Evidence map›Paper›PMID 34110797›Full record

ArticleAnalytical chemistry2021

A Universal and High-Throughput Proteomics Sample Preparation Platform.

Andrew P Burns, Ya-Qin Zhang, Tuan Xu, Zhengxi Wei, Qin Yao, Yuhong Fang, Valeriu Cebotaru, Menghang Xia, Matthew D Hall, Ruili Huang and 3 more

Abstract read
In one paragraph

Article in Analytical chemistry, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
–field-weighted citation impact
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

16 citing papers in PubMed.

  1. Article
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  15. Separation methods in single-cell proteomics: RPLC or CE?International journal of mass spectrometry · 2022
    Article
  16. Article
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

13 authors.

Andrew P BurnsNational Center for Advancing Translational Sciences, National Institutes of Health, 9800 Medical Center Drive, Rockville, Maryland 20850, United States.
Ya-Qin ZhangNational Center for Advancing Translational Sciences, National Institutes of Health, 9800 Medical Center Drive, Rockville, Maryland 20850, United States.
Tuan XuNational Center for Advancing Translational Sciences, National Institutes of Health, 9800 Medical Center Drive, Rockville, Maryland 20850, United States.
Zhengxi WeiNational Center for Advancing Translational Sciences, National Institutes of Health, 9800 Medical Center Drive, Rockville, Maryland 20850, United States.
Qin YaoDivision of Nephrology, Department of Medicine, University of Maryland School of Medicine, Baltimore, Maryland 21201, United States.
Yuhong FangNational Center for Advancing Translational Sciences, National Institutes of Health, 9800 Medical Center Drive, Rockville, Maryland 20850, United States.
Valeriu CebotaruDivision of Nephrology, Department of Medicine, University of Maryland School of Medicine, Baltimore, Maryland 21201, United States.
Menghang XiaNational Center for Advancing Translational Sciences, National Institutes of Health, 9800 Medical Center Drive, Rockville, Maryland 20850, United States.ORCID 0000-0001-7285-8469
Matthew D HallNational Center for Advancing Translational Sciences, National Institutes of Health, 9800 Medical Center Drive, Rockville, Maryland 20850, United States.ORCID 0000-0002-5073-442X
Ruili HuangNational Center for Advancing Translational Sciences, National Institutes of Health, 9800 Medical Center Drive, Rockville, Maryland 20850, United States.
Anton SimeonovNational Center for Advancing Translational Sciences, National Institutes of Health, 9800 Medical Center Drive, Rockville, Maryland 20850, United States.
Christopher A LeClairNational Center for Advancing Translational Sciences, National Institutes of Health, 9800 Medical Center Drive, Rockville, Maryland 20850, United States.ORCID 0000-0002-2746-5938
Dingyin TaoNational Center for Advancing Translational Sciences, National Institutes of Health, 9800 Medical Center Drive, Rockville, Maryland 20850, United States.ORCID 0000-0001-6531-2740

Funding

Analytical ChemistryZICTR000037 · NCATS · NATIONAL CENTER FOR ADVANCING TRANSLATIONAL SCIENCES · PI LECLAIR, CHRISTOPHER ARTHUR · 2015 to 2025
$23.2M
Toxicology in the 21st Century Program (Tox21) - Computational ToxicologyZIATR000040 · NCATS · NATIONAL CENTER FOR ADVANCING TRANSLATIONAL SCIENCES · PI HUANG, RUILI · 2016 to 2025
$3.5M
Intramural NIH HHS Z99 TR999999
6 · The paper itself

Abstract

Major advances have been made to improve the sensitivity of mass analyzers, spectral quality, and speed of data processing enabling more comprehensive proteome discovery and quantitation. While focus has recently begun shifting toward robust proteomics sample preparation efforts, a high-throughput proteomics sample preparation is still lacking. We report the development of a highly automated universal 384-well plate sample preparation platform with high reproducibility and adaptability for extraction of proteins from cells within a culture plate. Digestion efficiency was excellent in comparison to a commercial digest peptide standard with minimal sample loss while improving sample preparation throughput by 20- to 40-fold (the entire process from plated cells to clean peptides is complete in ∼300 min). Analysis of six human cell types, including two primary cell samples, identified and quantified ∼4,000 proteins for each sample in a single high-performance liquid chromatography (HPLC)-tandem mass spectrometry injection with only 100-10K cells, thus demonstrating universality of the platform. The selected protein was further quantified using a developed HPLC-multiple reaction monitoring method for HeLa digests with two heavy labeled internal standard peptides spiked in. Excellent linearity was achieved across different cell numbers indicating a potential for target protein quantitation in clinical research.

Indexed as

ProteomeProteomicsChromatography, High Pressure LiquidHumansMass SpectrometryReproducibility of ResultsProteome

Identifiers

PMID34110797
PMCPMC9876622

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.