Unzipping the Polyglutamine Steric Zipper Using High Throughput Flow Cytometry

Kandola, Tejbir Singh (2021). Unzipping the Polyglutamine Steric Zipper Using High Throughput Flow Cytometry. PhD thesis The Open University.

DOI: https://doi.org/10.21954/ou.ro.0001364f

Abstract

The transition of soluble proteins into insoluble aggregates underlies many neurodegenerative disorders. While disorders vary with respect to age of onset, disease phenotype, prognosis and the identity of the involved proteins, the irreversible transition to a thermodynamically stable amyloid state has been strongly implicated in all of them. Amyloids have been studied for over 160 years and much work has gone into the study of amyloid morphology and assembly. Despite extensive experimentation, information regarding the structures of amyloid nuclei, and therefore the initiation of amyloid formation and therefore the defining event underlying many neurodegenerative diseases, has eluded researchers. Biophysical models show that, in fact, the direct visualization of the high-energy, transient amyloid nucleus would be predicted to be incredibly difficult if not impossible. Additionally, due to the lack of sequence complexity in many of these peptides, bioinformatic prediction of amyloidogenic proteins or regions is exceedingly error prone. At the extreme of this lack of sequence complexity is the polyglutamine expansion underlying Huntingtin’s Disease (HD). We utilized a high-throughput cytometric platform for the analysis of amyloid nucleation barriers in living cells to systematically dissect the nucleus of polyglutamine expansions. We probed how geometry relating to the primary structure of the polypeptide could affect the transition of these disordered regions by introducing amino acids at regular spacings. Using rational mutagenesis, we found that simple rules relating to glutamine spacing had predictable results on amyloid nucleation. These results supported molecular dynamics free energy simulations of rationally designed nuclei. These results provide more context for the prediction of potential amyloidogenic proteins which could be implicated in disease.

Viewing alternatives

Look up in Google Scholar

Download history

Metrics

Public Attention

Altmetrics from Altmetric

Number of Citations

Citations from Dimensions

Item Actions

Export

About

CORE (COnnecting REpositories)

Recommendations