Automated Microchromatography Enables Multiplexing of Immunoaffinity Enrichment of Peptides to Greater than 150 for Targeted MS-Based Assays.
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Abstract | Immunoaffinity enrichment of peptides coupled with analysis by stable isotope dilution multiple reaction mass spectrometry has been shown to have analytical performance and detection limits suitable for many biomarker verification studies and biological applications. Prior studies have shown that antipeptide antibodies can be multiplexed up to 50 in a single assay without significant loss of performance. Achieving higher multiplex levels is relevant to all studies involving precious biological material as this minimizes the amount of sample that must be consumed to measure a given set of analytes and reduces the assay cost per analyte. Here we developed automated methods employing the Agilent AssayMAP Bravo microchromatography platform and used these methods to characterize the performance of immunoaffinity enrichment of peptides up to multiplex levels of 172. Median capture efficiency for the target peptides remained high (88%) even at levels of 150-plex and declined to 70% at 172-plex compared to antibody performance observed at standard lower multiplex levels (n = 25). Subsequently, we developed and analytically characterized a multiplexed immuno-multiple reaction monitoring-mass spectrometry (immuno-MRM-MS) assay (n = 110) and applied it to measure candidate protein biomarkers of cardiovascular disease in plasma of patients undergoing planned myocardial infarction. The median lower limit of detection of all peptides was 71.5 amol/μL (nM), and the coefficient of variation (CV) was less than 15% at the lower limit of quantification. The results demonstrate that high multiplexed immuno-MRM-MS assays are readily achievable using the optimized sample processing and peptide capture methods described here. |
Year of Publication | 2016
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Journal | Anal Chem
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Volume | 88
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Issue | 15
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Pages | 7548-55
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Date Published | 2016 08 02
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ISSN | 1520-6882
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DOI | 10.1021/acs.analchem.6b00946
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PubMed ID | 27321643
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Grant list | U24 CA160034 / CA / NCI NIH HHS / United States
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