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Updated: Mar 14, 2026

Deep Proteome Profiling by Isobaric Labeling, Extensive Liquid Chromatography, Mass Spectrometry, and Software-assisted Quantification
Published on: November 15, 2017
On-column trypsin digestion coupled with LC-MS/MS for quantification of apolipoproteins
Christopher A Toth1, Zsuzsanna Kuklenyik1, Jeffrey I Jones1
1Centers for Disease Control and Prevention, Division of Laboratory Sciences, Atlanta, GA, United States.
Abstract:
Apolipoproteins measured in plasma or serum are potential biomarkers for assessing metabolic irregularities that are associated with the development of cardiovascular disease (CVD). LC-MS/MS allows quantitative measurement of multiple apolipoproteins in the same sample run. However, the accuracy and precision of the LC-MS/MS measurement depends on the reproducibility of the enzymatic protein digestion step. With the application of an immobilized enzyme reactor (IMER), the reproducibility of the trypsin digestion can be controlled with high precision via flow rate, column volume and temperature. In this report, we demonstrate the application of an integrated IMER-LC-MS/MS platform for the simultaneous quantitative analysis of eight apolipoproteins. Using a dilution series of a characterized serum pool as calibrator, the method was validated by repeated analysis of pooled sera and individual serum samples with a wide range of lipid profiles, all showing intra-assay CV<4.4% and inter-assay CV<8%. In addition, the method was compared with traditional homogeneous digestion coupled LC-MS/MS for the quantification of apoA-I and apoB-100. Applied in large scale human population studies, this method can serve the translation of a wider panel of apolipoprotein biomarkers from research to clinical application.
Significance:
Currently, the translation of apolipoprotein biomarkers to clinical application is impaired because of the high cost of large cohort studies using traditional single-analyte immunoassays. The application of on-line tryptic digestion coupled with LC-MS/MS analysis is an effective way to address this problem. In this work we demonstrate a high throughput, multiplexed, automated proteomics workflow for the simultaneous analysis of multiple proteins.
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