4.8 Article

Identification of 7 000-9 000 Proteins from Cell Lines and Tissues by Single-Shot Microflow LC-MS/MS

期刊

ANALYTICAL CHEMISTRY
卷 93, 期 25, 页码 8687-8692

出版社

AMER CHEMICAL SOC
DOI: 10.1021/acs.analchem.1c00738

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资金

  1. Alexander von Humboldt Foundation
  2. Carl Friedrich von Siemens Foundation
  3. National Natural Science Foundation of China [81600046]
  4. German Science Foundation (DFG) [SFB924]
  5. German Ministry for Science and Research (BMBF) [031L0008A, 031L0168, 031L0214A]
  6. ERC Advanced Grant [833710]
  7. European Research Council (ERC) [833710] Funding Source: European Research Council (ERC)

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Acquiring proteomic data in a single-shot by microflow LC-MS/MS system allows for efficient and comprehensive analysis of proteins from various samples, with high reliability for samples with sufficient quantities. This method demonstrates high proteome coverage and quantitative accuracy, showing potential for further advancements in rapid chromatography and data independent acquisition approaches.
A current trend in proteomics is to acquire data in a single-shot by LC-MS/MS because it simplifies workflows and promises better throughput and quantitative accuracy than schemes that involve extensive sample fractionation. However, single-shot approaches can suffer from limited proteome coverage when performed by data dependent acquisition (ssDDA) on nanoflow LC systems. For applications where sample quantities are not scarce, this study shows that high proteome coverage can be obtained using a microflow LC-MS/MS system operating a 1 mm i.d. x 150 mm column, at a flow-rate of 50 mu L/min and coupled to an Orbitrap HF-X mass spectrometer. The results demonstrate the identification of similar to 9 000 proteins from 50 mu g of protein digest from Arabidopsis roots, 7 500 from mouse thymus, and 7 300 from human breast cancer cells in 3 h of analysis time in a single run. The dynamic range of protein quantification measured by the iBAQ approach spanned 5 orders of magnitude and replicate analysis showed that the median coefficient of variation was below 20%. Together, this study shows that ssDDA by mu LC-MS/MS is a robust method for comprehensive and large-scale proteome analysis and which may be further extended to more rapid chromatography and data independent acquisition approaches in the future.

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