Dynamic properties of the tight junction barrier

Abstract

A principal role of tight junctions is to seal the apical intercellular space and limit paracellular flux of ions and molecules. Despite the fact that tight junctions form heavily cross-linked structures, functional studies have fostered the hypothesis that the tight junction barrier is dynamic and defined by opening and closing events. However, it has been impossible to directly measure tight junction barrier function with sufficient resolution to detect such events. Nevertheless, recent electrophysiological and sieving studies have provided tremendous insight into the presence of at least two pathways of trans-tight junction flux: a high-capacity ion-selective "pore" pathway and a low-capacity "leak" pathway that allows the passage of macromolecules. Furthermore, it is now known that the tight junction molecular structure is highly dynamic and that dynamics are correlated with barrier function. Taken together, these data support a dynamic model of tight junction conductance and suggest that regulation of tight junction openings and closings may provide sensitive means of barrier regulation.

Figure 1

Size dependence of paracellular flux (solid black line) indicates the presence of two pathways. (A) A high-capacity pore pathway (dashed green line) is responsible for trans-tight junction flux of small ions and molecules, whereas a leaky pathway (dashed red line) allows paracellular flux of larger molecules (after Refs. , , and 17). (B) Claudins primarily regulate the pore pathway, while occludin appears to be important to leak pathway regulation (after Ref. 29).^,,

Figure 2

IL-13 and TNF-α differentially regulate pore and leak pathways of tight junction flux. (A) Claudin-2 protein was increased by 308%, and occludin protein was reduced by 60% after respective treatments with IL-13 or TNF-α. (B) IL-13 specifically increased claudin-2 localization at the tight junction without affecting occludin or ZO-1. In contrast, TNF-α caused occludin internalization without affecting ZO-1 or claudin-2. Bar, 10 µm. (C) TNF-α (red; 2.5 ng/mL) and IL-13 (green; 0.1 ng/mL) reduced TER of T84 monolayers cells at 4 and 12 h, respectively. (D) IL-13 (green), but not TNF-α (red), increased PNa⁺/PCl⁻ of T84 monolayers. (**P ≤ 0.01; ***P ≤ 0.001, SEM). (E) TNF-α (red), but not IL-13 (green), increased the paracellular permeability of 4 kDa dextran (from Ref. 23).

Figure 3

Tight junction proteins are dynamic and undergo continuous remodeling in steady state. (A) Computer models were established based on fluorescence recovery after photobleaching of fluorescently labeled claudin-1, occludin, or ZO-1. The model reflects distinct dynamic behavior and exchange of these proteins within three cellular compartments: tight junction, lateral membrane, and cytosol. Claudin-1 is largely anchored at the tight junction, while occludin exchanges with a small lateral membrane pool (20% of total). ZO-1 is immobile at the tight junction and exchanges with intracellular pools (from Ref. 30). (B) A laser is used to transiently photobleach a region of tight junction–expressing EGFP-labeled tight junction proteins (here demonstrated for ZO-1 before and after a laser pulse at t = 0). (C–E) Kymographs demonstrate time course of fluorescence recovery in the tight junction region indicated by the dashed line in Figure 3C (simulation parameters from Ref. 31). (C) ZO-1 recovery occurs entirely from intracellular pools. (D) Occludin recovery is fast and occurs from the tight junction and lateral membrane. (E) Claudin-1 recovery is slow and occurs from a mobile pool of claudin in the adjacent area of the tight junction.

Figure 4

Static and dynamic simulations are used to predict tight junction pore barrier. (A) In a static model, each tight junction strand has a low conductance (2 pS per 100 nm) and is populated by four 70 pS claudin pores per 100 nm of tight junction. (B) In a dynamic model, only a percentage of claudins form conductive pores, and pores randomly flicker between open and closed states with defined probabilities. The percentage of open pores is defined by the probability of a closed claudin moving to an open state and an open claudin moving to a closed state. (C) In a dynamic model (red), conductance is higher than would be predicted for a simple inverse relationship with strand number (as is true for the static model, green), and conductance may be quite sensitive to the percentage of open claudin-2 pores.