Triggering of the T cell receptor (TCR) integrates both binding kinetics and mechanical forces. To understand the contribution of the T cell cytoskeleton to these forces, we triggered T cells using a novel application of atomic force microscopy (AFM). We presented antigenic stimulation using the AFM cantilever while simultaneously imaging with optical microscopy and measuring forces on the cantilever. T cells respond forcefully to antigen after calcium flux. All forces and calcium responses were abrogated upon treatment with an F-actin inhibitor. When we emulated the forces of the T cell using the AFM cantilever, even these actin-inhibited T cells became activated. Purely mechanical stimulation was not sufficient; the exogenous forces had to couple through the TCR. These studies suggest a mechanical-chemical feedback loop in which TCR-triggered T cells generate forceful contacts with antigen-presenting cells to improve access to antigen.

This manuscript details methods to ligate cell-surface receptors on live cells with precise spatiotemporal control using an atomic force microscope (AFM) to deliver ligands. This approach can be used to image cellular responses upon activating T cell receptors when the AFM is mounted on an optical microscope. Moreover, the AFM measures forces generated by the cell during the contact. Using AFM to trigger cellular responses adds an important capability to the field of mechanobiology. We describe how to incorporate anti-CD3 antibodies or other molecules onto an AFM cantilever and how to use AFM to activate T cells. © 2019 by John Wiley & Sons, Inc.

The factors that govern T cell activation control the initiation and progression of adaptive immune responses. T cells recognize their cognate antigen on the surface of antigen-presenting cells (APCs) through the T cell receptor, which results in the formation of a contact region (immune synapse) between the two cells and the activation of the T cells. Activated T cells proliferate and differentiate into effector T cells that secrete cytokines, provide help to B cells, and kill target cells. We asked whether the actin cytoskeleton governs differences in signaling in effector T cells versus naïve (unstimulated) T cells. Using atomic force microscopy and quantitative confocal microscopy, we found that naïve T cells had a mechanically stiffer cortical cytoskeleton than that of effector cells, which resulted in naïve cells forming smaller immune synapses with APCs. This suggests that the cytoskeletal stiffness of the T cell before it undergoes antigen stimulation predicts its subsequent dynamic engagement with APCs and its activation potential. Cytoskeletal rigidity depended on the activity of the actin-severing enzyme cofilin through a pathway requiring the small guanosine triphosphatase RhoA and the kinases ROCK (Rho-activated kinase) and LIMK. These findings suggest that the baseline cytoskeletal state controls T cell responses and that the underlying pathway could be a therapeutic target for modulating adaptive immunity.

Advances in methods that determine cell mechanical phenotype, or mechanotype, have demonstrated the utility of biophysical markers in clinical and research applications ranging from cancer diagnosis to stem cell enrichment. Here, we introduce quantitative deformability cytometry (q-DC), a method for rapid, calibrated, single-cell mechanotyping. We track changes in cell shape as cells deform into microfluidic constrictions, and we calibrate the mechanical stresses using gel beads. We observe that time-dependent strain follows power-law rheology, enabling single-cell measurements of apparent elastic modulus, E_a, and power-law exponent, β. To validate our method, we mechanotype human promyelocytic leukemia (HL-60) cells and thereby confirm q-DC measurements of E_a = 0.53 ± 0.04 kPa. We also demonstrate that q-DC is sensitive to pharmacological perturbations of the cytoskeleton as well as differences in the mechanotype of human breast cancer cell lines (E_a = 2.1 ± 0.1 and 0.80 ± 0.19 kPa for MCF-7 and MDA-MB-231 cells). To establish an operational framework for q-DC, we investigate the effects of applied stress and cell/pore-size ratio on mechanotype measurements. We show that E_a increases with applied stress, which is consistent with stress stiffening behavior of cells. We also find that E_a increases for larger cell/pore-size ratios, even when the same applied stress is maintained; these results indicate strain stiffening and/or dependence of mechanotype on deformation depth. Taken together, the calibrated measurements enabled by q-DC should advance applications of cell mechanotype in basic research and clinical settings.

