High-speed imaging of giant unilamellar vesicle production in cDICE.

Abstract

Giant unilamellar vesicles (GUVs) are cell-sized containers that are commonly used as three-dimensional model membranes in biophysics, as in vitro model systems in synthetic biology, and even as cargo carriers in various other research fields. Despite their ubiquitous use, there is still no one-size-fits-all GUV production method. Over the years, numerous methods have been developed, attempting to meet the demanding requirements of robustness, reliability, and high yield while simultaneously achieving robust encapsulation. Double emulsion-based methods are often praised for their apparent simplicity and good yields; hence, methods like continuous droplet interface crossing encapsulation (cDICE) that make use of this principle, have gained popularity in recent years. In cDICE, aqueous droplets that originate from a capillary orifice are continuously forced through an oil-water interface by centrifugal force, thereby forming a lipid bilayer and thus GUVs. Although cDICE and related methods are frequently used in the field, the complexity of the underlying principles and fluid dynamics has not been considered previously, and how exactly the GUVs are being formed remains unknown. To elucidate the process of GUV formation in cDICE, we have developed a high-speed microscopy setup that allows us to visualize GUV formation in real time. We focused on the capillary orifice, where initial droplet formation occurs, and on the oil-water interface, where droplets are converted into GUVs. Our experiments reveal a complex droplet formation process at the capillary orifice and suboptimal droplet transfer through the water-oil interface, which we explain using fluid dynamics and theoretical modeling. Our results are a first step towards explaining the widely observed variation in encapsulation efficiency and size polydispersity in cDICE. Ultimately, these results will contribute to a better understanding of GUV formation processes in cDICE and in extension, in double emulsion-based methods in general.