Measurement of Forces Acting on Single T-Cell Receptors.

Molecular forces are increasingly recognized as an important parameter to understand cellular signaling processes. In the recent years, evidence accumulated that also T-cells exert tensile forces via their T-cell receptor during the antigen recognition process. To measure such intercellular pulling forces, one can make use of the elastic properties of spider silk peptides, which act similar to Hookean springs: increased strain corresponds to increased stress applied to the peptide. Combined with Förster resonance energy transfer (FRET) to read out the strain, such peptides represent powerful and versatile nanoscopic force sensing tools. In this paper, we provide a detailed protocol how to synthesize a molecular force sensor for application in T-cell antigen recognition and hands-on guidelines on experiments and analysis of obtained single molecule FRET data.

Monomeric agonist peptide/MHCII complexes activate T-cells in an autonomous fashion.

Molecular crowding of agonist peptide/MHC class II complexes (pMHCIIs) with structurally similar, yet per se non-stimulatory endogenous pMHCIIs is postulated to sensitize T-cells for the recognition of single antigens on the surface of dendritic cells and B-cells. When testing this premise with the use of advanced live cell microscopy, we observe pMHCIIs as monomeric, randomly distributed entities diffusing rapidly after entering the APC surface. Synaptic TCR engagement of highly abundant endogenous pMHCIIs is low or non-existent and affects neither TCR engagement of rare agonist pMHCII in early and advanced synapses nor agonist-induced TCR-proximal signaling. Our findings highlight the capacity of single freely diffusing agonist pMHCIIs to elicit the full T-cell response in an autonomous and peptide-specific fashion with consequences for adaptive immunity and immunotherapeutic approaches.

Immune cell profiles and patient clustering in complex cases of interstitial lung disease.

Interstitial lung disease comprises numerous clinical entities posing significant challenges towards a prompt and accurate diagnosis. Amongst the contributing factors are intricate pathophysiological mechanisms, an overlap between conditions, and interobserver disagreement. We developed a model for patient clustering offering an additional approach to such complex clinical cases. The model is based on surface phenotyping of over 40 markers on immune cells isolated from bronchoalveolar lavage in combination with clinical data. Based on the marker expression pattern we constructed an individual immune cell profile, then merged these to create a global profile encompassing various pathologies. The contribution of each participant to the global profile was assessed through dimensionality reduction tools and the ensuing similarity between samples was calculated. Our model enables two approaches. First, assessing the immune cell population landscape similarity between patients within a diagnostic group allows rapid identification of divergent profiles, which is particularly helpful for cases with uncertain diagnoses. Second, sample clustering is based exclusively on the calculated similarity of the immune cell profiles, thereby removing physician bias and relying on cellular nearest neighbors.

Mechanosurveillance: Tiptoeing T Cells.

Efficient scanning of tissue that T cells encounter during their migratory life is pivotal to protective adaptive immunity. In fact, T cells can detect even a single antigenic peptide/MHC complex (pMHC) among thousands of structurally similar yet non-stimulatory endogenous pMHCs on the surface of antigen-presenting cells (APCs) or target cells. Of note, the glycocalyx of target cells, being composed of proteoglycans and bulky proteins, is bound to affect and even modulate antigen recognition by posing as a physical barrier. T cell-resident microvilli are actin-rich membrane protrusions that puncture through such barriers and thereby actively place the considerably smaller T-cell antigen receptors (TCRs) in close enough proximity to APC-presented pMHCs so that productive interactions may occur efficiently yet under force. We here review our current understanding of how the plasticity of T-cell microvilli and physicochemical properties of the glycocalyx may affect early events in T-cell activation. We assess insights gained from studies on T-cell plasma membrane ultrastructure and provide an update on current efforts to integrate biophysical aspects such as the amplitude and directionality of TCR-imposed mechanical forces and the distribution and lateral mobility of plasma membrane-resident signaling molecules into a more comprehensive view on sensitized T-cell antigen recognition.

Automated Two-dimensional Spatiotemporal Analysis of Mobile Single-molecule FRET Probes.

