Deep Profiling of Microgram-Scale Proteome by Tandem Mass Tag Mass Spectrometry

J Proteome Res. 2021 Jan 1;20(1):337-345. doi: 10.1021/acs.jproteome.0c00426. Epub 2020 Nov 11.

Abstract

Tandem mass tag (TMT)-based mass spectrometry (MS) enables deep proteomic profiling of more than 10,000 proteins in complex biological samples but requires up to 100 μg protein in starting materials during a standard analysis. Here, we present a streamlined protocol to quantify more than 9000 proteins with 0.5 μg protein per sample by 16-plex TMT coupled with two-dimensional liquid chromatography and tandem mass spectrometry (LC/LC-MS/MS). In this protocol, we optimized multiple conditions to reduce sample loss, including processing each sample in a single tube to minimize surface adsorption, increasing digestion enzymes to shorten proteolysis and function as carriers, eliminating a desalting step between digestion and TMT labeling, and developing miniaturized basic pH LC for prefractionation. By profiling 16 identical human brain tissue samples of Alzheimer's disease (AD), vascular dementia (VaD), and non-dementia controls, we directly compared this new microgram-scale protocol to the standard-scale protocol, quantifying 9116 and 10,869 proteins, respectively. Importantly, bioinformatics analysis indicated that the microgram-scale protocol had adequate sensitivity and reproducibility to detect differentially expressed proteins in disease-related pathways. Thus, this newly developed protocol is of general application for deep proteomics analysis of biological and clinical samples at sub-microgram levels.

Keywords: Alzheimer’s disease; TMT; isobaric labeling; liquid chromatography; mass spectrometry; nanoscale; proteome; proteomics; single cell proteomics; vascular dementia.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Chromatography, Liquid
  • Humans
  • Proteome*
  • Proteomics
  • Reproducibility of Results
  • Tandem Mass Spectrometry*

Substances

  • Proteome