution imaging techniques, it is crucial to understand protein structure at the nanoscale in terms of clustering and organization in a cell. However, cluster analysis from single-molecule localization microscopy (SMLM) images remains challenging because the classical computational cluster analysis methods developed for conventional microscopy images do not apply to pointillism SMLM data, necessitating the development of distinct methods for cluster analysis from SMLM images. In this review, we discuss the development of computational cluster analysis methods for SMLM images by categorizing them into classical and machine-learning-based methods. Finally, we address possible future directions for machine learning-based cluster analysis methods for SMLM data.

Measuring the Co-Localization and Dynamics of Mobile Proteins in Live Cells Undergoing Signaling Responses

Single molecule imaging in live cells enables the study of protein interactions and dynamics as they participate in signaling processes. When combined with fluorophores that stochastically transition between fluorescent and reversible dark states, as in super-resolution localization imaging, labeled molecules can be visualized in single cells over time. This improvement in sampling enables the study of extended cellular responses at the resolution of single molecule localization. This chapter provides optimized experimental and analytical methods used to quantify protein interactions and dynamics within the membranes of adhered live cells. Importantly, the use of pair-correlation functions resolved in both space and time allows researchers to probe interactions between proteins on biologically relevant distance and timescales, even though fluorescence localization methods typically require long times to assemble well-sampled reconstructed images. We describe an application of this approach to measure protein interactions in B cell receptor signaling and include sample analysis code for post-processing of imaging data. These methods are quantitative, sensitive, and broadly applicable to a range of signaling systems.

Rafting on the Plasma Membrane: Lipid Rafts in Signaling and Disease

The plasma membrane is not a uniform phospholipid bilayer; it has specialized membrane nano- or microdomains called lipid rafts. Lipid rafts are small cholesterol and sphingolipid-rich plasma membrane islands. Although their existence was long debated, their presence in the plasma membrane of living cells is now well accepted with the advent of super-resolution imaging techniques. It is interesting to note that lipid rafts function to compartmentalize receptors and their regulators and substantially modulate cellular signaling. In this review, we will examine the role of lipid rafts and caveolae-lipid raft-like microdomains with a distinct 3D morphology-in cellular signaling. Moreover, we will investigate how raft compartmentalized signaling regulates diverse physiological processes such as proliferation, apoptosis, immune signaling, and development. Also, the deregulation of lipid raft-mediated signaling during tumorigenesis and metastasis will be explored.

Molecular dynamics simulations reveal membrane lipid interactions of the full-length lymphocyte specific kinase (Lck)

The membrane-bound lymphocyte-specific protein-tyrosine kinase (Lck) triggers T cell antigen receptor signalling to initiate adaptive immune responses. Despite many structure-function studies, the mode of action of Lck and the potential role of plasma membrane lipids in regulating Lck's activity remains elusive. Advances in molecular dynamics simulations of membrane proteins in complex lipid bilayers have opened a new perspective in gathering such information. Here, we have modelled the full-length Lck open and closed conformations  using data available from different crystalographic studies and simulated its interaction with the inner leaflet of the T cell plasma membrane. In both conformations, we found that the unstructured unique domain and the structured domains including the kinase interacted with the membrane with a preference for PIP lipids. Interestingly, our simulations suggest that the Lck-SH2 domain interacts with lipids differently in the open and closed Lck conformations, demonstrating that lipid interaction can potentially regulate Lck's conformation and in turn modulate T cell signalling. Additionally, the Lck-SH2 and kinase domain residues that significantly contacted PIP lipids are found to be conserved among the Src family of kinases, thereby potentially representing similar PIP interactions within the family.

A short hepatitis C virus NS5A peptide expression by AAV vector modulates human T cell activation and reduces vector immunogenicity

Viral vector-mediated gene therapies have the potential to treat many human diseases; however, host immune responses against the vector and/or the transgene pose a safety risk to the patients and can negatively impact product efficacy. Thus, novel strategies to reduce vector immunogenicity are critical for the advancement of these therapies. T cell activation (TCA) is required for the development of immune responses during gene therapy. We hypothesized that modulation of TCA by incorporating a novel viral immunomodulatory factor into a viral vector may reduce unwanted TCA and immune responses during gene therapy. To test this hypothesis, we identified an immunomodulatory domain of the hepatitis C virus (HCV) NS protein 5A (NS5A) protein and studied the effect of viral vectors expressing NS5A peptide on TCA. Lentiviral vector-mediated expression of a short 20-mer peptide derived from the NS5A protein in human T cells was sufficient to inhibit TCA. Synthetic 20-mer NS5A peptide also inhibited TCA in primary human T cells. Mechanistically, the NS5A protein interacted with Lck and inhibited proximal TCR signaling. Importantly, NS5A peptide expression did not cause global T cell signaling dysfunction as distal T cell signaling was not inhibited. Finally, recombinant adeno-associated virus (AAV) vector expressing the 20-mer NS5A peptide reduced both the recall antigen and the TCR-mediated activation of human T cells and did not cause global T cell signaling dysfunction. Together, these data suggest that expression of a 20-mer NS5A peptide by an AAV vector may reduce unwanted TCA and may contribute to lower vector immunogenicity during gene therapy.

