Protein aggregation plays an important role in biology and disease. For example, a variety of syndromes termed amyloid diseases involve the self-assembly of proteins into elongated amyloid fibers. A critical first step in understanding the forces that underlie these processes is to define which proteins can self-associate ? more specifically, to identify the sequence determinants of aggregation. This is not feasible with current methods, which are low-throughput and can only be used to study a very limited number of sequences. Furthermore, isolating the contribution of protein sequence independent from the surrounding cellular milieu requires measurement in biochemically defined conditions. We propose to develop a droplet microfluidics-based assay to measure protein aggregation. Droplet microfluidics is a technique that generates and manipulates picoliter- sized aqueous droplets, embedded in a stream of fluorinated oil that effectively isolates the droplets from one another. These droplets can be generated at a rate of up to 5000 hertz, and individual genes can be encapsulated in them, enabling the analysis of large libraries. We describe an approach to observe protein self-assembly in droplets and to sequence the genes that give rise to aggregation-prone peptides. We will apply this approach to two sequence libraries comprising variants of the Alzheimer?s associated protein, Tau. If successful, this system could be applied to identify other sequences that self-associate, or sequences or cofactors that modulate amyloid formation in a large variety of disease-associated proteins, as well as in other sorts of aggregation phenomena such as liquid-liquid phase separation.
Some proteins have the capacity to self-assemble into long fibrils, so-called ?amyloids,? that are associated with a variety of diseases. Our goal is to understand how the protein sequence specifies this capability. We are developing a high-throughput method, based on droplet microfluidics, to measure aggregation in diverse libraries of protein sequences, which provides fundamental information regarding processes that underlie many neurodegenerative diseases.
