Electrophoretic focusing in microchannels combined with mass spectrometry Applications on amyloid beta peptides

Analysis of low-abundance components in small samples remains a challenge within bioanalytical chemistry, and new techniques for sample pretreatments followed by sensitive and informative detection are required. In this thesis, procedures for preconcentration and separation of proteins and peptides in open microchannels fabricated on silicon microchips are presented. Analyte electromigration was induced by applying a voltage along the channel length, and detection was performed either by matrix-assisted laser desorption ionization mass spectrometry (MALDI-MS) within the open channel, or by sampling a nL fraction containing the preconcentrated analytes from the channel for subsequent nano-electrospray ionization(nESI-) or MALDI-MS. Utilizing solvent evaporation from the open system during sample supply, sample volumes exceeding the 25-75 nL channel volume could be analyzed. For preconcentration/separation of components in the discrete channel volume a lid of inert fluorocarbon liquid was used for evaporation control. In Papers I and II, aqueous, carrier-free solutions of proteins and peptides were analyzed, and the method was successfully applied for fast and simple preconcentration of amyloid beta (Aβ) peptides, related to Alzheimer’s disease. The impact of possible impurities in the analysis of carrier-free solutions was investigated in Paper III with the 1D simulation software GENTRANS, and a method for open-channel isoelectric focusing in a tailor-made pH gradient was developed. The latter approach was used in Paper IV for preconcentration and purification of Aβ peptides after immunoprecipitation from cerebrospinal fluid and blood plasma, followed by MALDI-MS from a micropillar chip. Paper V includes simulations of an isotachophoretic strategy for selective enrichment of Aβ peptides. GENTRANS simulations were used to select the electrolyte composition, and 2D simulations in a geometry suitable for on-chip implementation were performed using COMSOL Multiphysics.