Tetraspanin-5-mediated MHC class I clustering is required for optimal CD8 T cell activation

MHC molecules are not randomly distributed on the plasma membrane but instead are present in discrete nanoclusters. The mechanisms that control formation of MHC I nanoclusters and the importance of such structures are incompletely understood. Here, we report a molecular association between tetraspanin-5 (Tspan5) and MHC I molecules that started in the endoplasmic reticulum and was maintained on the plasma membrane. This association was observed both in mouse dendritic cells and in human cancer cell lines. Loss of Tspan5 reduced the size of MHC I clusters without affecting MHC I peptide loading, delivery of complexes to the plasma membrane, or overall surface MHC I levels. Functionally, CD8 T cell responses to antigen presented by Tspan5-deficient dendritic cells were impaired but were restored by antibody-induced reclustering of MHC I molecules. In contrast, Tspan5 did not associate with two other plasma membrane proteins, Flotillin1 and CD55, with or the endoplasmic reticulum proteins Tapasin and TAP. Thus, our findings identify a mechanism underlying the clustering of MHC I molecules that is important for optimal T cell responses.

Mass spectrometry and the cellular surfaceome

The collection of exposed plasma membrane proteins, collectively termed the surfaceome, is involved in multiple vital cellular processes, such as the communication of cells with their surroundings and the regulation of transport across the lipid bilayer. The surfaceome also plays key roles in the immune system by recognizing and presenting antigens, with its possible malfunctioning linked to disease. Surface proteins have long been explored as potential cell markers, disease biomarkers, and therapeutic drug targets. Despite its importance, a detailed study of the surfaceome continues to pose major challenges for mass spectrometry-driven proteomics due to the inherent biophysical characteristics of surface proteins. Their inefficient extraction from hydrophobic membranes to an aqueous medium and their lower abundance compared to intracellular proteins hamper the analysis of surface proteins, which are therefore usually underrepresented in proteomic datasets. To tackle such problems, several innovative analytical methodologies have been developed. This review aims at providing an extensive overview of the different methods for surfaceome analysis, with respective considerations for downstream mass spectrometry-based proteomics.

Correction of multiple-blinking artifacts in photoactivated localization microscopy

Photoactivated localization microscopy (PALM) produces an array of localization coordinates by means of photoactivatable fluorescent proteins. However, observations are subject to fluorophore multiple blinking and each protein is included in the dataset an unknown number of times at different positions, due to localization error. This causes artificial clustering to be observed in the data. We present a 'model-based correction' (MBC) workflow using calibration-free estimation of blinking dynamics and model-based clustering to produce a corrected set of localization coordinates representing the true underlying fluorophore locations with enhanced localization precision, outperforming the state of the art. The corrected data can be reliably tested for spatial randomness or analyzed by other clustering approaches, and descriptors such as the absolute number of fluorophores per cluster are now quantifiable, which we validate with simulated data and experimental data with known ground truth. Using MBC, we confirm that the adapter protein, the linker for activation of T cells, is clustered at the T cell immunological synapse.

Approach to map nanotopography of cell surface receptors

Cells communicate with their environment via surface receptors, but nanoscopic receptor organization with respect to complex cell surface morphology remains unclear. This is mainly due to a lack of accessible, robust and high-resolution methods. Here, we present an approach for mapping the topography of receptors at the cell surface with nanometer precision. The method involves coating glass coverslips with glycine, which preserves the fine membrane morphology while allowing immobilized cells to be positioned close to the optical surface. We developed an advanced and simplified algorithm for the analysis of single-molecule localization data acquired in a biplane detection scheme. These advancements enable direct and quantitative mapping of protein distribution on ruffled plasma membranes with near isotropic 3D nanometer resolution. As demonstrated successfully for CD4 and CD45 receptors, the described workflow is a straightforward quantitative technique to study molecules and their interactions at the complex surface nanomorphology of differentiated metazoan cells.

A super-resolution localisation-based method is shown to map receptor topography in immune cells, which allows quantitative study of molecules and their interactions at the complex surface nanomorphology of cells.

