Mass Defect-Based DiLeu Tagging for Multiplexed Data-Independent Acquisition.
Xiaofang ZhongDustin C FrostQinying YuMiyang LiTing-Jia GuLingjun LiPublished in: Analytical chemistry (2020)
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 (MS2) 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 MS2 spectra. Quantitative analysis of yeast samples displayed comparable accuracy and precision for MS2-based DIA and MS1-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.
Keyphrases
- mass spectrometry
- high resolution
- single cell
- tandem mass spectrometry
- liquid chromatography
- multiple sclerosis
- ms ms
- high performance liquid chromatography
- gas chromatography
- electronic health record
- ultra high performance liquid chromatography
- cerebrospinal fluid
- small molecule
- big data
- high throughput
- wastewater treatment
- machine learning
- artificial intelligence
- antibiotic resistance genes
- density functional theory
- label free
- molecular dynamics