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Optimized cDICE for Efficient Reconstitution of Biological Systems in Giant Unilamellar Vesicles. | LitMetric

AI Article Synopsis

  • Giant unilamellar vesicles (GUVs) are valuable in simulating biological membranes and studying synthetic cells, but creating reliable GUVs has been challenging due to the lack of a universal fabrication method.
  • The study introduces an optimized method called continuous droplet interface crossing encapsulation (cDICE), which greatly enhances the quality and reproducibility of GUVs by carefully controlling environmental factors and lipid dispersion.
  • The improved cDICE method successfully encapsulates various biochemical systems, including an actin cytoskeleton and a functional protein synthesis system, indicating its potential as a standard technique in biophysics and synthetic biology research.

Article Abstract

Giant unilamellar vesicles (GUVs) are often used to mimic biological membranes in reconstitution experiments. They are also widely used in research on synthetic cells, as they provide a mechanically responsive reaction compartment that allows for controlled exchange of reactants with the environment. However, while many methods exist to encapsulate functional biomolecules in GUVs, there is no one-size-fits-all solution and reliable GUV fabrication still remains a major experimental hurdle in the field. Here, we show that defect-free GUVs containing complex biochemical systems can be generated by optimizing a double-emulsion method for GUV formation called continuous droplet interface crossing encapsulation (cDICE). By tightly controlling environmental conditions and tuning the lipid-in-oil dispersion, we show that it is possible to significantly improve the reproducibility of high-quality GUV formation as well as the encapsulation efficiency. We demonstrate efficient encapsulation for a range of biological systems including a minimal actin cytoskeleton, membrane-anchored DNA nanostructures, and a functional PURE (protein synthesis using recombinant elements) system. Our optimized cDICE method displays promising potential to become a standard method in biophysics and bottom-up synthetic biology.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8291763PMC
http://dx.doi.org/10.1021/acssynbio.1c00068DOI Listing

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