Evidence map›Paper›PMID 33175545›Full record

ArticleJournal of proteome research2021

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

Danting Liu, Shu Yang, Kanisha Kavdia, Jeffrey M Sifford, Zhiping Wu, Boer Xie, Zhen Wang, Vishwajeeth R Pagala, Hong Wang, Kaiwen Yu and 5 more

Open access · greenAbstract read
In one paragraph

Article in Journal of proteome research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed
2.5field-weighted citation impact, top 10% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

23 citing papers in PubMed, 37 citations in OpenAlex.

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  16. Mass spectrometry-based retina proteomics.Mass spectrometry reviews · 2023
    Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

15 authors at 2 institutions in 1 country.

Danting LiuDepartments of Structural Biology and Developmental Neurobiology, Saint Jude Children's Research Hospital, 262 Danny Thomas Place, Memphis, Tennessee 38105, United States.
Shu YangDepartments of Structural Biology and Developmental Neurobiology, Saint Jude Children's Research Hospital, 262 Danny Thomas Place, Memphis, Tennessee 38105, United States.
Kanisha KavdiaCenter for Proteomics and Metabolomics, Saint Jude Children's Research Hospital, 262 Danny Thomas Place, Memphis, Tennessee 38105, United States.
Jeffrey M SiffordDepartments of Structural Biology and Developmental Neurobiology, Saint Jude Children's Research Hospital, 262 Danny Thomas Place, Memphis, Tennessee 38105, United States.
Zhiping WuDepartments of Structural Biology and Developmental Neurobiology, Saint Jude Children's Research Hospital, 262 Danny Thomas Place, Memphis, Tennessee 38105, United States.
Boer XieCenter for Proteomics and Metabolomics, Saint Jude Children's Research Hospital, 262 Danny Thomas Place, Memphis, Tennessee 38105, United States.
Zhen WangDepartments of Structural Biology and Developmental Neurobiology, Saint Jude Children's Research Hospital, 262 Danny Thomas Place, Memphis, Tennessee 38105, United States.
Vishwajeeth R PagalaCenter for Proteomics and Metabolomics, Saint Jude Children's Research Hospital, 262 Danny Thomas Place, Memphis, Tennessee 38105, United States.
Hong WangCenter for Proteomics and Metabolomics, Saint Jude Children's Research Hospital, 262 Danny Thomas Place, Memphis, Tennessee 38105, United States.
Kaiwen YuDepartments of Structural Biology and Developmental Neurobiology, Saint Jude Children's Research Hospital, 262 Danny Thomas Place, Memphis, Tennessee 38105, United States.ORCID 0000-0002-6050-8477
Kaushik Kumar DeyDepartments of Structural Biology and Developmental Neurobiology, Saint Jude Children's Research Hospital, 262 Danny Thomas Place, Memphis, Tennessee 38105, United States.
Anthony A HighCenter for Proteomics and Metabolomics, Saint Jude Children's Research Hospital, 262 Danny Thomas Place, Memphis, Tennessee 38105, United States.
Geidy E SerranoBanner Sun Health Research Institute, Sun City, Arizona 85351, United States.
Thomas G BeachBanner Sun Health Research Institute, Sun City, Arizona 85351, United States.
Junmin PengDepartments of Structural Biology and Developmental Neurobiology, Saint Jude Children's Research Hospital, 262 Danny Thomas Place, Memphis, Tennessee 38105, United States.ORCID 0000-0003-0472-7648
St. Jude Children's Research Hospital · USBanner Sun Health Research Institute · US

Funding

Viral Vector Technology (VVTSR)P30CA021765 · NCI · ST. JUDE CHILDREN'S RESEARCH HOSPITAL · PI CHARLES ROBERTS · 1985 to 2026
$166.9M
Research Education ComponentP30AG019610 · NIA · SUN HEALTH RESEARCH INSTITUTE · PI REIMAN, ERIC MICHAEL · 2001 to 2020
$32.5M
Research Education ComponentP30AG072980 · NIA · BANNER HEALTH · PI Nicholas Ashton · 2021 to 2026
$24.9M
Utilization of proteomics and lipidomics to identify modifiers of LBDU54NS110435 · NINDS · MAYO CLINIC JACKSONVILLE · PI DICKSON, DENNIS WILLIAM · 2019 to 2023
$14.5M
National Brain and Tissue Resource for Parkinson's Disease and Related DisordersU24NS072026 · NINDS · BANNER SUN HEALTH RESEARCH INSTITUTE · PI BEACH, THOMAS G · 2011 to 2015
$7.8M
Systems Approaches to Novel Molecular Mechanism in Alzheimer's DiseaseRF1AG064909 · NIA · UT SOUTHWESTERN MEDICAL CENTER · PI PENG, JUNMIN, YU, GANG · 2019 to 2024
$6.4M
Multi-level Integrative Proteomics to Alzheimer's Disease PathwaysR01AG053987 · NIA · ST. JUDE CHILDREN'S RESEARCH HOSPITAL · PI PENG, JUNMIN · 2016 to 2020
$2.2M
RNA splicing dysfunction in Alzheimer's diseaseR01AG047928 · NIA · ST. JUDE CHILDREN'S RESEARCH HOSPITAL · PI PENG, JUNMIN · 2015 to 2019
$1.8M
Proteomics Approaches to Protein TurnoverR01GM114260 · NIGMS · ST. JUDE CHILDREN'S RESEARCH HOSPITAL · PI PENG, JUNMIN · 2016 to 2019
$1.4M
NCI NIH HHS P30 CA021765NIA NIH HHS P30 AG019610NIA NIH HHS P30 AG072980NIA NIH HHS R01 AG047928NIA NIH HHS R01 AG053987NIA NIH HHS RF1 AG064909NIGMS NIH HHS R01 GM114260NINDS NIH HHS U24 NS072026NINDS NIH HHS U54 NS110435
6 · The paper itself

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.

Indexed as

ProteomeTandem Mass SpectrometryChromatography, LiquidHumansProteomicsReproducibility of ResultsProteomeAlzheimer’s diseaseisobaric labelingliquid chromatographymass spectrometrynanoscaleproteomeproteomicssingle cell proteomicsTMTvascular dementia

Identifiers

PMID33175545
PMCPMC8262114
OpenAlexW3098085375

What OpenQuestion holds

Textmetadata
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.