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Systematic Optimization of Long Gradient Chromatography Mass Spectrometry for Deep Analysis of Brain Proteome
[Image: see text] 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...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Chemical
Society
2014
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4324436/ https://www.ncbi.nlm.nih.gov/pubmed/25455107 http://dx.doi.org/10.1021/pr500882h |
Sumario: | [Image: see text] 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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