4.7 Article

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

Journal

JOURNAL OF PROTEOME RESEARCH
Volume 20, Issue 1, Pages 337-345

Publisher

AMER CHEMICAL SOC
DOI: 10.1021/acs.jproteome.0c00426

Keywords

proteomics; proteome; mass spectrometry; isobaric labeling; TMT; liquid chromatography; nanoscale; single cell proteomics; Alzheimer's disease; vascular dementia

Funding

  1. NIH [R01GM114260, R01AG047928, R01AG053987, RF1AG064909, U54NS110435, U24NS072026, P30AG19610]
  2. Arizona Department of Health Services [211002]
  3. Arizona Biomedical Research Commission [4001, 0011, 05-901, 1001]
  4. ALSAC (American Lebanese Syrian Associated Charities)
  5. NIH Cancer Center Support Grant [P30CA021765]

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A streamlined protocol has been developed to quantify over 9000 proteins with 0.5 μg of protein using 16-plex TMT coupled with LC/LC-MS/MS. Comparison with the standard protocol in 16 human brain tissue samples showed that the microgram-scale protocol had adequate sensitivity and reproducibility to detect differentially expressed proteins in disease-related pathways. This newly developed method holds promise for deep proteomic analysis at sub-microgram levels in biological and clinical samples.
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 mu g protein in starting materials during a standard analysis. Here, we present a streamlined protocol to quantify more than 9000 proteins with 0.5 mu g 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.

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