Surface Adsorbed Antibody Characterization Using ToF-SIMS with Principal Component Analysis and Artificial Neural Networks

Artificial neural networks (ANNs) form a class of powerful multivariate analysis techniques, yet their routine use in the surface analysis community is limited. Principal component analysis (PCA) is more commonly employed to reduce the dimensionality of large data sets and highlight key characteristics. Herein, we discuss the strengths and weaknesses of PCA and ANNs as methods for investigation and interpretation of a complex multivariate sample set. Using time-of-flight secondary ion mass spectrometry (ToF-SIMS) we acquired spectra from an antibody and its proteolysis fragments with three primary-ion sources to obtain a panel of 72 spectra and a characteristic peak list of 775 fragment ions. We describe the use of ANNs as a means to interpret the ToF-SIMS spectral data, highlight the optimal neural network design and computational parameters, and discuss the technique limitations. Further, employing Bi₃⁺ as the primary-ion source, ANNs can accurately classify antibody fragments from the parent antibody based on ToF-SIMS spectra

ToF-SIMS and Principal Component Analysis Investigation of Denatured, Surface-Adsorbed Antibodies

Antibody denaturation at solid–liquid interfaces plays an important role in the sensitivity of protein assays such as enzyme-linked immunosorbent assays (ELISAs). Surface immobilized antibodies must maintain their native state, with their antigen binding (Fab) region intact, to capture antigens from biological samples and permit disease detection. In this work, two identical sample sets were prepared with whole antibody IgG, F­(ab′)₂ and Fc fragments, immobilized to either a silicon wafer or a diethylene glycol dimethyl ether plasma polymer surface. Analysis was conducted on one sample set at day 0, and the second sample set after 14 days in vacuum, with time-of-flight secondary ion mass spectrometry (ToF-SIMS) for molecular species representative of denaturation. A 1003 mass fragment peak list was compiled from ToF-SIMS data and compared to a 35 amino acid mass fragment peak list using principal component analysis. Several ToF-SIMS secondary ions, pertaining to disulfide and thiol species, were identified in the 14 day (presumably denatured) samples. A substrate and primary ion independent marker for denaturation (aging) was then produced using a ratio of mass peak intensities according to denaturation ratio: [<i>I</i>_61.9534 + <i>I</i>_62.9846 + <i>I</i>_122.9547 + <i>I</i>_84.9609 + <i>I</i>_120.9461]/[<i>I</i>_30.9979 + <i>I</i>_42.9991 + <i>I</i>_73.0660 + <i>I</i>_147.0780]. The ratio successfully identifies denaturation on both the silicon and plasma polymer substrates and for spectra generated with Mn⁺, Bi⁺, and Bi₃⁺ primary ions. We believe this ratio could be employed to as a marker of denaturation of antibodies on a plethora of substrates