4.7 Article

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

期刊

ACS SYNTHETIC BIOLOGY
卷 10, 期 7, 页码 1690-1702

出版社

AMER CHEMICAL SOC
DOI: 10.1021/acssynbio.1c00068

关键词

bottom-up synthetic biology; GUVs; emulsion transfer; synthetic cell; actin cytoskeleton; in vitro transcription-translation

资金

  1. Netherlands Ministry of Education, Culture and Science (OCW) [024.003.019]
  2. Netherlands Organization for Scientific Research (NWO) [024.003.019]
  3. NWO-WISE funding

向作者/读者索取更多资源

Optimizing the continuous droplet interface crossing encapsulation (cDICE) method can produce defect-free GUVs, significantly improving reproducibility and encapsulation efficiency for various biological systems.
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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