Dynamic Range Expansion Applied to Mass Spectrometry Based on Data-Dependent Selective Ion Ejection in Capillary Liquid Chromatography Fourier Transform Ion Cyclotron Resonance for Enhanced Proteome Characterization
The characterization of cellular proteomes is important for understanding biochemical processes ranging from cell differentiation to cancer development. In one highly promising approach, whole protein extracts or fractions are digested (e.g., with trypsin) and injected into a packed capillary column...
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Published in: | Analytical chemistry (Washington) Vol. 73; no. 21; pp. 5052 - 5060 |
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Main Authors: | , , , , , , |
Format: | Journal Article |
Language: | English |
Published: |
Washington, DC
American Chemical Society
01-11-2001
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Subjects: | |
Online Access: | Get full text |
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Summary: | The characterization of cellular proteomes is important for understanding biochemical processes ranging from cell differentiation to cancer development. In one highly promising approach, whole protein extracts or fractions are digested (e.g., with trypsin) and injected into a packed capillary column for subsequent separation. The separated peptides are then introduced on-line to an electrospray ionization source of a Fourier transform ion cyclotron resonance (FTICR) mass spectrometer for the detection of peptide accurate mass tags that serve as biomarkers for their parent proteins. In this work, we report the use of data-dependent selective external ion ejection in conjunction with FTICR and on-line capillary LC separations for the enhanced characterization of peptide mixtures and a yeast extract proteome. The number of peptides identified in an LC-FTICR analysis of a yeast proteome digest employing data-dependent rf-only dipolar ejection of the most abundant ion species prior to ion accumulation was 40% higher than that detected in a separate LC-FTICR analysis using conventional nonselective ion accumulation. |
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Bibliography: | istex:5EEA8C7CED145F8412D02E21D5C99665BE44F1B3 ark:/67375/TPS-837LZ7QJ-K ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
ISSN: | 0003-2700 1520-6882 |
DOI: | 10.1021/ac010733h |