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QuantGUV: Quantifying Encapsulation Efficiency of Small Molecules in GUVs

Created on 24 Oct 2025

Authors

Marshall, Z., Bano, R., Dylan, P., Trifan, L., Mckeaveney, C., Gerber, A. P., Bae, W.

Abstract

Synthetic cells, constructed through the self-assembly of small molecules, are designed to mimic life-like behaviours by encapsulating functional molecules. For such synthetic cells to accurately replicate cellular reactions, it is critical that the concentrations of encapsulated molecules mirror those in living systems, as reaction kinetics and cellular network states are highly sensitive to these concentrations. However, methods for precisely determining encapsulation efficiency in synthetic cells at single cell resolution have been limited. To address this challenge, we developed QuantGUV, a software-driven, image-based analysis method that determines the concentrations of fluorescent molecules encapsulated within giant unilamellar vesicles (GUVs). We used QuantGUV to measure the encapsulation efficiencies of fluorescent molecules, ranging in size from 0.5 nm to 20 nm. These measurements were conducted on GUVs formed via the water-in-oil emulsion transfer method under various experimental conditions. Using QuantGUV, we have measured the encapsulation efficiencies of three fluorescence molecules, sulforhodamine B, mEGFP and polystyrene bead, in GUVs formed via the water-in-oil emulsion transfer method. The encapsulation efficiencies for polystyrene bead was close to 100 % in most of the conditions while sulforhodamine B and mEGFP's encapsulation efficiencies depended on the parameters during the GUV formation such as concentrations of lipids and oil-water ratio during the GUV formation. By providing crucial insights into encapsulation efficiencies, QuantGUV offers a valuable tool to monitor the building quantitative synthetic cell systems with accurately controlled internal environments which is a critical step towards the creation of synthetic cells.

Preprint server: bioRxiv
The authors list and abstract were imported from bioRxiv on 24 Oct 2025.

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