Clumping of protein molecules in a process called 'aggregation' is a common problem in cellular biology. One kind of protein aggregation leads to a specific structure of the clumps called 'amyloids' and is thought to play a key role in many neurodegenerative diseases including Alzheimer's disease. Recently, protein amyloids have also been associated with normal cellular functions. A wide variety of aggregate structures are formed during aggregation, and many of these cause a specific biological response. Hence, understanding the mechanisms of aggregation is critical for human health. Amyloid formation is influenced by biological surfactant molecules, which associate many amyloid proteins. In the proposed project, the principal investigator along with a team of collaborators will use experiments, computer simulations, and mathematical analysis to understand how surfactants modulate amyloid protein aggregation to form specific aggregate species. This will transform our understanding of these interactions which play a role in Alzheimer's disease. This scientific endeavor will also involve many students, who will not only learn new areas of research but will also contribute towards data collection and interpretation of results.
Self-association of a protein called amyloid beta, associated with Alzheimer's disease, involves the conversion from its intrinsically disordered, monomeric form to well-organized, fibrillar structures in a nucleation-dependent manner. Among the aggregates formed, the low-molecular weight oligomers have emerged to be physiologically important species. The oligomers formed need not be the obligate intermediates of the fibril formation pathway, and they could be formed along alternate 'off-pathways', which result in many distinct structural strains of amyloid beta. Many factors can induce off-pathway products. Among these factors, interfaces generated by biological surfactants (SAs) are physiologically relevant due to their perpetual association with amyloid beta. Recent findings from the principle investigator's lab indicate that non-esterified fatty acid SAs induce off- or on- pathway aggregates in a concentration dependent manner. The investigators hypothesize that concentration-dependent phase transitions of SAs modulate amyloid beta aggregation pathways to generate distinct oligomers. In this work, a collaborative team will test the hypothesis with two specific aims: Aim 1 will investigate biophysically the interactions between amyloid beta and SAs using a variety of anionic SAs, and Aim 2 will model temporal evolution of oligomers as a result of amyloid beta-SA interactions using numerical simulations and reduced order mathematical analysis. An interdisciplinary approach involving experimental biophysics, simulation and mathematical analysis with a synergistic feedback between the experiments (Aim 1) and simulations (Aim 2) will provide insights into the heterotypic interactions between amyloid beta and SAs and will bridge the existing knowledge gap in the field. Considering that the functional effects of off-pathway aggregates are related to their respective morphologies, understanding the physiochemical properties of amyloid beta-SA interactions will be of paramount significance in deciphering amyloid-related cellular processes. This work will also help in a better understanding of aggregation pathways in a larger, more complex network of reactions involving amyloids, which can then be utilized to design intervention strategies in the future. The proposed project will have broader impacts on science and education for undergraduate and graduate students from the three institutions of University of Southern Mississippi (USM), Virginia Commonwealth University (VCU), and Montclair State University (MSU) spanning the areas of molecular biophysics, computational systems biology and mathematical biology respectively.
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.
|Effective start/end date||10/1/16 → 7/31/22|