A Multimodal Platform for Simultaneous T-Cell Imaging, Defined Activation, and Mechanobiological Characterization

Mechanical regulation of lymphocyte activation and function

Mechanosensing, or how cells sense and respond to the physical environment, is crucial for many aspects of biological function, ranging from cell movement during development to cancer metastasis, the immune response and gene expression driving cell fate determination. Relevant physical stimuli include the stiffness of the extracellular matrix, contractile forces, shear flows in blood vessels, complex topography of the cellular microenvironment and membrane protein mobility. Although mechanosensing has been more widely studied in non-immune cells, it has become increasingly clear that physical cues profoundly affect the signaling function of cells of the immune system. In this Review, we summarize recent studies on mechanical regulation of immune cells, specifically lymphocytes, and explore how the force-generating cytoskeletal machinery might mediate mechanosensing. We discuss general principles governing mechanical regulation of lymphocyte function, spanning from the molecular scale of receptor activation to cellular responses to mechanical stimuli.

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.

Understanding How Cells Probe the World: A Preliminary Step towards Modeling Cell Behavior?

Cell biologists have long aimed at quantitatively modeling cell function. Recently, the outstanding progress of high-throughput measurement methods and data processing tools has made this a realistic goal. The aim of this paper is twofold: First, to suggest that, while much progress has been done in modeling cell states and transitions, current accounts of environmental cues driving these transitions remain insufficient. There is a need to provide an integrated view of the biochemical, topographical and mechanical information processed by cells to take decisions. It might be rewarding in the near future to try to connect cell environmental cues to physiologically relevant outcomes rather than modeling relationships between these cues and internal signaling networks. The second aim of this paper is to review exogenous signals that are sensed by living cells and significantly influence fate decisions. Indeed, in addition to the composition of the surrounding medium, cells are highly sensitive to the properties of neighboring surfaces, including the spatial organization of anchored molecules and substrate mechanical and topographical properties. These properties should thus be included in models of cell behavior. It is also suggested that attempts at cell modeling could strongly benefit from two research lines: (i) trying to decipher the way cells encode the information they retrieve from environment analysis, and (ii) developing more standardized means of assessing the quality of proposed models, as was done in other research domains such as protein structure prediction.

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.

Is There a Need for a More Precise Description of Biomolecule Interactions to Understand Cell Function?

An important goal of biological research is to explain and hopefully predict cell behavior from the molecular properties of cellular components. Accordingly, much work was done to build extensive “omic” datasets and develop theoretical methods, including computer simulation and network analysis to process as quantitatively as possible the parameters contained in these resources. Furthermore, substantial effort was made to standardize data presentation and make experimental results accessible to data scientists. However, the power and complexity of current experimental and theoretical tools make it more and more difficult to assess the capacity of gathered parameters to support optimal progress in our understanding of cell function. The purpose of this review is to focus on biomolecule interactions, the interactome, as a specific and important example, and examine the limitations of the explanatory and predictive power of parameters that are considered as suitable descriptors of molecular interactions. Recent experimental studies on important cell functions, such as adhesion and processing of environmental cues for decision-making, support the suggestion that it should be rewarding to complement standard binding properties such as affinity and kinetic constants, or even force dependence, with less frequently used parameters such as conformational flexibility or size of binding molecules.