1. Hybrid Spectral Library Combining DIA-MS Data and a Targeted Virtual Library Substantially Deepens the Proteome Coverage
- Author
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Shanshan Li, Ronghui Lou, Kang Ding, Cuiping Tian, Suwen Zhao, Y. Li, Yaoyang Zhang, Wenqing Shui, and Pan Tang
- Subjects
Proteomics ,0301 basic medicine ,Hybrid library ,Multidisciplinary ,Protein family ,Proteomic Profiling ,Computer science ,A protein ,02 engineering and technology ,Computational biology ,Structural Classification of Proteins database ,Biological Sciences ,021001 nanoscience & nanotechnology ,Article ,Analytical Chemistry ,03 medical and health sciences ,030104 developmental biology ,Proteome ,lcsh:Q ,Protein identification ,lcsh:Science ,0210 nano-technology ,Classification of Proteins - Abstract
Summary Data-independent acquisition mass spectrometry (DIA-MS) is a powerful technique that enables relatively deep proteomic profiling with superior quantification reproducibility. DIA data mining predominantly relies on a spectral library of sufficient proteome coverage that, in most cases, is built on data-dependent acquisition-based analysis of the same sample. To expand the proteome coverage for a pre-determined protein family, we report herein on the construction of a hybrid spectral library that supplements a DIA experiment-derived library with a protein family-targeted virtual library predicted by deep learning. Leveraging this DIA hybrid library substantially deepens the coverage of three transmembrane protein families (G protein-coupled receptors, ion channels, and transporters) in mouse brain tissues with increases in protein identification of 37%–87% and peptide identification of 58%–161%. Moreover, of the 412 novel GPCR peptides exclusively identified with the DIA hybrid library strategy, 53.6% were validated as present in mouse brain tissues based on orthogonal experimental measurement., Graphical Abstract, Highlights • A virtual library is built for a selected protein family using deep learning models • The hybrid library strategy vastly deepens the coverage for the targeted protein family • About 53.6% of novel GPCR peptides identified with the DIA hybrid library are validated • Extend the strategy to deep mapping of multiple transmembrane protein families, Analytical Chemistry; Biological Sciences; Classification of Proteins; Proteomics
- Published
- 2020
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