Dataset Information

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

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.

SUBMITTER: Liu D

PROVIDER: S-EPMC8262114 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

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

Liu Danting D Yang Shu S Kavdia Kanisha K Sifford Jeffrey M JM Wu Zhiping Z Xie Boer B Wang Zhen Z Pagala Vishwajeeth R VR Wang Hong H Yu Kaiwen K Dey Kaushik Kumar KK High Anthony A AA Serrano Geidy E GE Beach Thomas G TG Peng Junmin J

Journal of proteome research 20201111 1

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 re ...[more]

PMID: 33175545

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Project description:BackgroundDespite the widespread application of new drug-eluting stents, a considerable portion of patients experience in-stent restenosis (ISR). To date, the pathophysiologic mechanisms of ISR remain poorly understood.MethodsIn this study, we collected plasma samples from ISR patients (n = 29) and non-ISR patients (n = 36) after drug-eluting stent implantation, as well as from healthy controls (HCs) (n = 32). Our goal was to investigate differences in plasma protein profiles using tandem mass tag (TMT) labeling coupled with liquid chromatography and tandem mass spectrometry. The proteomic data were validated by enzyme-linked immunosorbent assay (ELISA). Bioinformatic analyses were conducted to analyze potential pathways and protein-protein interaction (PPI) involved in ISR.ResultsA total of 1,696 proteins were identified, of which 278 differed in protein abundance between non-ISR and HCs, 497 between ISR and HCs, and 387 between ISR and non-ISR, respectively. Bioinformatic analyses, including Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and PPI, further demonstrated that differentially abundant proteins between ISR and non-ISR are involved in several crucial biological processes and signaling pathways, such as focal adhesion, platelet activation, Rap1 signaling, regulation of actin cytoskeleton, and cholesterol metabolism. Among the identified differentially abundant proteins in ISR, 170 were increased in abundance relative to both non-ISR patients and HCs. Some of these proteins were identified to have critical functions for atherosclerosis development and might be involved in ISR pathology. Among these proteins, 3 proteins with increased abundance including fetuin-B, apolipoprotein C-III (APOC3), and cholesteryl ester transfer protein (CETP) were confirmed by ELISA.ConclusionsThis is the first study provided a comprehensive proteomic profile to understand ISR pathology, which may help identify early diagnostic biomarkers and therapeutic targets.

Dataset Information

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

Publications

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

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