The spatio-temporal control of effector T cell migration

Abstract

Effector T cells leave the lymph nodes armed with specialized functional attributes. Their antigenic targets may be located anywhere in the body, posing the ultimate challenge: how to efficiently identify the target tissue, navigate through a complex tissue matrix and, ultimately, locate the immunological insult. Recent advances in real-time in situ imaging of effector T cell migratory behaviour have revealed a great degree of mechanistic plasticity that enables effector T cells to push and squeeze their way through inflamed tissues. This process is shaped by an array of 'stop' and 'go' guidance signals including target antigens, chemokines, integrin ligands and the mechanical cues of the inflamed microenvironment. Effector T cells must sense and interpret these competing signals to correctly position themselves to mediate their effector functions for complete and durable responses in infectious disease and malignancy. Tuning T cell migration therapeutically will require a new understanding of this complex decision-making process.

Figure 1.. The study of T cell migration: a trade-off between molecular resolution and biological complexity

The tool box for in situ analysis of T cell migration is growing rapidly thanks to innovations in resolution through tissue-clearing techniques and super-resolution imaging modalities. Increasing molecular resolution often results in loss of biological complexity. At one end of the spectrum, the use of photoactivated localization microscopy (PALM) and stochastic optical reconstruction microscopy (STORM) facilitates single molecule analysis in whole cells, enabling the determination of conformational changes in single integrin heterodimers in migrating cells. Use of total internal reflection fluorescence microscopy (TIRF) microscopy has enabled the study of the dynamics of force transmission close (within ~100nm) to the plasma membrane of migrating cells. Real-time 3D analysis of T cell surface topography is possible with light-sheet microscopy. These tools have provided critical insight into molecular mechanism, but cannot be utilized in complex 3D tissues of the living animal. At the other end of the spectrum, advances in 3D histology using tissue clearing techniques and multiplex confocal microscopy has provided an unprecedented look at antigen dispersal and immune cell position in 3D, but the dynamics of T cell migration are lost. In between, the use of intravital multiphoton microscopy provides the ability to visualize T cell migration in real-time in the context of tissue complexity (albeit for relatively short periods of time, hours). Development of photoactivation tools and force sensors to assess molecular details and manipulate signals in individual migrating cells in real time by multiphoton will help to bridge these gaps in scale.

Figure 2.. Mode of migration is shaped by input from multiple signals

(A) A phase space diagram illustrating the cooperative behaviour of chemoattractants, adhesive ligands and the degree of confinement or tissue topography in promoting or inhibiting cell motility and tissue exploration. The upper diagram is based on a gaussian function with two variables (chemoattractant versus adhesive ligand). The presence of one parameter without the other is unable to support motility. High levels of adhesion or chemoattractant result in T cell arrest by being stuck in place or ‘spinning their wheels’, respectively. The shaded regions indicate migration modes occupied by T cells that favour chemokine or adhesion dependency. The lower diagrams introduce a third variable, confinement, and illustrate how the peak (optimal exploration) moves towards chemokine-based efficiency under high confinement associated with dense ECM (left) and towards adhesion-requirements under low confinement (right). (B) 4D landscape model of 3 variables (X, Y, Z) with a fourth functional dimension of exploration efficiency. In vivo, gaussian functions and simple relations between each variable are unlikely, rather the tuning of T cell exploration in the tissue will be determined by local microdomains resulting in a highly variable navigable landscape. Here x, y, z are hypothetical variables as there is insufficient data to map integrated responses to known guidance cues, but each variable would represent an individual chemokine, integrin ligand or specific mechanical parameter. (C) Intravital multiphoton microscope image of migrating Th1 cells (green) in a dermal collagen network (white, second harmonic generation (SHG) to illustrate the variability of just one visible parameter, physical confinement, in vivo. Although in reality, these cells are integrating signals from multiple ‘hidden’ factors such as chemokines and integrin ligands.

Figure 3.. Regulation of effector T cell migration within inflamed tissues

Successful tissue immunity requires efficient T cell migration within the inflamed tissue. The migratory path is shaped by multiple guidance cues spatiotemporal displayed in distinct microenvironments. At the tissue level, Effector T cells (green) must undergo extravasation or transendothelial migration from the blood into tissue, cross the basement membrane, ‘search’ the inflamed tissue for antigen-bearing target cells (antigen presenting cell, purple) for peripheral reactivation and exert effector function at foci of infection. This migratory path is influenced (promoted and inhibited) by: the density and composition of the matrix; the multivariate and dynamic display of chemoattractants; effector T cell intrinsic motility programming that pre-sets receptivity to guidance cues and optimizes the ability to ‘search’ for tissue targets; the density and distribution of antigen-bearing targets; pathogen-specific infection niches and the ability to retain T cells for rapid recall.

Figure 4.. Spatiotemporal optimization of effector T cell positioning

A summary of the control points that build an efficient effector T cell response. The complexity of external cues and T cell receptivity to these cues is increased by the inflammatory milieu and by T cell differentiation, but can be honed at the tissue site by spatiotemporal mechanisms that appear to amplify the target to optimize effector T cell-specific positioning. Receptivity is enhanced as T cells differentiate from naive to effector T cells (for example, Th1, Th2, Th17 cells) in the lymph node where intrinsic programming drives expression of receptor and signaling machinery that promotes biased receptivity to guidance cues at the inflamed tissue. Once the effector T cells enter the inflamed tissue, a sharp increase in complexity of external cues at the tissue site is driven by a host of competing guidance cues (indicated by the shaded gray boxes) that promote or restrict the ability of effector T cells to ‘search’ the inflamed tissue. This complexity is functionally simplified by non-random spatial clustering of antigen and guidance cues within the inflamed/infected tissue, that appears to amplify the target in an effector T cell-specific way, by reducing the scope of the tissue search and promoting local retention.