Exhausted mature dendritic cells exhibit a slower and less persistent random motility but retain chemotaxis against CCL19

Dendritic cells (DCs), which are immune sentinels in the peripheral tissues, play a number of roles, including patrolling for pathogens, internalising antigens, transporting antigens to the lymph nodes (LNs), interacting...

Exhausted mature dendritic cells exhibit a slower and less persistent random motility but retain chemotaxis against CCL19

Dendritic cells (DCs), which are immune sentinels in the peripheral tissues, play a number of roles, including patrolling for pathogens, internalising antigens, transporting antigens to the lymph nodes (LNs), interacting with T cells, and secreting cytokines. The well-coordinated migration of DCs under various immunological or inflammatory conditions is therefore essential to ensure an effective immune response. Upon maturation, DCs migrate faster and more persistently than immature DCs (iDCs), which is believed to facilitate CCR7-dependent chemotaxis. It has been reported that lipopolysaccharide-activated DCs produce IL-12 only transiently, and become resistant to further stimulation through exhaustion. However, little is known about the influence of DC exhaustion on cellular motility. Here, we studied the cellular migration of exhausted DCs in tissue-mimicked confined environments. We found that the speed of exhausted matured DCs (xmDCs) decreased significantly compared to active matured DCs (amDCs) and iDCs. In contrast, the speed fluctuation increased compared to that of amDCs and was similar to that of iDCs. In addition, the diffusivity of the xmDCs was significantly lower than that of the amDCs, which implies that DC exhaustion reduces the space exploration ability. Interestingly, CCR7-dependent chemotaxis against CCL19 in xmDCs was not considerably different from that observed in amDCs. Taken together, we report a unique intrinsic cell migration behavior of xmDCs, which exhibit a slower, less persistent, and less diffusive random motility, which results in the DCs remaining at the site of infection, although a well-preserved CCR7-dependent chemotactic motility is maintained.

Mechanistic and experimental models of cell migration reveal the importance of intercellular interactions in cell invasion

Moving fronts of cells are essential for development, repair and disease progression. Therefore, understanding and quantifying the details of the mechanisms that drive the movement of cell fronts is of wide interest. Quantitatively identifying the role of intercellular interactions, and in particular the role of cell pushing, remains an open question. Indeed, perhaps the most common continuum mathematical idealization of moving cell fronts is to treat the population of cells, either implicitly or explicitly, as a population of point particles undergoing a random walk that neglects intercellular interactions. In this work, we report a combined experimental-modelling approach showing that intercellular interactions contribute significantly to the spatial spreading of a population of cells. We use a novel experimental data set with PC-3 prostate cancer cells that have been pretreated with Mitomycin-C to suppress proliferation. This allows us to experimentally separate the effects of cell migration from cell proliferation, thereby enabling us to focus on the migration process in detail as the population of cells recolonizes an initially-vacant region in a series of two-dimensional experiments. We quantitatively model the experiments using a stochastic modelling framework, based on Langevin dynamics, which explicitly incorporates random motility and various intercellular forces including: (i) long range attraction (adhesion); and (ii) finite size effects that drive short range repulsion (pushing). Quantitatively comparing the ability of this model to describe the experimentally observed population-level behaviour provides us with quantitative insight into the roles of random motility and intercellular interactions. To quantify the mechanisms at play, we calibrate the stochastic model to match experimental cell density profiles to obtain estimates of cell diffusivity, D, and the amplitude of intercellular forces, f0. Our analysis shows that taking a standard modelling approach which ignores intercellular forces provides a poor match to the experimental data whereas incorporating intercellular forces, including short-range pushing and longer range attraction, leads to a faithful representation of the experimental observations. These results demonstrate a significant role for intercellular interactions in cell invasion.Author summaryMoving cell fronts are routinely observed in various physiological processes, such as wound healing, malignant invasion and embryonic morphogenesis. We explore the effects of a previously overlooked mechanism that contributes to population-level front movement: pushing. Our framework is flexible and incorporates range of reasonable biological phenomena, such as random motility, cell-to-cell adhesion, and pushing. We find that neglecting finite size effects and intercellular forces, such as cell pushing, reduces our ability to mimic and predict our experimental observations.

Effect of adhesion and chemokine presentation on T-lymphocyte haptokinesis

The random motility of human T-lymphocytes was measured on microcontact printed surfaces containing ICAM-1 and VCAM-1, and the additional effects of the chemokines CCL21 and CCL19 were investigated. This image shows the morphology of human T-lymphocytes on ICAM-1 substrates in the presence of immobilized CCL21, immunostained for actin (in red) and α-tubulin (in green).

Quantifying the roles of cell motility and cell proliferation in a circular barrier assay

Moving fronts of cells are essential features of embryonic development, wound repair and cancer metastasis. This paper describes a set of experiments to investigate the roles of random motility and proliferation in driving the spread of an initially confined cell population. The experiments include an analysis of cell spreading when proliferation was inhibited. Our data have been analysed using two mathematical models: a lattice-based discrete model and a related continuum partial differential equation model. We obtain independent estimates of the random motility parameter, D , and the intrinsic proliferation rate, λ , and we confirm that these estimates lead to accurate modelling predictions of the position of the leading edge of the moving front as well as the evolution of the cell density profiles. Previous work suggests that systems with a high λ / D ratio will be characterized by steep fronts, whereas systems with a low λ / D ratio will lead to shallow diffuse fronts and this is confirmed in the present study. Our results provide evidence that continuum models, based on the Fisher–Kolmogorov equation, are a reliable platform upon which we can interpret and predict such experimental observations.