Mechanobiological modulation of blood-brain barrier permeability by laser stimulation of endothelial-targeted nanoparticles

Xiaoqing Li, Qi Cai, Blake A. Wilson, Hanwen Fan, Harsh Dave, Monica Giannotta, Robert Bachoo, Zhenpeng Qin

Research output: Contribution to journalArticlepeer-review


The blood-brain barrier (BBB) maintains an optimal environment for brain homeostasis but excludes most therapeutics from entering the brain. Strategies that reversibly increase BBB permeability are essential for treating brain diseases and are the focus of significant preclinical and translational interest. Picosecond laser excitation of tight junction-targeted gold nanoparticles (AuNPs) generates a nanoscale mechanical perturbation and induces a graded and reversible increase in BBB permeability (OptoBBB). Here we advanced this technique by showing that targeting endothelial glycoproteins leads to >10-fold higher targeting efficiency than targeting tight junctions both in vitro and in vivo. With both tight-junction and glycoprotein targeting, we demonstrate that OptoBBB is associated with a transient elevation and propagation of Ca2+, actin polymerization, and phosphorylation of ERK1/2 (extracellular signal-regulated protein kinase). These collectively activate the cytoskeleton resulting in increased paracellular permeability. The Ca2+ response involves internal Ca2+ depletion and Ca2+ influx with contributions from mechanosensitive ion channels (TRPV4, Piezo1). We provide insight into how the excitation of tight junction protein (JAM-A)-targeted and endothelial (glycocalyx)-targeted AuNPs leads to similar mechanobiological modulation of BBB permeability while targeting the glycocalyx significantly improves the nanoparticle accumulation in the brain. The results will be critical for guiding the future development of this technology for brain disease treatment.

Original languageEnglish (US)
Pages (from-to)3387-3397
Number of pages11
Issue number7
StatePublished - Jan 17 2023

ASJC Scopus subject areas

  • Materials Science(all)


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