Single-molecule Förster resonance energy transfer (smFRET) is a versatile technique reporting on distances in the sub-nanometer to nanometer range. It has been used in a wide range of biophysical and molecular biological experiments, including the measurement of molecular forces, characterization of conformational dynamics of biomolecules, observation of intracellular colocalization of proteins, and determination of receptor-ligand interaction times. In a widefield microscopy configuration, experiments are typically performed using surface-immobilized probes. Here, a method combining single-molecule tracking with alternating excitation (ALEX) smFRET experiments is presented, permitting the acquisition of smFRET time traces of surface-bound, yet mobile probes in plasma membranes or glass-supported lipid bilayers. For the analysis of recorded data, an automated, open-source software collection was developed supporting (i) the localization of fluorescent signals, (ii) single-particle tracking, (iii) determination of FRET-related quantities including correction factors, (iv) stringent verification of smFRET traces, and (v) intuitive presentation of the results. The generated data can conveniently be used as input for further exploration via specialized software, e.g., for the assessment of the diffusional behavior of probes or the investigation of FRET transitions.

Temporal analysis of T-cell receptor-imposed forces via quantitative single molecule FRET measurements.

Mechanical forces acting on ligand-engaged T-cell receptors (TCRs) have previously been implicated in T-cell antigen recognition, yet their magnitude, spread, and temporal behavior are still poorly defined. We here report a FRET-based sensor equipped either with a TCR-reactive single chain antibody fragment or peptide-loaded MHC, the physiological TCR-ligand. The sensor was tethered to planar glass-supported lipid bilayers (SLBs) and informed most directly on the magnitude and kinetics of TCR-imposed forces at the single molecule level. When confronting T-cells with gel-phase SLBs we observed both prior and upon T-cell activation a single, well-resolvable force-peak of approximately 5 pN and force loading rates on the TCR of 1.5 pN per second. When facing fluid-phase SLBs instead, T-cells still exerted tensile forces yet of threefold reduced magnitude and only prior to but not upon activation.

Statistical analysis of 3D localisation microscopy images for quantification of membrane protein distributions in a platelet clot model.

We present the software platform 2CALM that allows for a comparative analysis of 3D localisation microscopy data representing protein distributions in two biological samples. The in-depth statistical analysis reveals differences between samples at the nanoscopic level using parameters such as cluster-density and -curvature. An automatic classification system combines multiplex and multi-level statistical approaches into one comprehensive parameter for similarity testing of the compared samples. We demonstrated the biological importance of 2CALM, comparing the protein distributions of CD41 and CD62p on activated platelets in a 3D artificial clot. Additionally, using 2CALM, we quantified the impact of the inflammatory cytokine interleukin-1ß on platelet activation in clots. The platform is applicable to any other cell type and biological system and can provide new insights into biological and medical applications.

Monomeric TCRs drive T cell antigen recognition.

T cell antigen recognition requires T cell antigen receptors (TCRs) engaging MHC-embedded antigenic peptides (pMHCs) within the contact region of a T cell with its conjugated antigen-presenting cell. Despite micromolar TCR:pMHC affinities, T cells respond to even a single antigenic pMHC, and higher-order TCRs have been postulated to maintain high antigen sensitivity and trigger signaling. We interrogated the stoichiometry of TCRs and their associated CD3 subunits on the surface of living T cells through single-molecule brightness and single-molecule coincidence analysis, photon-antibunching-based fluorescence correlation spectroscopy and Förster resonance energy transfer measurements. We found exclusively monomeric TCR-CD3 complexes driving the recognition of antigenic pMHCs, which underscores the exceptional capacity of single TCR-CD3 complexes to elicit robust intracellular signaling.

Kinetic analysis of single molecule FRET transitions without trajectories.

Single molecule Förster resonance energy transfer (smFRET) is a popular tool to study biological systems that undergo topological transitions on the nanometer scale. smFRET experiments typically require recording of long smFRET trajectories and subsequent statistical analysis to extract parameters such as the states' lifetimes. Alternatively, analysis of probability distributions exploits the shapes of smFRET distributions at well chosen exposure times and hence works without the acquisition of time traces. Here, we describe a variant that utilizes statistical tests to compare experimental datasets with Monte Carlo simulations. For a given model, parameters are varied to cover the full realistic parameter space. As output, the method yields p-values which quantify the likelihood for each parameter setting to be consistent with the experimental data. The method provides suitable results even if the actual lifetimes differ by an order of magnitude. We also demonstrated the robustness of the method to inaccurately determine input parameters. As proof of concept, the new method was applied to the determination of transition rate constants for Holliday junctions.

Suitable transfection methods for single particle tracing in plant suspension cells.

