Synthetic Membraneless Droplets for Synaptic-Like Clustering of Lipid Vesicles

Area of Science:

• Cell Biology
• Biophysics
• Materials Science

Background:

• Membraneless organelles (MLOs) in eukaryotic cells interact with membranous organelles (MOs), often by clustering them.
• Synapsin-rich MLOs cluster synaptic vesicles at nerve terminals, a key process in neuronal function.
• Existing aqueous droplet mimics like coacervates and aqueous two-phase systems cannot effectively cluster lipid vesicles.

Purpose of the Study:

• To develop a synthetic droplet system capable of clustering lipid vesicles, mimicking MLO functions.
• To investigate the role of combined associative and segregative interactions in droplet formation and lipid vesicle clustering.
• To create a novel MLO mimic for studying cellular dynamics and synaptic vesicle organization.

Main Methods:

• Development of segregative-associative (SA) droplets by combining associative and segregative interaction principles.
• Utilizing SA droplets to cluster and disperse lipid vesicles (LVs).
• Characterizing the interaction environment within SA droplets, focusing on electrostatic interactions.

Main Results:

• SA droplets were successfully assembled by integrating segregative and associative interactions.
• SA droplets demonstrated the ability to cluster and disperse lipid vesicles, similar to synapsin condensates.
• The clustering of LVs by SA droplets was attributed to the specific weak electrostatic interaction environment they provide.

Conclusions:

• Combined segregative and associative interactions offer a viable strategy for creating MLO-mimicking droplets.
• SA droplets serve as effective mimics for studying synaptic clustering of lipid vesicles.
• This work introduces SA droplets as valuable models for exploring and replicating cellular dynamics related to MLOs and MOs.