Systematic optimization of long gradient chromatography mass spectrometry for deep analysis of brain proteome
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Updated: Apr 20, 2026

Deep Proteome Profiling by Isobaric Labeling, Extensive Liquid Chromatography, Mass Spectrometry, and Software-assisted Quantification
Published on: November 15, 2017
Hong Wang1, Yanling Yang, Yuxin Li
1Department of Structural Biology, ‡St. Jude Proteomics Facility, and §̂Department of Developmental Neurobiology, St. Jude Children's Research Hospital , 262 Danny Thomas Place, Memphis, Tennessee 38105, United States.
Abstract:
The development of high-resolution liquid chromatography (LC) is essential for improving the sensitivity and throughput of mass spectrometry (MS)-based proteomics. Here we present systematic optimization of a long gradient LC-MS/MS platform to enhance protein identification from a complex mixture. The platform employed an in-house fabricated, reverse-phase long column (100 μm × 150 cm, 5 μm C18 beads) coupled to Q Exactive MS. The column was capable of achieving a peak capacity of ∼700 in a 720 min gradient of 10-45% acetonitrile. The optimal loading level was ∼6 μg of peptides, although the column allowed loading as many as 20 μg. Gas-phase fractionation of peptide ions further increased the number of peptide identification by ∼10%. Moreover, the combination of basic pH LC prefractionation with the long gradient LC-MS/MS platform enabled the identification of 96,127 peptides and 10,544 proteins at 1% protein false discovery rate in a post-mortem brain sample of Alzheimer's disease. Because deep RNA sequencing of the same specimen suggested that ∼16,000 genes were expressed, the current analysis covered more than 60% of the expressed proteome. Further improvement strategies of the LC/LC-MS/MS platform were also discussed.
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