Don’t Be Fooled by Randomness: Valid p-Values for Single Molecule Microscopy

The human mind shows extraordinary capability at recognizing patterns, while at the same time tending to underestimate the natural scope of random processes. Taken together, this easily misleads researchers in judging whether the observed characteristics of their data are of significance or just the outcome of random effects. One of the best tools to assess whether observed features fall into the scope of pure randomness is statistical significance testing, which quantifies the probability to falsely reject a chosen null hypothesis. The central parameter in this context is the p-value, which can be calculated from the recorded data sets. In case of p-values smaller than the level of significance, the null hypothesis is rejected, otherwise not. While significance testing has found widespread application in many sciences including the life sciences, it is hardly used in (bio-)physics. We propose here that significance testing provides an important and valid addendum to the toolbox of quantitative (single molecule) biology. It allows to support a quantitative judgement (the hypothesis) about the data set with a probabilistic assessment. In this manuscript we describe ways for obtaining valid p-values in two selected applications of single molecule microscopy: (i) Nanoclustering in single molecule localization microscopy. Previously, we developed a method termed 2-CLASTA, which allows to calculate a valid p-value for the null hypothesis of an underlying random distribution of molecules of interest while circumventing overcounting issues. Here, we present an extension to this approach, yielding a single overall p-value for data pooled from multiple cells or experiments. (ii) Single molecule trajectories. Data from a single molecule trajectory are inherently correlated, thus prohibiting a direct analysis via conventional statistical tools. Here, we introduce a block permutation test, which yields a valid p-value for the analysis and comparison of single molecule trajectory data. We exemplify the approach based on FRET trajectories.

Identification of Biomarkers Related to Regulatory T Cell Infiltration in Oral Squamous Cell Carcinoma Based on Integrated Bioinformatics Analysis

Background

Oral squamous cell carcinoma (OSCC) is one of the most prevalent malignancies worldwide. More recently, the administration of immune checkpoint inhibitors has opened up more possibilities for cancer treatment.

Methods

We utilized a weighted gene co-expression network and the single sample gene set enrichment analysis (ssGSEA) algorithm in the TCGA database and identified a module highly correlated with regulatory T cell (Treg) abundance in OSCC. Subsequently, we verified the results by tissue microarrays and utilized immunohistochemical staining (IHC) to test the relationship between the expression level and clinicopathological staging. CCK-8, transwell, and wound healing assays were utilized to detect the functions of OSCC cells.

Results

LCK, IL10RA, and TNFRSF1B were selected as biomarkers related to regulatory T cell infiltration. IHC staining showed significantly increased expression of LCK, IL10RA or TNFRSF1B in OSCC patients, and the expression levels were associated with tumor stage, lymph node metastasis, pathological stage, clinical status and the overall survival. In vitro experiments showed that LCK, IL10RA or TNFRSF1B knockdown efficiently impaired the proliferative, migrative, and invasive capacity in OSCC cell lines.

Conclusion

We performed a series of bioinformatics analyses in OSCC and identified three oncogenic indicators: LCK, IL10RA, TNFRSF1B. These findings uncovered the potential prognostic values of hub genes, thus laying foundations for in-depth research in OSCC.

Raw Data to Results: A Hands-On Introduction and Overview of Computational Analysis for Single-Molecule Localization Microscopy

Single-molecule localization microscopy (SMLM) is an advanced microscopy method that uses the blinking of fluorescent molecules to determine the position of these molecules with a resolution below the diffraction limit (∼5-40 nm). While SMLM imaging itself is becoming more popular, the computational analysis surrounding the technique is still a specialized area and often remains a "black box" for experimental researchers. Here, we provide an introduction to the required computational analysis of SMLM imaging, post-processing and typical data analysis. Importantly, user-friendly, ready-to-use and well-documented code in Python and MATLAB with exemplary data is provided as an interactive experience for the reader, as well as a starting point for further analysis. Our code is supplemented by descriptions of the computational problems and their implementation. We discuss the state of the art in computational methods and software suites used in SMLM imaging and data analysis. Finally, we give an outlook into further computational challenges in the field.

Technological advances in super-resolution microscopy to study cellular processes

Since its initial demonstration in 2000, far-field super-resolution light microscopy has undergone tremendous technological developments. In parallel, these developments have opened a new window into visualizing the inner life of cells at unprecedented levels of detail. Here, we review the technical details behind the most common implementations of super-resolution microscopy and highlight some of the recent, promising advances in this field.

Metrics of 2D immunological synapses in human T cells via high-content confocal cell imaging

Immunological synapses (IS) are the privileged site of complex information transfer between T cells and antigen presenting cells. IS are highly structured in terms of actin and tubulin cytoskeleton organization, receptor and proximal signal patterning, and intracellular organelle polarization. The magnitude and quality of T cell responses upon antigen recognition is dependent on IS molecular organization. For that reason, methods to precisely assess IS parameters are crucial to monitor T cell activation and function in health and disease, but also for T cell centered therapeutic intervention. Confocal and super-resolution microscopy approaches have allowed to characterize the complex structure of the T cell IS. However, those approaches suffer from a low-throughput and low-content format precluding multi-parametric classification of IS across large numbers of samples or stimulatory conditions. Here, we present a protocol of high-content confocal cell imaging in a 384-well plate format adapted to the unbiased analysis of primary T cells forming IS over pre-coated stimulatory molecules. The protocol focuses on the staining of F-actin, pericentrin and granzyme B in CD8⁺ T cells, but is transposable to other IS molecular markers and lymphocyte subsets. We discuss potential applications offered by the multi-parametric characterization of T cell IS in a high-throughput format.

