Department of Mechanical and Aerospace Engineering, Princeton University, Princeton, New Jersey.
Department of Chemistry and Chemical Biology, Rutgers University, Piscataway, New Jersey.
Biophys J. 2024 Jun 4;123(11):1393-1403. doi: 10.1016/j.bpj.2023.09.018. Epub 2023 Oct 2.
There is growing evidence that biological condensates, which are also referred to as membraneless organelles, and liquid-liquid phase separation play critical roles regulating many important cellular processes. Understanding the roles these condensates play in biology is predicated on understanding the material properties of these complex substances. Recently, micropipette aspiration (MPA) has been proposed as a tool to assay the viscosity and surface tension of condensates. This tool allows the measurement of both material properties in one relatively simple experiment, in contrast to many other techniques that only provide one or a ratio of parameters. While this technique has been commonly used in the literature to determine the material properties of membrane-bound objects dating back decades, the model describing the dynamics of MPA for objects with an external membrane does not correctly capture the hydrodynamics of unbounded fluids, leading to a calibration parameter several orders of magnitude larger than predicted. In this work we derive a new model for MPA of biological condensates that does not require any calibration and is consistent with the hydrodynamics of the MPA geometry. We validate the predictions of this model by conducting MPA experiments on a standard silicone oil of known material properties and are able to predict the viscosity and surface tension using MPA. Finally, we reanalyze with this new model the MPA data presented in previous works for condensates formed from LAF-1 RGG domains.
越来越多的证据表明,生物凝聚物(也称为无膜细胞器)和液-液相分离在调节许多重要的细胞过程中起着关键作用。要了解这些凝聚物在生物学中的作用,就必须了解这些复杂物质的材料特性。最近,微量吸管抽吸(MPA)已被提议作为一种测定凝聚物粘度和表面张力的工具。与许多其他只能提供一个或一个参数比的技术相比,该工具允许在一个相对简单的实验中测量这两种材料特性。虽然这项技术在文献中已经被广泛用于确定几十年来具有膜结合物体的材料特性,但描述具有外部膜的物体的 MPA 动力学的模型并不能正确捕获无界流体的流体动力学,导致校准参数比预测值大几个数量级。在这项工作中,我们推导出了一个新的生物凝聚物 MPA 模型,该模型不需要任何校准,并且与 MPA 几何形状的流体动力学一致。我们通过对具有已知材料特性的标准硅油进行 MPA 实验来验证该模型的预测,并且能够使用 MPA 来预测粘度和表面张力。最后,我们使用这个新模型重新分析了之前关于 LAF-1 RGG 结构域形成的凝聚物的 MPA 数据。