Analytical technology and methods for proteome analysis using chromatographic media for protein capture and digestion.

摘要

Mass spectrometry (MS) has been the method of choice for protein identification and characterization for the past several years. Currently, numerous research efforts are focused on proteome analysis. The proteome is defined as the set of proteins being expressed in a cell, tissue, or organism under defined conditions at a specific time, and may consist of several thousand proteins. Therefore, the demand for rapid analysis has recently increased. Mass spectrometers are capable of generating data quickly and thus have a great potential for high-throughput analysis.; In this work a new technology has been developed for protein identification using mass spectrometry that incorporates sample cleanup, preconcentration, and protein digestion in a single-stage system. The procedure involves the adsorption of a protein, or protein mixture, from solution onto a hydrophobic media that is contained within a microcolumn. The protein is digested while still bound to the hydrophobic support. The method is demonstrated with standard protein samples at concentrations down to 10 nM. Real world samples, as well as hydrophobic proteins, are also successfully digested on the hydrophobic media and detected by mass spectrometry. Peptide fragments, generated from digestion of standard protein samples bound to various types of micro-bead surfaces, were examined to determine the effects of surface chemistry and surface morphology on the digestion process. It is demonstrated that digesting proteins on various types of hydrophobic surfaces produce peptide mass fingerprints with only minor differences.; Finally, this technology is adapted to directly couple the surface digestion procedure with mass spectrometric detection. The entire system is fully automated and optimization for high throughput analysis. Proteins extracted from E. coli cells were used to demonstrate the power of this novel technology. The methods and system described in this thesis provide reliable protein identification capable of high-throughput analysis. This technology offers a potential solution for high throughput proteome analysis.