2024 AIChE Annual Meeting

Modeling Stress Granule Dynamics: A Quantitative Biophysical Framework for Therapeutic Intervention in Neurodegenerative Diseases

Stress granules (SGs) are RNA-protein condensates that assemble in response to cellular stress and play a critical role in regulating mRNA triage during translational arrest. Aberrant SG dynamics have been implicated in neurodegenerative diseases such as Alzheimer’s and amyotrophic lateral sclerosis, where protein misfolding leads to chronic endoplasmic reticulum stress. Unlike normal SGs, which disassemble once stress is resolved, pathological SGs persist and disrupt normal cellular functions. Canonically, SGs form through a two-step liquid-liquid phase separation (LLPS) process: proteins like G3BP1, TIA1, and UBAPL2 bind mRNA transcripts to form core nucleating complexes, which interact with low-complexity domains of other RNA-binding proteins (RBPs) such as TDP43 and FUS to create a dynamic outer shell. As pathological SGs age under chronic stress, mutated TDP43 and FUS drive them toward a liquid-to-solid phase transition, forming amyloid fibrils. By gaining insights into and controlling pathological SG assembly dynamics, specifically targeting proteins involved in neurodegenerative diseases and disrupting their interaction landscape, we may prevent or reverse protein aggregation, potentially restoring normal cellular function and slowing disease progression. However, maturation and destabilization pathways of diseased-state SGs and their implications on material-function relations remain largely unexplored.

To address this knowledge gap, we develop a continuum model that interrogates the mechanisms governing SG assembly and disassembly. Our model describes the interaction between SG components with the Flory-Huggins theory and incorporates reaction kinetics that describes their binding and unbinding, including the case of pathological fibrillization. Together, the reaction-diffusion model allows us to simulate phase separation and transitions of SG systems and investigate how the process depends on key parameters, such as the chi parameter, which quantifies molecular binding affinities and interaction energies, along with the concentrations of participating proteins and ribonucleoprotein complexes. We aim to use this model to elucidate how system-level molecular interactions govern the formation and aging of SGs. For example, to probe disassembly mechanisms, we will introduce small molecules or chaperones into the multi-component SG systems to perturb phase behavior. By varying their concentrations and chi parameters, we aim to understand how these new species affect phase boundaries and disrupt protein aggregates. Our simulations will predict how the introduction of these molecules alters the binding interactions of other components, potentially restoring the system to a liquid-like phase that supports normal LLPS function. By developing quantitative models to uncover the fundamental mechanisms driving biological systems and disease, we can explore stress granules as a potential therapeutic target to prevent neurodegenerative disease pathology.