Proteolytic Digestion and TiO2 Phosphopeptide Enrichment Microreactor for Fast MS Identification of Proteins

Autor: Jingren Deng, Iulia M. Lazar
Rok vydání: 2016
Předmět:
Zdroj: Journal of the American Society for Mass Spectrometry. 27:686-698
ISSN: 1044-0305
DOI: 10.1007/s13361-015-1332-6
Popis: The characterization of phosphorylation state(s) of a protein is best accomplished by using isolated or enriched phosphoprotein samples or their corresponding phosphopeptides. The process is typically time-consuming as, often, a combination of analytical approaches must be used. To facilitate throughput in the study of phosphoproteins, a microreactor that enables a novel strategy for performing fast proteolytic digestion and selective phosphopeptide enrichment was developed. The microreactor was fabricated using 100 μm i.d. fused-silica capillaries packed with 1-2 mm beds of C18 and/or TiO2 particles. Proteolytic digestion-only, phosphopeptide enrichment-only, and sequential proteolytic digestion/phosphopeptide enrichment microreactors were developed and tested with standard protein mixtures. The protein samples were adsorbed on the C18 particles, quickly digested with a proteolytic enzyme infused over the adsorbed proteins, and further eluted onto the TiO2 microreactor for enrichment in phosphopeptides. A number of parameters were optimized to speed up the digestion and enrichments processes, including microreactor dimensions, sample concentrations, digestion time, flow rates, buffer compositions, and pH. The effective time for the steps of proteolytic digestion and enrichment was less than 5 min. For simple samples, such as standard protein mixtures, this approach provided equivalent or better results than conventional bench-top methods, in terms of both enzymatic digestion and selectivity. Analysis times and reagent costs were reduced ~10- to 15-fold. Preliminary analysis of cell extracts and recombinant proteins indicated the feasibility of integration of these microreactors in more advanced workflows amenable for handling real-world biological samples. Graphical Abstract ᅟ.
Databáze: OpenAIRE