Extracellular Vesicle Biology
Efficient intracellular delivery of macromolecular therapeutics remains a major barrier to the clinical translation of biologic modalities. The Liu Lab studies how extracellular vesicles (EVs) can be engineered to overcome these limitations and enable precise, functional delivery of proteins and nucleic acid–based cargos. Our work addresses key challenges in the field, including cargo loading efficiency, vesicle heterogeneity, and endosomal escape.
We have developed a programmable EV platform that enables active and selective cargo loading, reducing nonspecific encapsulation and improving functional delivery of proteins and ribonucleoprotein complexes for genome modification both in vitro and in vivo. Building on this foundation, we identified the Chandipura virus glycoprotein (CNV-G) as a potent inducer of EV biogenesis and intracellular cargo delivery. CNV-G expression robustly stimulates the production of plasma membrane–derived vesicles, termed gectosomes, which exhibit high yield, efficient cargo incorporation, and entry mechanisms distinct from classical vesicle systems such as VSV-G.
Comparative analyses reveal that CNV-G gectosomes display unique cellular tropism, receptor-independent uptake pathways, and differential sensitivity to pharmacological inhibitors. Functional studies demonstrate efficient cytosolic and nuclear delivery of diverse macromolecular cargos, resulting in measurable phenotypic and genomic changes in recipient cells. In vivo pharmacokinetic and biodistribution analyses further establish the capacity of gectosomes to deliver functional payloads to multiple tissues, including the nervous system.
Together, this work defines a virus-derived mechanism of EV biogenesis and establishes gectosomes as a versatile platform for intracellular delivery. Ongoing efforts in the lab focus on expanding the biological understanding of gectosome formation, tuning vesicle specificity and cargo control, and translating EV-based delivery strategies toward applications in disease modeling and therapeutic intervention.