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Proteomics. 2017 Jan;17(1-2). doi: 10.1002/pmic.201600085.

Automation of PRM-dependent D3-Leu tracer enrichment in HDL to study the metabolism of apoA-I, LCAT and other apolipoproteins.

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Center for Interdisciplinary Cardiovascular Sciences, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.


We developed an automated quantification workflow for PRM-enabled detection of D3-Leu labeled apoA-I in high-density lipoprotein (HDL) isolated from humans. Subjects received a bolus injection of D3-Leu and blood was drawn at eight time points over three days. HDL was isolated and separated into six size fractions for subsequent proteolysis and PRM analysis for the detection of D3-Leu signal from ∼0.03 to 0.6% enrichment. We implemented an intensity-based quantification approach that takes advantage of high-resolution/accurate mass PRM scans to identify the D3-Leu 2HM3 ion from non-specific peaks. Our workflow includes five modules for extracting the targeted PRM peak intensities (XPIs): Peak centroiding, noise removal, fragment ion matching using Δm/z windows, nine intensity quantification options, and validation and visualization outputs. We optimized the XPI workflow using in vitro synthesized and clinical samples of D0/D3-Leu labeled apoA-I. Three subjects' apoA-I enrichment curves in six HDL size fractions, and LCAT, apoA-II and apoE from two size fractions were generated within a few hours. Our PRM strategy and automated quantification workflow will expedite the turnaround of HDL apoA-I metabolism data in clinical studies that aim to understand and treat the mechanisms behind dyslipidemia.


Apolipoprotein; Bioinformatics; Endogenous labeling; Ion peak intensity; Neutron encoded mass signatures; Noise removal; Targeted mass spectrometry

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