BACKGROUND: A multitude of different imaging systems are already available to image genetically altered RNA species; however, only a few of these techniques are actually suitable to visualize endogenous RNA. One possibility is to use fluorescently-labelled and hybridization-sensitive probes. In order to yield more information about the exact localization and movement of a single RNA molecule, it is necessary to image such probes with highly sensitive microscope setups. More challenges arise if such experiments are conducted in plant cells due to their high autofluorescence and demanding transfection procedures. RESULTS: Here, we report in planta imaging of single RNA molecules using fluorescently labeled molecular beacons. We tested three different transfection protocols in order to identify optimal conditions for transfection of fluorescent DNA probes and their subsequent detection at the single molecule level. CONCLUSIONS: We found that an optimized heat shock protocol provided a vastly improved transfection method for small DNA molecules which were used for subsequent single RNA molecule detection in living plant suspension cells.

Imaging of endogenous messenger RNA splice variants in living cells reveals nuclear retention of transcripts inaccessible to nonsense-mediated decay in Arabidopsis.

Alternative splicing (AS) is an important regulatory process that leads to the creation of multiple RNA transcripts from a single gene. Alternative transcripts often carry premature termination codons (PTCs), which trigger nonsense-mediated decay (NMD), a cytoplasmic RNA degradation pathway. However, intron retention, the most prevalent AS event in plants, often leads to PTC-carrying splice variants that are insensitive to NMD; this led us to question the fate of these special RNA variants. Here, we present an innovative approach to monitor and characterize endogenous mRNA splice variants within living plant cells. This method combines standard confocal laser scanning microscopy for molecular beacon detection with a robust statistical pipeline for sample comparison. We demonstrate this technique on the localization of NMD-insensitive splice variants of two Arabidopsis thaliana genes, RS2Z33 and the SEF factor. The experiments reveal that these intron-containing splice variants remain within the nucleus, which allows them to escape the NMD machinery. Moreover, fluorescence recovery after photobleaching experiments in the nucleoplasm show a decreased mobility of intron-retained mRNAs compared with fully spliced RNAs. In addition, differences in mobility were observed for an mRNA dependent on its origin from an intron-free or an intron-containing gene.

TeloTool: a new tool for telomere length measurement from terminal restriction fragment analysis with improved probe intensity correction.

Telomeres comprise the protective caps of natural chromosome ends and function in the suppression of DNA damage signaling and cellular senescence. Therefore, techniques used to determine telomere length are important in a number of studies, ranging from those investigating telomeric structure to effects on human disease. Terminal restriction fragment (TRF) analysis has for a long time shown to be one of the most accurate methods for quantification of absolute telomere length and range from a number of species. As this technique centers on standard Southern blotting, telomeric DNA is observed on resulting autoradiograms as a heterogeneous smear. Methods to accurately determine telomere length from telomeric smears have proven problematic, and no reliable technique has been suggested to obtain mean telomere length values. Here, we present TeloTool, a new program allowing thorough statistical analysis of TRF data. Using this new method, a number of methodical biases are removed from previously stated techniques, including assumptions based on probe intensity corrections. This program provides a standardized mean for quick and reliable extraction of quantitative data from TRF autoradiograms; its wide application will allow accurate comparison between datasets generated in different laboratories.

Spatial cluster analysis of nanoscopically mapped serotonin receptors for classification of fixed brain tissue.

We present a cluster spatial analysis method using nanoscopic dSTORM images to determine changes in protein cluster distributions within brain tissue. Such methods are suitable to investigate human brain tissue and will help to achieve a deeper understanding of brain disease along with aiding drug development. Human brain tissue samples are usually treated postmortem via standard fixation protocols, which are established in clinical laboratories. Therefore, our localization microscopy-based method was adapted to characterize protein density and protein cluster localization in samples fixed using different protocols followed by common fluorescent immunohistochemistry techniques. The localization microscopy allows nanoscopic mapping of serotonin 5-HT1A receptor groups within a two-dimensional image of a brain tissue slice. These nanoscopically mapped proteins can be confined to clusters by applying the proposed statistical spatial analysis. Selected features of such clusters were subsequently used to characterize and classify the tissue. Samples were obtained from different types of patients, fixed with different preparation methods, and finally stored in a human tissue bank. To verify the proposed method, samples of a cryopreserved healthy brain have been compared with epitope-retrieved and paraffin-fixed tissues. Furthermore, samples of healthy brain tissues were compared with data obtained from patients suffering from mental illnesses (e.g., major depressive disorder). Our work demonstrates the applicability of localization microscopy and image analysis methods for comparison and classification of human brain tissues at a nanoscopic level. Furthermore, the presented workflow marks a unique technological advance in the characterization of protein distributions in brain tissue sections.