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Updated: Apr 27, 2026

Comprehensive Workflow of Mass Spectrometry-based Shotgun Proteomics of Tissue Samples
Published on: November 13, 2021
Quantitative shotgun proteomics with data-independent acquisition and traveling wave ion mobility spectrometry: a
1Quantitative Proteomics Center, Department of Biological Sciences, Columbia University, New York, NY, 10027, USA, lb2425@columbia.edu.
Abstract:
Data-independent acquisition (DIA) implemented in a method called MS(E) can be performed in a massively parallel, time-based schedule rather than by sampling masses sequentially in shotgun proteomics. In MS(E) alternating low and high energy spectra are collected across the full mass range. This approach has been very successful and stimulated the development of variants modeled after the MS(E) protocol, but over narrower mass ranges. The massively parallel MS(E) and other DIA methodologies have enabled effective label-free quantitation methods that have been applied to a wide variety of samples including affinity pulldowns and studies of cells, tissues, and clinical samples. Another complementary technology matches accurate mass and retention times of precursor ions across multiple chromatographic runs. This further enhances the impact of MS(E) in counteracting the stochastic nature of mass spectrometry as applied in proteomics. Otherwise significant amounts of data in typical large-scale protein profiling experiments are missing. A variety of software packages perform this function similar in concept to matching of accurate mass tags. Another enhancement of this method involves a variation of MS(E) coupled with traveling wave ion mobility spectrometry to provide separations of peptides based on cross-sectional area and shape in addition to mass/charge (m/z) ratio. Such a two-dimensional separation in the gas phase considerably increases protein coverage as well as typically a doubling of the number of proteins detected. These developments along with advances in ultrahigh pressure liquid chromatography have resulted in the evolution of a robust and versatile platform for label-free protein profiling.
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