Shedding Structured Light on Molecular Immunity: The Past, Present and Future of Immune Cell Super Resolution Microscopy

In the two decades since the invention of laser-based super resolution microscopy this family of technologies has revolutionised the way life is viewed and understood. Its unparalleled resolution, speed, and accessibility makes super resolution imaging particularly useful in examining the highly complex and dynamic immune system. Here we introduce the super resolution technologies and studies that have already fundamentally changed our understanding of a number of central immunological processes and highlight other immunological puzzles only addressable in super resolution.

Infant T cells are developmentally adapted for robust lung immune responses through enhanced T cell receptor signaling

Infants require coordinated immune responses to prevent succumbing to multiple infectious challenges during early life, particularly in the respiratory tract. The mechanisms by which infant T cells are functionally adapted for these responses are not well understood. Here, we demonstrated using an in vivo mouse cotransfer model that infant T cells generated greater numbers of lung-homing effector cells in response to influenza infection compared with adult T cells in the same host, due to augmented T cell receptor (TCR)–mediated signaling. Mouse infant T cells showed increased sensitivity to low antigen doses, originating at the interface between T cells and antigen-bearing accessory cells—through actin-mediated mobilization of signaling molecules to the immune synapse. This enhanced signaling was also observed in human infant versus adult T cells. Our findings provide a mechanism for how infants control pathogen load and dissemination, which is important for designing developmentally targeted strategies for promoting immune responses at this vulnerable life stage.

Three-Dimensional Single Molecule Localization Microscopy Reveals the Topography of the Immunological Synapse at Isotropic Precision below 15 nm

T-cells engage with antigen-presenting cells in search for antigenic peptides and form transient interfaces termed immunological synapses. Synapse topography affects receptor binding rates and the mutual segregation of proteins due to size exclusion effects. It is hence important to determine the 3D topography of the immunological synapse at high precision. Current methods provide only rather coarse images of the protein distribution within the synapse. Here, we applied supercritical angle fluorescence microscopy combined with defocused imaging, which allows three-dimensional single molecule localization microscopy (3D-SMLM) at an isotropic localization precision below 15 nm. Experiments were performed on hybrid synapses between primary T-cells and functionalized glass-supported lipid bilayers. We used 3D-SMLM to quantify the cleft size within the synapse by mapping the position of the T-cell receptor (TCR) with respect to the supported lipid bilayer, yielding average distances of 18 nm up to 31 nm for activating and nonactivating bilayers, respectively.

Biosensors based on peptide exposure show single molecule conformations in live cells

We describe an approach to study the conformation of individual proteins during single particle tracking (SPT) in living cells. "Binder/tag" is based on incorporation of a 7-mer peptide (the tag) into a protein where its solvent exposure is controlled by protein conformation. Only upon exposure can the peptide specifically interact with a reporter protein (the binder). Thus, simple fluorescence localization reflects protein conformation. Through direct excitation of bright dyes, the trajectory and conformation of individual proteins can be followed. Simple protein engineering provides highly specific biosensors suitable for SPT and FRET. We describe tagSrc, tagFyn, tagSyk, tagFAK, and an orthogonal binder/tag pair. SPT showed slowly diffusing islands of activated Src within Src clusters and dynamics of activation in adhesions. Quantitative analysis and stochastic modeling revealed in vivo Src kinetics. The simplicity of binder/tag can provide access to diverse proteins.

Aggregation and mobility of membrane proteins interplay with local lipid order in the plasma membrane of T cells

To disentangle the elusive lipid-protein interactions in T-cell activation, we investigate how externally imposed variations in mobility of key membrane proteins (T-cell receptor [TCR], kinase Lck, and phosphatase CD45) affect the local lipid order and protein colocalisation. Using spectral imaging with polarity-sensitive membrane probes in model membranes and live Jurkat T cells, we find that partial immobilisation of proteins (including TCR) by aggregation or ligand binding changes their preference towards a more ordered lipid environment, which can recruit Lck. Our data suggest that the cellular membrane is poised to modulate the frequency of protein encounters upon alterations of their mobility, for example in ligand binding, which offers new mechanistic insight into the involvement of lipid-mediated interactions in membrane-hosted signalling events.

