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MSQ: a tool for quantification of proteomics data generated by a liquid chromatography/matrix‐assisted laser desorption/ionization time‐of‐flight tandem mass spectrometry based targeted quantitative proteomics platform
Authors:Jung Hun Oh  Sheng Pan  Jing Zhang  Jean Gao
Institution:1. Department of Radiation Oncology, Washington University School of Medicine, St. Louis, MO, USA;2. Department of Pathology, University of Washington, Seattle, WA, USA;3. Department of Computer Science and Engineering, University of Texas, Arlington, TX, USA
Abstract:Mass spectrometry (MS)‐based quantitative proteomics has become a critical component of biological and clinical research for identification of biomarkers that can be used for early detection of diseases. In particular, MS‐based targeted quantitative proteomics has been recently developed for the detection and validation of biomarker candidates in complex biological samples. In such approaches, synthetic reference peptides that are the stable isotope labeled version of proteotypic peptides of proteins to be quantitated are used as internal standards enabling specific identification and absolute quantification of targeted peptides. The quantification of targeted peptides is achieved using the intensity ratio of a native peptide to the corresponding reference peptide whose spike‐in amount is known. However, a manual calculation of the ratios can be time‐consuming and labor‐intensive, especially when the number of peptides to be tested is large. To establish a liquid chromatography/matrix‐assisted laser desorption/ionization time‐of‐flight tandem mass spectrometry (LC/MALDI TOF/TOF)‐based targeted quantitative proteomics pipeline, we have developed a software named Mass Spectrometry based Quantification (MSQ). This software can be used to automate the quantification and identification of targeted peptides/proteins by the MALDI TOF/TOF platform. MSQ was applied to the detection of a selected group of targeted peptides in pooled human cerebrospinal spinal fluid (CSF) from patients with Alzheimer's disease (AD) in comparison with age‐matched control (OC). The results for the automated quantification and identification of targeted peptides/proteins in CSF were in good agreement with results calculated manually. Copyright © 2010 John Wiley & Sons, Ltd.
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