Collaborative Research: Computational Modeling of How Living Cells Utilize Liquid-Liquid Phase Separation to Organize Chemical Compartments

真核细胞已经进化出多种机制来隔离和维持局部的化学或分子浓度。最明显的是物理膜，例如将细胞质与其周围环境分开的细胞膜或将染色体DNA限制在细胞核内的核膜。区隔化机制是必不可少的，因为它们覆盖了浓度梯度的扩散平滑，否则会使细胞内容物均匀化，并且无法允许关键细胞过程的空间调节。细胞生物学最近发现的一个热点是在没有物理膜的情况下形成的化学隔室。本项目侧重于一个具体的例子：通过液-液相分离（LLPS）将细胞质蛋白质和rna结合成复合物，形成富含蛋白质的液滴。通过汇集数学、计算和生物科学家，研究人员的目标是开发一个通用的计算建模平台来研究由LLPS产生的细胞质液滴及其空间分布。目的是了解这些区室如何在活细胞中建立和保持mRNA定位和表达的细胞质异质性，以及与之相关的分子种类、复合物和动力学时间尺度。通过将该平台应用于其他活细胞，有可能了解LLPS的基本细胞特异性分子成分和化学动力学，从而有助于理解细胞生物学中细胞内区隔化的多样性。在细胞生物学中，膜的研究及其在建立细胞外和细胞内化学区室中的作用有着悠久的历史。然而，对于细胞质或细胞核内的分子蛋白、细胞器和染色体DNA如何在没有物理膜的情况下进行化学相互作用和自组织，以创造、维持和进化局部化学和大分子区室，人们知之甚少。有了基本分子物种和物种复合体确定的时空实验数据，本项目的研究人员将重点关注三个具体目标。1. 一个计算建模平台，用于探索初级分子（蛋白质、rna、蛋白质- rna复合物）和微观（核、膜）物种的输入空间、化学物种亲和力和空间限制条件。该平台将生成模拟活细胞数据（复合体和分子物种的动态自组织，液-液相分离导致的液滴形成）的结果相图，并揭示无膜细胞内化学隔室的足够成分和相互作用及其稳健性。2. 通过随机和连续耦合建模，以离体和体内实验数据为条件，发现足够的分子种类、复合物和隐藏的化学亲和力，再现活细胞的化学区隔化。3. 扩展多相建模的数值工具，以适应由化学动力学、液滴粘弹性和液-液分离诱导流动驱动的强波动和非平衡行为。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Eukaryotic cells have evolved multiple mechanisms for sequestering and maintaining localized chemical or molecular concentrations. The most obvious is a physical membrane, such as the cell membrane that separates the cytoplasm from its surrounding environment or the nuclear membrane that confines chromosomal DNA within the nucleus. Mechanisms for compartmentalization are essential as they override diffusive smoothing of concentration gradients that would otherwise homogenize cellular contents and fail to allow spatial regulation of critical cellular processes. A recently identified and current intense focus in cell biology is on chemical compartments that form in the absence of physical membranes. This project focuses on a specific example: the binding of cytoplasmic proteins and RNAs into complexes that form protein-rich droplets by way of liquid-liquid phase separation (LLPS). By bringing together mathematical, computational, and biological scientists, the investigators aim to develop a general computational modeling platform to study cytoplasmic droplets and their spatial distributions that arise from LLPS. The aim is to understand mechanistically how these compartments establish and preserve cytoplasmic heterogeneity in mRNA localization and expression in live cells, and the molecular species, complexes, and kinetic timescales that are responsible. By applications of this platform to other live cells, there is the potential to understand the essential cell-specific molecular ingredients and chemical kinetics for LLPS, thereby contributing to understanding of the diversity of intracellular compartmentalization across cell biology. There is a rich history in cell biology of the study of membranes and their role in establishing extracellular and intracellular chemical compartments. Yet, relatively little is known about how molecular proteins, organelles, and chromosomal DNA, within the cytoplasm or within the nucleus, chemically interact and self-organize to create, sustain, and evolve localized chemical and macromolecular compartments in the absence of physical membranes. Armed with resolved spatial and temporal experimental data of primary molecular species and species complexes, the investigators in this project focus on three specific aims. 1. A computational modeling platform to explore the input space of primary molecular (proteins, RNAs, protein-RNA complexes) and microscopic (nuclei, membranes) species, chemical species affinities, and spatial confinement conditions. This platform will produce a phase diagram of outcomes that mimics live cell data (dynamic self-organization of complexes and molecular species, droplet formation due to liquid-liquid phase separation), and that reveals sufficient ingredients and interactions for membrane-less, intracellular chemical compartments, and their robustness. 2. By way of coupled stochastic and continuum modeling, conditioning on ex vivo and in vivo experimental data, to discover sufficient molecular species, complexes, and hidden chemical affinities that reproduce the chemical compartmentalization of live cells. 3. To extend numerical tools for multiphase modeling to accommodate strong fluctuations and out-of-equilibrium behavior driven by chemical kinetics, viscoelasticity of droplets, and induced flow by liquid-liquid phase separation.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.