Rapid statistical discrimination of fluorescence images of T cell receptors on immobilizing surfaces with different coating conditions

The spatial organization of T cell receptors (TCRs) correlates with membrane-associated signal amplification, dispersion, and regulation during T cell activation. Despite its potential clinical importance, quantitative analysis of the spatial arrangement of TCRs from standard fluorescence images remains difficult. Here, we report Statistical Classification Analyses of Membrane Protein Images or SCAMPI as a technique capable of analyzing the spatial arrangement of TCRs on the plasma membrane of T cells. We leveraged medical image analysis techniques that utilize pixel-based values. We transformed grayscale pixel values from fluorescence images of TCRs into estimated model parameters of partial differential equations. The estimated model parameters enabled an accurate classification using linear discrimination techniques, including Fisher Linear Discriminant (FLD) and Logistic Regression (LR). In a proof-of-principle study, we modeled and discriminated images of fluorescently tagged TCRs from Jurkat T cells on uncoated cover glass surfaces (Null) or coated cover glass surfaces with either positively charged poly-L-lysine (PLL) or TCR cross-linking anti-CD3 antibodies (OKT3). Using 80 training images and 20 test images per class, our statistical technique achieved 85% discrimination accuracy for both OKT3 versus PLL and OKT3 versus Null conditions. The run time of image data download, model construction, and image discrimination was 21.89 s on a laptop computer, comprised of 20.43 s for image data download, 1.30 s on the FLD-SCAMPI analysis, and 0.16 s on the LR-SCAMPI analysis. SCAMPI represents an alternative approach to morphology-based qualifications for discriminating complex patterns of membrane proteins conditioned on a small sample size and fast runtime. The technique paves pathways to characterize various physiological and pathological conditions using the spatial organization of TCRs from patient T cells.

Multi-dimensional and spatiotemporal correlative imaging at the plasma membrane of live cells to determine the continuum nano-to-micro scale lipid adaptation and collective motion

The primary cilium is a specialized plasma membrane protrusion with important receptors for signalling pathways. In polarized epithelial cells, the primary cilium assembles after the midbody remnant (MBR) encounters the centrosome at the apical surface. The membrane surrounding the MBR, namely remnant-associated membrane patch (RAMP), once situated next to the centrosome, releases some of its lipid components to form a centrosome-associated membrane patch (CAMP) from which the ciliary membrane stems. The RAMP undergoes a spatiotemporal membrane refinement during the formation of the CAMP, which becomes highly enriched in condensed membranes with low lateral mobility. To better understand this process, we have developed a correlative imaging approach that yields quantitative information about the lipid lateral packing, its mobility and collective assembly at the plasma membrane at different spatial scales over time. Our work paves the way towards a quantitative understanding of the spatiotemporal lipid collective assembly at the plasma membrane as a functional determinant in cell biology and its direct correlation with the membrane physicochemical state. These findings allowed us to gain a deeper insight into the mechanisms behind the biogenesis of the ciliary membrane of polarized epithelial cells.

A pairwise distance distribution correction (DDC) algorithm to eliminate blinking-caused artifacts in SMLM

Single-molecule localization microscopy (SMLM) relies on the blinking behavior of a fluorophore, which is the stochastic switching between fluorescent and dark states. Blinking creates multiple localizations belonging to the same fluorophore, confounding quantitative analyses and interpretations. Here we present a method, termed distance distribution correction (DDC), to eliminate blinking-caused repeat localizations without any additional calibrations. The approach relies on obtaining the true pairwise distance distribution of different fluorophores naturally from the imaging sequence by using distances between localizations separated by a time much longer than the average fluorescence survival time. We show that, using the true pairwise distribution, we can define and maximize the likelihood, obtaining a set of localizations void of blinking artifacts. DDC results in drastic improvements in obtaining the closest estimate of the true spatial organization and number of fluorescent emitters in a wide range of applications, enabling accurate reconstruction and quantification of SMLM images.

PD-1 suppresses TCR-CD8 cooperativity during T-cell antigen recognition

Despite the clinical success of blocking its interactions, how PD-1 inhibits T-cell activation is incompletely understood, as exemplified by its potency far exceeding what might be predicted from its affinity for PD-1 ligand-1 (PD-L1). This may be partially attributed to PD-1's targeting the proximal signaling of the T-cell receptor (TCR) and co-stimulatory receptor CD28 via activating Src homology region 2 domain-containing phosphatases (SHPs). Here, we report PD-1 signaling regulates the initial TCR antigen recognition manifested in a smaller spreading area, fewer molecular bonds formed, and shorter bond lifetime of T cell interaction with peptide-major histocompatibility complex (pMHC) in the presence than absence of PD-L1 in a manner dependent on SHPs and Leukocyte C-terminal Src kinase. Our results identify a PD-1 inhibitory mechanism that disrupts the cooperative TCR-pMHC-CD8 trimolecular interaction, which prevents CD8 from augmenting antigen recognition, explaining PD-1's potent inhibitory function and its value as a target for clinical intervention.

