InterCells: A Generic Monte-Carlo Simulation of Intercellular Interfaces Captures Nanoscale Patterning at the Immune Synapse

Reinforcement learning-guided control strategies for CAR T-cell activation and expansion

Reinforcement learning (RL), a subset of machine learning (ML), could optimize and control biomanufacturing processes, such as improved production of therapeutic cells. Here, the process of CAR T-cell activation by antigen-presenting beads and their subsequent expansion is formulated in silico. The simulation is used as an environment to train RL-agents to dynamically control the number of beads in culture to maximize the population of robust effector cells at the end of the culture. We make periodic decisions of incremental bead addition or complete removal. The simulation is designed to operate in OpenAI Gym, enabling testing of different environments, cell types, RL-agent algorithms, and state inputs to the RL-agent. RL-agent training is demonstrated with three different algorithms (PPO, A2C, and DQN), each sampling three different state input types (tabular, image, mixed); PPO-tabular performs best for this simulation environment. Using this approach, training of the RL-agent on different cell types is demonstrated, resulting in unique control strategies for each type. Sensitivity to input-noise (sensor performance), number of control step interventions, and advantages of pre-trained RL-agents are also evaluated. Therefore, we present an RL framework to maximize the population of robust effector cells in CAR T-cell therapy production.

Adhering interacting cells to two opposing coverslips allows super-resolution imaging of cell-cell interfaces

Cell-cell interfaces convey mechanical and chemical information in multicellular systems. Microscopy has revealed intricate structure of such interfaces, yet typically with limited resolution due to diffraction and unfavourable orthogonal orientation of the interface to the coverslip. We present a simple and robust way to align cell-cell interfaces in parallel to the coverslip by adhering the interacting cells to two opposing coverslips. We demonstrate high-quality diffraction-limited and super-resolution imaging of interfaces (immune-synapses) between fixed and live CD8+ T-cells and either antigen presenting cells or melanoma cells. Imaging methods include bright-field, confocal, STED, dSTORM, SOFI, SRRF and large-scale tiled images. The low background, lack of aberrations and enhanced spatial stability of our method relative to existing cell-trapping techniques allow use of these methods. We expect that the simplicity and wide-compatibility of our approach will allow its wide dissemination for super-resolving the intricate structure and molecular organization in a variety of cell-cell interfaces.

T Cell Activation through Isolated Tight Contacts

T cells engage antigen-presenting cells in search for cognate antigens via dynamic cell protrusions before forming a tight immune synapse. The spatiotemporal events that may lead to rapid TCR triggering and signal amplification in microvilli-driven isolated contacts, and in subsequent, more uniform contacts, remain poorly understood. Here, we combined interference-reflectance microscopy and single-molecule localization microscopy in live cells to resolve TCR-dependent signaling at tight cell contacts. We show that early contacts are sufficient for robust TCR triggering and ZAP-70 recruitment. With cell spreading, TCR activation and ZAP-70 recruitment increase and shift to the edges of the growing tight contacts. CD45 segregates from TCR at tight contacts and is enriched at high local curvature membrane. Surprisingly, cortical actin and LFA localized at contact regions of intermediate tightness. Our results show in molecular detail the roles of early and tight T cell contacts in T cell activation, as both sensing and decision-making entities.

T Cell Membrane Heterogeneity Aids Antigen Recognition and T Cell Activation

T cells are critical for co-ordinating the immune response. T cells are activated when their surface T cell receptors (TCRs) engage cognate antigens in the form of peptide-major histocompatibility complexes (pMHC) presented on the surface of antigen presenting cells (APCs). Large changes in the contact interface between T cells and APCs occur over the course of tens of minutes from the initial contact to the formation of a large-scale junction between the two cells. The mature junction between a T cell and APC is known as the immunological synapse, and this specialized plasma membrane structure is the major platform for TCR signaling. It has long been known that the complex organization of signaling molecules at the synapse is critical for appropriate activation of T cells, but within the last decade advances in microscopy have opened up investigation into the dynamics of T cell surface topology in the immune synapse. From mechanisms mediating the initial contact between T cells and APCs to roles in the organization of molecules in the mature synapse, these studies have made it increasingly clear that local membrane topology has a large impact on signaling processes. This review focuses on the functional consequences of the T cells' highly dynamic and heterogeneous membrane, in particular, how membrane topology leads to the reorganization of membrane proteins on the T cell surface.