Multiple particle tracking using PEGylated nanoparticles reveals lymph node is riddled with heterogeneous pores smaller than reported and interstitial tissue material properties vary by lymph node location

Abstract

Lymph nodes (LNs) are highly structured lymphoid organs that compartmentalize B and T cells in the outer cortex and inner paracortex, respectively, and are supported by a collagen-rich reticular network. Tissue material properties like viscoelasticity and diffusion of materials within extracellular spaces and their implications on cellular behavior and therapeutic delivery have been a recent topic of investigation. Here, we developed a nanoparticle system to investigate the rheological properties, including pore size and viscoelasticity, through multiple particle tracking (MPT) combined with LN slice cultures. Dense coatings with polyethylene glycol (PEG) allow nanoparticles to diffuse within the LN extracellular spaces. Despite differences in function in B and T cell zones, we found that extracellular tissue properties and mesh spacing do not change significantly in the cortex and paracortex, though nanoparticle diffusion was slightly reduced in B cell zones. Interestingly, our data suggest that LN pore sizes are smaller than the previously predicted 10 - 20 m, with pore sizes ranging from 500 nm - 1.5 m. Our studies also confirm that LNs exhibit viscoelastic properties, with an initial solid-like response followed by stress-relaxation at higher frequencies. Finally, we found that nanoparticle diffusion is dependent on LN location, with nanoparticles in skin draining LNs exhibiting a higher diffusion coefficient and pore size compared to mesenteric LNs. Our data shed new light onto LN interstitial tissue properties, pore size, and define surface chemistry parameters required for nanoparticles to diffuse within LN interstitium. Our studies also provide both a tool for studying LN interstitium and developing design criteria for nanoparticles targeting LN interstitial spaces. AbbreviationsLNs, FBS, EDC, NHS, ECM, PEG