ERM-Dependent Assembly of T Cell Receptor Signaling and Co-stimulatory Molecules on Microvilli prior to Activation

T cell surfaces are covered with microvilli, actin-rich and flexible protrusions. We use super-resolution microscopy to show that ≥90% of T cell receptor (TCR) complex molecules TCRαβ and TCRζ, as well as the co-receptor CD4 (cluster of differentiation 4) and the co-stimulatory molecule CD2, reside on microvilli of resting human T cells. Furthermore, TCR proximal signaling molecules involved in the initial stages of the immune response, including the protein tyrosine kinase Lck (lymphocyte-specific protein tyrosine kinase) and the key adaptor LAT (linker for activation of T cells), are also enriched on microvilli. Notably, phosphorylated proteins of the ERM (ezrin, radixin, and moesin) family colocalize with TCRαβ as well as with actin filaments, implying a role for one or more ERMs in linking the TCR complex to the actin cytoskeleton within microvilli. Our results establish microvilli as key signaling hubs, in which the TCR complex and its proximal signaling molecules and adaptors are preassembled prior to activation in an ERM-dependent manner, facilitating initial antigen sensing.

The Role of Protein and Lipid Clustering in Lymphocyte Activation

Lymphocytes must strike a delicate balance between activating in response to signals from potentially pathogenic organisms and avoiding activation from stimuli emanating from the body's own cells. For cells, such as T or B cells, maximizing the efficiency and fidelity, whilst minimizing the crosstalk, of complex signaling pathways is crucial. One way of achieving this control is by carefully orchestrating the spatiotemporal organization of signaling molecules, thereby regulating the rates of protein-protein interactions. This is particularly true at the plasma membrane where proximal signaling events take place and the phenomenon of protein microclustering has been extensively observed and characterized. This review will focus on what is known about the heterogeneous distribution of proteins and lipids at the cell surface, illustrating how such distributions can influence signaling in health and disease. We particularly focus on nanoscale molecular organization, which has recently become accessible for study through advances in microscope technology and analysis methodology.

Microclusters as T Cell Signaling Hubs: Structure, Kinetics, and Regulation

When T cell receptors (TCRs) engage with stimulatory ligands, one of the first microscopically visible events is the formation of microclusters at the site of T cell activation. Since the discovery of these structures almost 20 years ago, they have been studied extensively in live cells using confocal and total internal reflection fluorescence (TIRF) microscopy. However, due to limits in image resolution and acquisition speed, the spatial relationships of signaling components within microclusters, the kinetics of their assembly and disassembly, and the role of vesicular trafficking in microcluster formation and maintenance were not finely characterized. In this review, we will summarize how new microscopy techniques have revealed novel insights into the assembly of these structures. The sub-diffraction organization of microclusters as well as the finely dissected kinetics of recruitment and disassociation of molecules from microclusters will be discussed. The role of cell surface molecules in microcluster formation and the kinetics of molecular recruitment via intracellular vesicular trafficking to microclusters is described. Finally, the role of post-translational modifications such as ubiquitination in the downregulation of cell surface signaling molecules is also discussed. These results will be related to the role of these structures and processes in T cell activation.

Control of SRC molecular dynamics encodes distinct cytoskeletal responses by specifying signaling pathway usage

Upon activation by different transmembrane receptors, the same signaling protein can induce distinct cellular responses. A way to decipher the mechanisms of such pleiotropic signaling activity is to directly manipulate the decision-making activity that supports the selection between distinct cellular responses. We developed an optogenetic probe (optoSRC) to control SRC signaling, an example of a pleiotropic signaling node, and we demonstrated its ability to generate different acto-adhesive structures (lamellipodia or invadosomes) upon distinct spatio-temporal control of SRC kinase activity. The occurrence of each acto-adhesive structure was simply dictated by the dynamics of optoSRC nanoclusters in adhesive sites, which were dependent on the SH3 and Unique domains of the protein. The different decision-making events regulated by optoSRC dynamics induced distinct downstream signaling pathways, which we characterized using time-resolved proteomic and network analyses. Collectively, by manipulating the molecular mobility of SRC kinase activity, these experiments reveal the pleiotropy-encoding mechanism of SRC signaling.

Multi-color Molecular Visualization of Signaling Proteins Reveals How C-Terminal Src Kinase Nanoclusters Regulate T Cell Receptor Activation

Elucidating the mechanisms that controlled T cell activation requires visualization of the spatial organization of multiple proteins on the submicron scale. Here, we use stoichiometrically accurate, multiplexed, single-molecule super-resolution microscopy (DNA-PAINT) to image the nanoscale spatial architecture of the primary inhibitor of the T cell signaling pathway, Csk, and two binding partners implicated in its membrane association, PAG and TRAF3. Combined with a newly developed co-clustering analysis framework, we find that Csk forms nanoscale clusters proximal to the plasma membrane that are lost post-stimulation and are re-recruited at later time points. Unexpectedly, these clusters do not co-localize with PAG at the membrane but instead provide a ready pool of monomers to downregulate signaling. By generating CRISPR-Cas9 knockout T cells, our data also identify that a major risk factor for autoimmune diseases, the protein tyrosine phosphatase non-receptor type 22 (PTPN22) locus, is essential for Csk nanocluster re-recruitment and for maintenance of the synaptic PAG population.

