Exploring the potential of infrared spectroscopy in qualitative and quantitative monitoring of ovalbumin amyloid fibrillation

Abstract

Amyloid fibrils are highly ordered self-assembled (poly)peptide aggregates with cross-β structural pattern. Ovalbumin was used as a model for exploring the potential of infrared spectroscopy in detecting structural transitions and quantitative monitoring of amyloid fibrillation.

Low pH (pH 2) and high temperature (90 °C) over the course of 24 h were conditions applied for amyloid formation. Fibrillation of ovalbumin was monitored by ThT and ANS fluorescence, and SDS PAGE. A significant increase in ThT fluorescence with a plateau reached after 4 h of incubation, without the lag phase, was detected. Structural transitions leading to amyloid fibrillation were analysed using all three Amide regions in ATR-FTIR spectra. Significant changes were detected in Amide I and Amide III region (decrease of α-helix and increase of β-sheet peaks). To establish a fast, precise and simple method for quantitative monitoring of amyloid fibrillation, the Amide I/Amide II ratios of aggregation specific β-sheets (1625 and 1695 cm−1, respectively) with 1540 cm−1 as internal standard were used, resulting in good correlation (R2 = 0.93 and 0.95) with the data observed by monitoring ThT fluorescence. On the other hand, assessing aggregation specific β-sheet contents by self-deconvolution showed lower correlation with ThT fluorescence (R2 = 0.75 and 0.64).

Here we examined structural transitions during ovalbumin fibrillation in a qualitative and quantitative manner by exploiting the full potential of Amide regions simultaneously. Secondary structure distribution was monitored using second derivative spectra in Amide I region. A novel, simple mathematical calculation for quantitative monitoring of fibrils formation was presented employing that the increase in low and high frequency aggregation specific β-sheet in Amide I region compared to the internal standard in Amide II region is suitable for fibril formation monitoring.