Open AccessMass Defect-Based DiLeu Tagging for Multiplexed Data-Independent Acquisition
Author(s) -
Xiaofang Zhong,
Dustin C. Frost,
Qinying Yu,
Miyang Li,
TingJia Gu,
Lingjun Li
Publication year - 2020
Publication title -
analytical chemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.117
H-Index - 332
eISSN - 1520-6882
pISSN - 0003-2700
DOI - 10.1021/acs.analchem.0c01136
Subject(s) - isobaric labeling , chemistry , tandem mass tag , mass spectrometry , proteome , proteomics , isotopologue , quantitative proteomics , label free quantification , multiplexing , tandem mass spectrometry , proteogenomics , computational biology , chromatography , analytical chemistry (journal) , protein mass spectrometry , biochemistry , genomics , computer science , telecommunications , organic chemistry , genome , molecule , biology , gene
The unbiased selection of peptide precursors makes data-independent acquisition (DIA) an advantageous alternative to data-dependent acquisition (DDA) for discovery proteomics, but traditional multiplexed quantification approaches employing mass difference labeling or isobaric tagging are incompatible with DIA. Here, we describe a strategy that permits multiplexed quantification by DIA using mass defect-based N , N -dimethyl leucine (mdDiLeu) tags and high-resolution tandem mass spectrometry (MS 2 ) analysis. Millidalton mass differences between mdDiLeu isotopologues produce fragment ion multiplet peaks separated in mass by as little as 5.8 mDa, enabling up to 4-plex quantification in DIA MS 2 spectra. Quantitative analysis of yeast samples displayed comparable accuracy and precision for MS 2 -based DIA and MS 1 -based DDA methods. Multiplexed DIA analysis of cerebrospinal fluid revealed the dynamic proteome changes in Alzheimer's disease, demonstrating its utility for discovery of potential clinical biomarkers. We show that the mdDiLeu tagging approach for multiplexed DIA is a viable methodology for investigating proteome changes, particularly for low-abundance proteins, in different biological matrices.