Concentration dependence of alpha-synuclein fibril length assessed by quantitative atomic force microscopy and statistical-mechanical theory

M.E. van Raaij, Jeroen van Gestel, Gezina M.J. Segers-Nolten, Simon W. de Leeuw, Vinod Subramaniam

Research output: Contribution to journalArticleAcademicpeer-review

51 Citations (Scopus)
31 Downloads (Pure)

Abstract

The initial concentration of monomeric amyloidogenic proteins is a crucial factor in the in vitro formation of amyloid fibrils. We use quantitative atomic force microscopy to study the effect of the initial concentration of human α-synuclein on the mean length of mature α-synuclein fibrils, which are associated with Parkinson's disease. We determine that the critical initial concentration, below which low-molecular-weight species dominate and above which fibrils are the dominant species, lies at ∼15 μM, in good agreement with earlier measurements using biochemical methods. In the concentration regime where fibrils dominate, we find that their mean length increases with initial concentration. These results correspond well to the qualitative predictions of a recent statistical-mechanical model of amyloid fibril formation. In addition, good quantitative agreement of the statistical-mechanical model with the measured mean fibril length as a function of initial protein concentration, as well as with the fibril length distributions for several protein concentrations, is found for reasonable values of the relevant model parameters. The comparison between theory and experiment yields, for the first time to our knowledge, an estimate of the magnitude of the free energies associated with the intermolecular interactions that govern α-synuclein fibril formation.
Original languageEnglish
Pages (from-to)4871-4878
Number of pages8
JournalBiophysical journal
Volume95
Issue number10
DOIs
Publication statusPublished - 2008

Fingerprint Dive into the research topics of 'Concentration dependence of alpha-synuclein fibril length assessed by quantitative atomic force microscopy and statistical-mechanical theory'. Together they form a unique fingerprint.

Cite this