Effects of system complexity on protein aggregation in neurodegeneration

Alzheimer's disease (AD) is a neurodegenerative disorder, the leading cause of dementia worldwide, and is one of the most pressing challenges in ageing societies. The disease is characterised by extensive brain atrophy, synaptic loss, and the accumulation of two types of protein aggregates: amyloid β (Aβ) plaques and tau neurofibrillary tangles. The deposition of Aβ can be causally linked to familial and early onset AD, however Aβ-targeting treatments against the more common sporadic form of the disease have so far shown limited to no efficacy. If early onset AD can be considered an autosomal dominant disease, sporadic AD is multi-factorial, and it might not have a unique cause. Indeed, the two largest risk factors for late-onset AD are not linked directly with Aβ processing: the first one being age and the second being the isoform APOE4 of the lipoprotein APOE—which is involved in lipid and cholesterol metabolism. In light of the high-dimensionality of this problem, in my thesis I will follow a bottom-up (biophysics to systems biology) approach in dealing with the influence of systemic complexity in protein aggregation across different components of cellular homoeostasis, in particular lipid membranes and the proteostasis network. In the first chapter of the thesis, I will present a selection of the scientific literature on AD, with a particular focus on systemic aspects, such as cellular networks of quality control, protein co-aggregation, and ageing. The second chapter will address the relationship between protein aggregation and the complexity of the lipid environment in which it occurs. This will be done by studying the aggregation of recombinant Aβ (rAβ) peptide in vitro in presence of model lipid membranes. After describing the theoretical foundations of the study of protein aggregation via means of chemical kinetics, I will show how different lipid species affect the aggregation kinetics of rAβ42 and highlight on how lipid-peptide interactions affect the ability to apply standard models of protein aggregation at the molecular scale. Then, I will present results demonstrating the acceleration of rAβ aggregation by cholesterol via a mechanism of heterogeneous primary nucleation. Finally, I will show the effect that mixtures of lipids of increasing complexity have on rAβ42 and introduce the concept of resilience in complexity—where complex lipid mixtures show an overall neutral kinetic contribution to amyloid aggregation and induce resistance to the onset of cooperative phenomena such as heterogeneous primary nucleation. The third chapter will analyse the role of a second critical component in protein aggregation: the proteostasis network. Combining mRNA and protein data from the turquoise killifish, an animal model for molecular ageing, with predictors of biophysical properties such as chaperon requirement for folding and intrinsic disorder, I will demonstrate strong links between the proteostasis network, protein stability, and protein aggregation upon ageing. In the final chapter, I will summarise and discuss some potential lines of research to expand and further generalise the work described in this thesis. AD is a complex disease, so adopting a systemic approach to the study of protein aggregation processes underlying its aetiology is of crucial importance from a conceptual point of view. Moreover, this framework has the potential to suggest network-wide therapeutic solutions for this and other neurodegenerative disorders.

Name dc:type.qualificationname

Doctor of Philosophy (PhD)

Level dc:type.qualificationlevel

Doctoral

Grantor dc:publisher.institution

University of Cambridge

Year dc:date.issued

2021

Author dc:creator

• Sanguanini, Michele

Advisor dc:contributor.advisor

• Vendruscolo, Michele

• ageing
• protein aggregation
• alzheimer's disease
• multiomics

Licence

• https://apollo8-f-pro.lib.cam.ac.uk/bitstreams/8dce8f2b-858b-46e4-b8ce-8a180d60c343/download
• https://creativecommons.org/licenses/by-nc/4.0/

Language dc:language

eng

Author Identifier

0000-0002-7142-3807

OAI identifier oai:identifier

oai:www.repository.cam.ac.uk:1810/324457