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

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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.