Macrophages display flexible activation states that range between pro-inflammatory (classical activation) and anti-inflammatory (alternative activation). These macrophage polarization states contribute to a variety of organismal phenotypes such as tissue remodeling and susceptibility to infectious and inflammatory diseases. Several macrophage- or immune-related genes have been shown to modulate infectious and inflammatory disease pathogenesis. However, the potential role that differences in macrophage activation phenotypes play in modulating differences in susceptibility to infectious and inflammatory disease is just emerging. We integrated transcriptional profiling and linkage analyses to determine the genetic basis for the differential murine macrophage response to inflammatory stimuli and to infection with the obligate intracellular parasite Toxoplasma gondii. We show that specific transcriptional programs, defined by distinct genomic loci, modulate macrophage activation phenotypes. In addition, we show that the difference between AJ and C57BL/6J macrophages in controlling Toxoplasma growth after stimulation with interferon gamma and tumor necrosis factor alpha mapped to chromosome 3, proximal to the Guanylate binding protein (Gbp) locus that is known to modulate the murine macrophage response to Toxoplasma. Using an shRNA-knockdown strategy, we show that the transcript levels of an RNA helicase, Ddx1, regulates strain differences in the amount of nitric oxide produced by macrophage after stimulation with interferon gamma and tumor necrosis factor. Our results provide a template for discovering candidate genes that modulate macrophage-mediated complex traits.

Introduction

Metastasis is a fundamentally physical process in which cells deform through narrow gaps and generate forces to invade surrounding tissues. While it is commonly thought that increased cell deformability is an advantage for invading cells, we previously found that more invasive pancreatic ductal adenocarcinoma (PDAC) cells are stiffer than less invasive PDAC cells. Here we investigate potential mechanisms of the simultaneous increase in PDAC cell stiffness and invasion, focusing on the contributions of myosin II, Arp2/3, and formins.

Method

We measure cell invasion using a 3D scratch wound invasion assay and cell stiffness using atomic force microscopy (AFM). To determine the effects of actin- and myosin-mediated force generation on cell stiffness and invasion, we treat cells with pharmacologic inhibitors of myosin II (blebbistatin), Arp2/3 (CK-666), and formins (SMIFH2).

Results

We find that the activity of myosin II, Arp2/3, and formins all contribute to the stiffness of PDAC cells. Interestingly, we find that the invasion of PDAC cell lines is differentially affected when the activity of myosin II, Arp2/3, or formins is inhibited, suggesting that despite having similar tissue origins, different PDAC cell lines may rely on different mechanisms for invasion.

Conclusions

These findings deepen our knowledge of the factors that regulate cancer cell mechanotype and invasion, and incite further studies to develop therapeutics that target multiple mechanisms of invasion for improved clinical benefit.

Spatial transcriptomics seeks to integrate single cell transcriptomic data within the three-dimensional space of multicellular biology. Current methods to correlate a cell's position with its transcriptome in living tissues have various limitations. We developed an approach, called 'ZipSeq', that uses patterned illumination and photocaged oligonucleotides to serially print barcodes ('zipcodes') onto live cells in intact tissues, in real time and with an on-the-fly selection of patterns. Using ZipSeq, we mapped gene expression in three settings: in vitro wound healing, live lymph node sections and a live tumor microenvironment. In all cases, we discovered new gene expression patterns associated with histological structures. In the tumor microenvironment, this demonstrated a trajectory of myeloid and T cell differentiation from the periphery inward. A combinatorial variation of ZipSeq efficiently scales in the number of regions defined, providing a pathway for complete mapping of live tissues, subsequent to real-time imaging or perturbation.

Native vascular extracellular matrices (vECM) consist of elastic fibers that impart varied topographical properties, yet most in vitro models designed to study the effects of topography on cell behavior are not representative of native architecture. Here, we engineer an electrospun elastin-like protein (ELP) system with independently tunable, vECM-mimetic topography and demonstrate that increasing topographical variation causes loss of endothelial cell-cell junction organization. This loss of VE-cadherin signaling and increased cytoskeletal contractility on more topographically varied ELP substrates in turn promote YAP activation and nuclear translocation, resulting in significantly increased endothelial cell migration and proliferation. Our findings identify YAP as a required signaling factor through which fibrous substrate topography influences cell behavior and highlights topography as a key design parameter for engineered biomaterials.

Multiphoton microscopy is a powerful technique for deep in vivo imaging in scattering samples. However, it requires precise, sample-dependent increases in excitation power with depth in order to generate contrast in scattering tissue, while minimizing photobleaching and phototoxicity. We show here how adaptive imaging can optimize illumination power at each point in a 3D volume as a function of the sample's shape, without the need for specialized fluorescent labeling. Our method relies on training a physics-based machine learning model using cells with identical fluorescent labels imaged in situ. We use this technique for in vivo imaging of immune responses in mouse lymph nodes following vaccination. We achieve visualization of physiologically realistic numbers of antigen-specific T cells (~2 orders of magnitude lower than previous studies), and demonstrate changes in the global organization and motility of dendritic cell networks during the early stages of the immune response. We provide a step-by-step tutorial for implementing this technique using exclusively open-source hardware and software.