Center for Integrated Nanotechnologies, Sandia National Laboratories.
Center for Integrated Nanotechnologies, Sandia National Laboratories;
J Vis Exp. 2021 Jul 26(173). doi: 10.3791/60899.
Lipid nanotube (LNT) networks represent an in vitro model system for studying molecular transport and lipid biophysics with relevance to the ubiquitous lipid tubules found in eukaryotic cells. However, in vivo LNTs are highly non-equilibrium structures that require chemical energy and molecular motors to be assembled, maintained, and reorganized. Furthermore, the composition of in vivo LNTs is complex, comprising of multiple different lipid species. Typical methods to extrude LNTs are both time- and labor-intensive, and they require optical tweezers, microbeads, and micropipettes to forcibly pull nanotubes from giant lipid vesicles. Presented here is a protocol for the gliding motility assay (GMA), in which large scale LNT networks are rapidly generated from giant unilamellar vesicles (GUVs) using kinesin-powered microtubule motility. Using this method, LNT networks are formed from a wide array of lipid formulations that mimic the complexity of biological LNTs, making them increasingly useful for in vitro studies of lipid biophysics and membrane-associated transport. Additionally, this method is capable of reliably producing LNT networks in a short time (<30 min) using commonly used laboratory equipment. LNT network characteristics such as length, width, and lipid partitioning are also tunable by altering the lipid composition of the GUVs used for fabricating the networks.
脂质纳米管（LNT）网络代表了一种体外模型系统，可用于研究与真核细胞中普遍存在的脂质小管相关的分子运输和脂质生物物理学。然而，体内 LNTs 是高度非平衡的结构，需要化学能量和分子马达来组装、维持和重组。此外，体内 LNTs 的组成非常复杂，包含多种不同的脂质种类。典型的挤出 LNTs 的方法既费时又费力，需要使用光学镊子、微珠和微管来从巨大的脂质囊泡中强行拉出纳米管。本文介绍了一种滑行运动测定法（GMA）的方案，该方案使用动力蛋白驱动的微管运动，从巨大的单层囊泡（GUV）中快速生成大规模的 LNT 网络。使用这种方法，可以从模拟生物 LNTs 复杂性的各种脂质配方中形成 LNT 网络，使它们在体外脂质生物物理学和膜相关运输研究中越来越有用。此外，该方法使用常用的实验室设备，能够在短时间内（<30 分钟）可靠地产生 LNT 网络。通过改变用于制造网络的 GUV 的脂质组成，还可以调整 LNT 网络的长度、宽度和脂质分配等特征。