ER/K-link-Leveraging a native protein linker to probe dynamic cellular interactions

ER/K α-helices are a subset of single alpha helical domains, which exhibit unusual stability as isolated protein secondary structures. They adopt an elongated structural conformation, while regulating the frequency of interactions between proteins or polypeptides fused to their ends. Here we review recent advances on the structure, stability and function of ER/K α-helices as linkers (ER/K linkers) in native proteins. We describe methodological considerations in the molecular cloning, protein expression and measurement of interaction strengths, using sensors incorporating ER/K linkers. We highlight biological insights obtained over the last decade by leveraging distinct biophysical features of ER/K-linked sensors. We conclude with the outlook for the use of ER/K linkers in the selective modulation of dynamic cellular interactions.

Unscrambling fluorophore blinking for comprehensive cluster detection via photoactivated localization microscopy

Determining nanoscale protein distribution via Photoactivated Localization Microscopy (PALM) mandates precise knowledge of the applied fluorophore's blinking properties to counteract overcounting artifacts that distort the resulting biomolecular distributions. Here, we present a readily applicable methodology to determine, optimize and quantitatively account for the blinking behavior of any PALM-compatible fluorophore. Using a custom-designed platform, we reveal complex blinking of two photoswitchable fluorescence proteins (PS-CFP2 and mEOS3.2) and two photoactivatable organic fluorophores (PA Janelia Fluor 549 and Abberior CAGE 635) with blinking cycles on time scales of several seconds. Incorporating such detailed information in our simulation-based analysis package allows for robust evaluation of molecular clustering based on individually recorded single molecule localization maps.

The role of competing mechanisms on Lck regulation

Lck is a Src-related protein tyrosine kinase that associates with CD4 and CD8 molecules and is essential to T cell development and T cell activation. Regulatory mechanisms of Lck are diverse and controversy exists regarding the importance of each mechanism. The balance of phosphorylation at the inhibitory and activating Tyr residues is maintained by a balance between CD45 and Csk and is dependent upon intact intracellular trafficking machinery. Current evidence shows that lipid-binding changes depending on Lck conformation and that phosphorylation-induced conformational changes in Lck modulate its kinase activity potentially through regulation of Lck clustering at the plasma membrane. Downstream regulators such as ZAP-70 mediate negative feedback that is dependent on Tyr¹⁹² phosphorylation. This review examines the diverse regulation of Lck in detail, highlighting the role of each mechanism on maintaining an appropriate amount of Lck in each conformational state, thus allowing for an efficient, appropriate, and controlled amount of T cell activation following TCR stimulation.

Noncanonical binding of Lck to CD3ε promotes TCR signaling and CAR function

Initiation of T cell antigen receptor (TCR) signaling involves phosphorylation of CD3 cytoplasmic tails by the tyrosine kinase Lck. How Lck is recruited to the TCR to initiate signaling is not well known. We report a previously unknown binding motif in the CD3ε cytoplasmic tail that interacts in a noncanonical mode with the Lck SH3 domain: the receptor kinase (RK) motif. The RK motif is accessible only upon TCR ligation, demonstrating how ligand binding leads to Lck recruitment. Binding of the Lck SH3 domain to the exposed RK motif resulted in local augmentation of Lck activity, CD3 phosphorylation, T cell activation and thymocyte development. Introducing the RK motif into a well-characterized 41BB-based chimeric antigen receptor enhanced its antitumor function in vitro and in vivo. Our findings underscore how a better understanding of the functioning of the TCR might promote rational improvement of chimeric antigen receptor design for the treatment of cancer.

A Review of Super-Resolution Single-Molecule Localization Microscopy Cluster Analysis and Quantification Methods

Single-molecule localization microscopy (SMLM) is a relatively new imaging modality, winning the 2014 Nobel Prize in Chemistry, and considered as one of the key super-resolution techniques. SMLM resolution goes beyond the diffraction limit of light microscopy and achieves resolution on the order of 10-20 nm. SMLM thus enables imaging single molecules and study of the low-level molecular interactions at the subcellular level. In contrast to standard microscopy imaging that produces 2D pixel or 3D voxel grid data, SMLM generates big data of 2D or 3D point clouds with millions of localizations and associated uncertainties. This unprecedented breakthrough in imaging helps researchers employ SMLM in many fields within biology and medicine, such as studying cancerous cells and cell-mediated immunity and accelerating drug discovery. However, SMLM data quantification and interpretation methods have yet to keep pace with the rapid advancement of SMLM imaging. Researchers have been actively exploring new computational methods for SMLM data analysis to extract biosignatures of various biological structures and functions. In this survey, we describe the state-of-the-art clustering methods adopted to analyze and quantify SMLM data and examine the capabilities and shortcomings of the surveyed methods. We classify the methods according to (1) the biological application (i.e., the imaged molecules/structures), (2) the data acquisition (such as imaging modality, dimension, resolution, and number of localizations), and (3) the analysis details (2D versus 3D, field of view versus region of interest, use of machine-learning and multi-scale analysis, biosignature extraction, etc.). We observe that the majority of methods that are based on second-order statistics are sensitive to noise and imaging artifacts, have not been applied to 3D data, do not leverage machine-learning formulations, and are not scalable for big-data analysis. Finally, we summarize state-of-the-art methodology, discuss some key open challenges, and identify future opportunities for better modeling and design of an integrated computational pipeline to address the key challenges.

