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Updated: Jan 8, 2026

Deep Proteome Profiling by Isobaric Labeling, Extensive Liquid Chromatography, Mass Spectrometry, and Software-assisted Quantification
Published on: November 15, 2017
A Robust Strategy for High-Throughput and Deep Proteomics by Combining Narrow-Window Data-Independent Acquisition and
Chaewon Kang1, Jiwon Hong1, Hokeun Kim1
1Department of Chemistry, Korea University, Seoul 136-701, Republic of Korea.
Abstract:
Data-independent acquisition (DIA) mass spectrometry systematically fragments all precursor ions within predefined isolation windows of a predefined mass-to-charge (m/z) range. Unlike data-dependent acquisition (DDA), which selects precursor ions based on intensity, DIA enhances identification and quantification opportunities for lower-intensity peptides, significantly improving proteome coverage. Nevertheless, standard DIA methodologies have limited application for isobaric-labeled peptides, primarily due to challenges in accurately quantifying reporter ions arising from coisolation interference from coeluting peptides, degrading quantitative precision and accuracy. Here, an ultra-narrow-window DIA workflow compatible with 18-plex TMTpro labeling is presented, a novel strategy overcoming a major limitation in conventional pipelines for isobaric labeling-based DIA analysis. Acquisition with an Orbitrap Astral mass spectrometer operating at 200 Hz MS/MS scan speed and 80,000 resolving power (m/z 200) enabled 0.6 Th isolation windows approaching DDA-level precursor specificity. Leveraging mPE-MMR, precursor masses were accurately assigned to multiplexed DIA spectra prior to conventional spectrum-centric database searching, permitting routine peptide-to-spectrum matching. Applied to ovarian cancer tissue digests, the method identified substantially more peptides and protein groups than did DDA analyses while sustaining reporter ion precision and accuracy. These gains translate into deeper proteomic coverage without compromising quantitative robustness for multiplexed proteomics, thereby holding significant potential for clinical and population-scale studies.

