The structural evaluation of amyloid beta on lipid membranes

Abstract

Amyloid beta (Aβ) adsorption onto lipid membranes depending on the condition of a lipid was investigated by means of time-offlight secondary ion mass spectrometry (ToF-SIMS). Aβ aggregation depending on the different hardness of lipid membrane has not been clarified yet although it is important to understand Alzheimer's disease. Aβ (1-40) on three different lipid membranes having different transition temperatures has been evaluated using ToF-SIMS in the previous study, and in this study, the differences between Aβ on liquid crystalline-phase lipid membranes and that on gel-phase lipid membranes were investigated in order to clarify the mechanisms of aggregation and peptide folding change. ToF-SIMS secondary ion images clearly showed Aβ distribution on lipid membranes. Because ToF-SIMS data is extremely complicated although it contains rich information, it was analysed by principal component analysis (PCA). Score images indicated by PCA are consistent with the images of secondary ions related to Aβ and are clearer than the secondary ion images. Moreover, PCA results suggest the difference between Aβ on different lipid membranes in terms of amino acid fragment ions, and the orientation of Aβ on 1,2-dipalmitoyl-sn-glycero-3-phosphocholine was indicated.

Two-Dimensional and Three-Dimensional Time-of-Flight Secondary Ion Mass Spectrometry Image Feature Extraction Using a Spatially Aware Convolutional Autoencoder

“…This can be used alone, or as an initial dimensionality reduction step in a larger data analysis pipeline. Matrix factorization (MF) techniques, such as principal component analysis (PCA), multivariate curve resolution, maximum autocorrelation factors (MAF), and non-negative matrix factorization (NMF), are the main methods of dimensionality reduction for ToF-SIMS images. − ,− …”