Analysis methods for interrogating spatial organisation of single molecule localisation microscopy data

Single-molecule localisation microscopy (SMLM) gives access to biological information below the diffraction limit, allowing nanoscale cellular structures to be probed. The data output is unlike that of conventional microscopy images, instead consisting of an array of molecular coordinates. These represent a spatial point pattern that attempts to approximate, as closely as possible, the underlying positions of the molecules of interest. Here, we review the analysis methods that can be used to extract biological insight from SMLM data, in particular for the application of quantifying nanoscale molecular clustering. We review how some of the common artefacts inherent in SMLM can corrupt the acquired data, and therefore, how the output of SMLM cluster analysis should be interpreted.

Conformational States Control Lck Switching between Free and Confined Diffusion Modes in T Cells

T cell receptor phosphorylation by Lck is an essential step in T cell activation. It is known that the conformational states of Lck control enzymatic activity; however, the underlying principles of how Lck finds its substrate over the plasma membrane remain elusive. Here, single-particle tracking is paired with photoactivatable localization microscopy to observe the diffusive modes of Lck in the plasma membrane. Individual Lck molecules switched between free and confined diffusion in both resting and stimulated T cells. Lck mutants locked in the open conformation were more confined than Lck mutants in the closed conformation. Further confinement of kinase-dead versions of Lck suggests that Lck confinement was not caused by phosphorylated substrates. Our data support a model in which confined diffusion of open Lck results in high local phosphorylation rates, and inactive, closed Lck diffuses freely to enable long-range distribution over the plasma membrane.

Machine learning for cluster analysis of localization microscopy data

Quantifying the extent to which points are clustered in single-molecule localization microscopy data is vital to understanding the spatial relationships between molecules in the underlying sample. Many existing computational approaches are limited in their ability to process large-scale data sets, to deal effectively with sample heterogeneity, or require subjective user-defined analysis parameters. Here, we develop a supervised machine-learning approach to cluster analysis which is fast and accurate. Trained on a variety of simulated clustered data, the neural network can classify millions of points from a typical single-molecule localization microscopy data set, with the potential to include additional classifiers to describe different subtypes of clusters. The output can be further refined for the measurement of cluster area, shape, and point-density. We demonstrate this approach on simulated data and experimental data of the kinase Csk and the adaptor PAG in primary human T cell immunological synapses.

The characterization of clusters in single-molecule microscopy data is vital to reconstruct emerging spatial patterns. Here, the authors present a fast and accurate machine-learning approach to clustering, to address the issues related to the size of the data and to sample heterogeneity.

Whole-cell imaging of plasma membrane receptors by 3D lattice light-sheet dSTORM

The molecular organization of receptors in the plasma membrane of cells is paramount for their functionality. We combined lattice light-sheet (LLS) microscopy with three-dimensional (3D) single-molecule localization microscopy (dSTORM) and single-particle tracking to quantify the expression and distribution, and mobility of CD56 receptors on whole fixed and living cells, finding that CD56 accumulated at cell-cell interfaces. For comparison, we investigated two other receptors, CD2 and CD45, which showed different expression levels and distributions in the plasma membrane. Overall, 3D-LLS-dSTORM enabled imaging and single-particle tracking of plasma membrane receptors with single-molecule sensitivity unperturbed by surface effects. Our results demonstrate that receptor distribution and mobility are largely unaffected by contact to the coverslip but the measured localization densities are in general lower at the basal plasma membrane due to partial limited accessibility for antibodies.

Single-molecule investigations of T-cell activation

T-cell activation is the central event governing its development, differentiation, and effector functions. T-cell activation is initiated by the direct physical interaction of the T cell antigen receptor (TCR) with cognate peptide presented by the major histocompatibility complex (pMHC) molecule expressed on the antigen presenting cell (APC) surface. Since the identification of TCR as the only receptor for antigen on T cells three decades ago, studies have elucidated the major molecular players and signaling events responding to TCR stimulation. However, the question of how the physical event of pMHC binding is converted across the membrane into chemical events to initiate signal transduction remains elusive. Here we review recent investigations of T-cell activation using single-molecule force and fluorescence techniques that shed new light on this key question.