Imaging effects of hyperosmolality on individual tricellular junctions

Abstract

The use of hyperosmolar agents (osmotherapy) has been a major treatment for intracranial hypertension, which occurs frequently in brain diseases or trauma. However, side-effects of osmotherapy on the brain, especially on the blood-brain barrier (BBB) are still not fully understood. Hyperosmolar conditions, termed hyperosmolality here, are known to transiently disrupt the tight junctions (TJs) at the endothelium of the BBB resulting in loss of BBB function. Present techniques for evaluation of BBB transport typically reveal aggregated responses from the entirety of BBB transport components, with little or no opportunity to evaluate heterogeneity present in the system. In this study, we utilized potentiometric-scanning ion conductance microscopy (P-SICM) to acquire nanometer-scale conductance maps of Madin-Darby Canine Kidney strain II (MDCKII) cells under hyperosmolality, from which two types of TJs, bicellular tight junctions (bTJs) and tricellular tight junctions (tTJs), can be visualized and differentiated. We discovered that hyperosmolality leads to increased conductance at tTJs without significant alteration in conductance at bTJs. To quantify this effect, an automated computer vision algorithm was designed to extract and calculate conductance components at both tTJs and bTJs. Additionally, lowering Ca²⁺ concentration in the bath facilitates tTJ disruption under hyperosmolality. Strengthening tTJ structure by overexpressing immunoglobulin-like domain-containing receptor 1 (ILDR1) protein abrogates the effect of hyperosmolality. We posit that osmotic stress physically disrupts tTJ structure, as evidenced by super-resolution microscopy. Findings from this study not only provide a high-resolution view of TJ structure and function, but also can inform current osmotherapy and drug delivery strategies for brain diseases.

Fig. 1. (a) Diagram of a hexagonal model of endothelial cell monolayer showing the organization of tricellular, bicellular junctions (tTJs, bTJs) and cell bodies (CBs). (b) Exemplified topography and corresponding conductance maps acquired by P-SICM on MDCKII cells. tTJs, bTJs and CBs can be identified in both images.

Fig. 2. P-SICM conductance maps of MDCKII cells before (a, c, e and g) and after (b, d, f and h) mannitol was introduced into basolateral side.

Fig. 3. (a) Validation of computer vision algorithms with P-SICM conductance map of model junctions on Si₃N₄ membrane created by FIB. (b) Line profiles drawn from red dash lines in conductance map and skeleton image of (a) respectively.

Fig. 4. Schematic of the algorithm automatically calculating averaged G value of individual tTJ region. (a) A P-SICM conductance map used as an example. (b) Skeleton image obtained by the algorithm from (a), with tTJ points highlighted. (c) Line profiles drawn along the dash lines in (b) from skeleton image and corresponding pixels of P-SICM conductance map.

Fig. 5. Schematic of the algorithm automatically calculating averaged G value of individual bTJ region. (a) A P-SICM conductance map used as example. (b) Skeleton image obtained from (a) with tTJ regions removed. (c) Line profiles drawn along the dash line in (b) from skeleton image and corresponding pixels of conductance map.

Fig. 6. Quantified local conductance change (ΔG) of CB, bTJ and tTJ regions after basolateral mannitol treatment, as calculated by the algorithm. (*p < 0.05, **p < 0.01, n = 6–8 for each condition).

Fig. 7. P-SICM conductance maps of MDCKII cells under low Ca²⁺ condition before (left) and after (right) 50 mM mannitol treatment.

Fig. 8. Topography and corresponding conductance maps of MDCKII-ILDR1 cells before (left) and after (right) 300 mM mannitol treatment.

Fig. 9. Effect of hyperosmolality on localization of (a) ZO-1 and tricellulin (Tric), (b) ZO-1 and claudin-2 (Cldn2). Scale bar in all images: 5 μm.