Protein aggregation

The study of the mechanisms of protein aggregation is of central importance to understanding fundamental biological processes such as protein assembly and turnover, as well as pathologies that are characterised by the presence of protein aggregates - such as Parkinson’s and Alzheimer’s diseases.

With the latter there is in fact a relatively short list of proteins or peptides the aggregation of which is linked to diseases, including the following examples.

Disease Proteins or peptides found in aggregates Further reading
Alzheimer’s disease Aβ peptide and hyperphosphorylated tau Haass and Selkoe Nature Reviews Mol Cell Bio 2007
Parkinson’s disease ɑ-Synuclein Stefanis CSH Perspectives in Medicine 2012
Huntington’s disease Huntingtin with polyglutamine expansion Bates Lancet 2003
Other polyglutamine diseases (DRPLA, SCA1-3) Atrophin-1, ataxins or AR Shao & Diamond Hum Mol Genet 2007  
Fronto-temporal dementia with Parkinsonism Hyperphosphorylated tau protein D’Souza et al PNAS 1999
Amyotophic lateral sclerosis (ALS) TDP-43 (TAR DNA binding protein of 43kDa) and FUS (Fused in Sarcoma, an RNA binding protein) Neumann et al Science 2006
Prion diseases (kuru, Creutzfeldt-Jakob disease etc) Prion protein Aguzzi & Heikenwalder Nat Rev Microbiol 2006

A great deal remains to be understood concerning the mechanisms of formation and nature of these pathological protein aggregates. However, probing such aggregates can be challenging because of their supramolecular nature, their heterogeneity, and their often dynamic nature.

One common experimental approach for monitoring aggregates is the use of the Thioflavin-T (ThT) assay. ThT fluorescence is enhanced upon binding to beta-sheet rich structures such as amyloid fibrils. However, this interaction is not perfectly specific, with some evidence suggesting that ThT fluorescence can occur following binding to monomers or oligomers (Groenning, Journal of Chemical Biology 2010). There is also the possibility that the ThT label that binds the beta-sheets of the fibril throughout the experiment may affect the behaviour of the protein during measurement. Finally, some amyloid fibrils are not detected by ThT fluorescence and can provide false negative results - for example if the fibrils are packed in a way that the surface for ThT binding is not present (Nilsson, Methods 2004) .

The Fluidity One addresses these problems by measuring the size of aggregates as they form in a label independent manner, either through the measurement of changes in size, or through changes in observed concentration when aggregation prevents labelling by amine reactive dye.

Case Study: Assessment of α-synuclein amyloid fibril growth

α-Synuclein is an abundantly expressed neuronal protein that contributes to a host of neurological conditions characterised by Lewy body formations, including Parkinson’s disease and dementia. α-Synuclein aggregation results in insoluble, beta-sheet rich amyloid fibrils, the growth of which is of key interest in studying the development of these diseases. 

Comparison of Fluidity One (using changes in concentration as the readout) and ThT Spectroscopy found that measurement of α-Synuclein fibril growth is highly comparable between the two approaches.

Assessment of α-synuclein amyloid fibril growth (figure 1)
Figure 1: Comparison of α-synuclein fibril growth as measured by MDS and ThT Spectroscopy at pH 5.6 and pH 6.5 A 100µm α-synuclein monomer solution was prepared in 20mM MES at pH 5.6 (80µL) and aggregation was seeded by addition of 10 µL of sonicated α-synuclein fibrils. 10 µL of 300 µm ThT was also added for a final concentration of 80 µm α-synuclein monomer in 16 mM MES buffer pH 5.6. The resulting mix was transferred to a 96 well plate in a single 100 µL aliquot and the ThT fluorescence of the plate was measured over a time course of 1400 minutes (red curve in Panels 1 and 2). A second identical solution was prepared in parallel replacing the ThT with 10 µL of MilliQ water. 3 µL aliquots of this solution were diluted to 6 µL with 20 mM MES immediately before loading on a Fluidity MDS Chip. Fourteen repeat measurements were taken over five hours with a final reading taken at 1400 minutes (Panel 1). This experiment was repeated with 20 mM PB buffer at pH 6.5 in place of 20 mM MES with all other variables maintained between experiments (Panel 2). The second to last measurement in PB buffer was taken after six hours. The data points from these measurements were used to generate the exponential fit present in both panels.

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The Fluidity One

In-solution sizing and quantification of native protein in less than 10 minutes