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

Optimized cDICE for Efficient Reconstitution of Biological Systems in Giant Unilamellar Vesicles
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优化的 cDICE 可有效重建巨型单层囊泡中的生物系统

DOI:
10.1101/2021.02.24.432456
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发表时间:
2021
影响因子:
4.7
通讯作者:
Kristina A. Ganzinger
Kristina A. Ganzinger
中科院分区:
生物学2区
文献类型:
--
作者:
Lori van de Cauter;F. Fanalista;Lennard van Buren;Nicola de Franceschi;Elisa Godino;Sharon Bouw;C. Danelon;C. Dekker;G. Koenderink;Kristina A. Ganzinger

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巨型单层囊泡(GUV)通常用于在重建实验中模拟生物膜。它们还广泛用于合成细胞的研究,因为它们提供了机械响应反应室,可以控制反应物与环境的交换。然而,虽然存在许多将功能生物分子封装在 GUV 中的方法,但没有一种通用的解决方案,可靠的 GUV 制造仍然是该领域的主要实验障碍。在这里,我们表明,通过优化称为连续液滴界面交叉封装(cDICE)的双乳液形成 GUV 方法,可以生成包含复杂生化系统的无缺陷 GUV。通过严格控制环境条件和调整油中脂质分散度,我们表明可以显着提高高质量 GUV 形成的再现性以及封装效率。我们展示了一系列最小系统的有效封装,包括最小肌动蛋白细胞骨架、膜锚定 DNA 纳米结构和功能性 PURE(使用重组元件的蛋白质合成)系统。我们优化的 cDICE 方法显示出成为生物物理学和自下而上合成生物学标准方法的巨大潜力。
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 minimal 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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