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Cytotoxic T lymphocytes (CTLs) kill virus-infected cells and tumor cells, and play a critical role in immune protection. Our knowledge of how the CTL killing efficiency varies with CTL and target cell numbers is limited. Here, we simulate a region of lymphoid tissue using a cellular Potts model to characterize the functional response of CTL killing of target cells, and find that the total killing rate saturates both with the CTL and the target cell densities. The relative saturation in CTL and target cell densities is determined by whether a CTL can kill multiple target cells at the same time, and whether a target cell can be killed by many CTLs together. We find that all the studied regimes can be well described by a double-saturation (DS) function with two different saturation constants. We show that this DS model can be mechanistically derived for the cases where target cells are killed by a single CTL. For the other cases, a biological interpretation of the parameters is still possible. Our results imply that this DS function can be used as a tool to predict the cellular interactions in cytotoxicity data.

It is well established how effector T cells exit the vasculature to enter the peripheral tissues in which an infection is ongoing. However, less is known regarding how CTLs migrate toward infected cells after entry into peripheral organs. Recently, it was shown that the chemokine receptor CXCR3 on T cells has an important role in their ability to localize infected cells and to control vaccinia virus infection. However, the search strategy of T cells for virus-infected targets has not been investigated in detail and could involve chemotaxis toward infected cells, chemokinesis (i.e., increased motility) combined with CTL arrest when targets are detected, or both. In this study, we describe and analyze the migration of CTLs within HSV-1–infected epidermis in vivo. We demonstrate that activated T cells display a subtle distance-dependent chemotaxis toward clusters of infected cells and confirm that this is mediated by CXCR3 and its ligands. Although the chemotactic migration is weak, computer simulations based on short-term experimental data, combined with subsequent long-term imaging indicate that this behavior is crucial for efficient target localization and T cell accumulation at effector sites. Thus, chemotactic migration of effector T cells within peripheral tissue forms an important factor in the speed with which T cells are able to arrive at sites of infection.

To fight infections, rare T cells must quickly home to appropriate lymph nodes (LNs), and reliably localize the antigen (Ag) within them. The first challenge calls for rapid trafficking between LNs, whereas the second may require extensive search within each LN. Here we combine simulations and experimental data to investigate which features of random T cell migration within and between LNs allow meeting these two conflicting demands. Our model indicates that integrating signals from multiple random encounters with Ag-presenting cells permits reliable detection of even low-dose Ag, and predicts a kinetic feature of cognate T cell arrest in LNs that we confirm using intravital two-photon data. Furthermore, we obtain the most reliable retention if T cells transit through LNs stochastically, which may explain the long and widely distributed LN dwell times observed in vivo. Finally, we demonstrate that random migration, both between and within LNs, allows recruiting the majority of cognate precursors within a few days for various realistic infection scenarios. Thus, the combination of two-scale stochastic migration and signal integration is an efficient and robust strategy for T cell immune surveillance., Author Summary Each of the immune system's T lymphocytes recognizes a highly specific molecular pattern, and only a very few T cells are capable of detecting any given infection. These rare cells are at first scattered throughout the body when a pathogen invades the host. To mount an immune response, they need to come together within lymphatic tissue near the infection site, and find cells that carry molecular fragments of the pathogen. Remarkably, experiments show that the immune system solves this needle-in-a-haystack problem in just a few days for various bacterial and viral infections. Aiming to understand how the immune system achieves this, we built a model that brings together classic and recent data on T cell migration. Our model explains how perpetual migration of T cells between and within lymphatic organs helps to find invading pathogens swiftly and reliably. Specifically, our results suggest that T cells can collect signals from activation-inducing cells for several hours, which allows for reliable detection of even low-profile infections. Thus, random T cell trafficking between and within lymphatic organs robustly protects against a broad range of pathogens, and comes close to an “optimal” surveillance strategy.