Several proteins related to Alzheimer?s disease and other dementias are known to undergo liquid-liquid phase separation, a process that may be essential for their function. At the same time, such proteins are often known to form amyloid fibrils and deposits in the brains of patients suffering from those conditions. The molecular connection between these processes is unclear and may involve an intermediate gelation step. Illuminating the properties of gels in molecular detail has been difficult due to their viscous, dynamic and heterogeneous nature. Here, we propose to develop a solid-state nuclear magnetic resonance (NMR) approach that can characterize the transformations of such proteins from the droplet to the gel and amyloid states in the same sample and in real time. Our goal is to characterize the elusive interactions that build the gel networks and to capture the dramatic transformations that proteins must undergo from the intrinsically disordered state to the ?- sheet rich amyloid form. This information will be essential in understanding the relationship between normal protein function and disease and to develop effective therapies, diagnostic tools and interventions. We will test and optimize our approach with the fused in sarcoma (FUS) protein. FUS is associated with frontotemporal dementia (FTD) and amyotrophic lateral sclerosis (ALS) and has a well characterized phase separation behavior that includes the formation of liquid droplets, gels and amyloids. Using our approach, we aim to provide a molecular description of these transformations. Furthermore, we propose to use our strategy to evaluate the influence of biologically relevant components such as RNA on these processes. Our approach is easily adaptable to other dementia-related proteins and we envision that it will become a powerful molecular tool in illuminating protein behavior in health and disease.
Many proteins associated with Alzheimer?s disease and related dementias can form liquid droplets, gels and amyloid fibrils. Here, we develop a methodology that can be used to track how proteins change as they transform from one of those state to another. This information will be essential in connecting the normal function of the proteins with their pathological states and in the design of therapeutic agents that can modulate these transformations.
