Evidence map›Paper›PMID 20807836›Full record

ArticleMolecular & cellular proteomics : MCP2011

A robust method for quantitative high-throughput analysis of proteomes by 18O labeling.

Elena Bonzon-Kulichenko, Daniel Pérez-Hernández, Estefanía Núñez, Pablo Martínez-Acedo, Pedro Navarro, Marco Trevisan-Herraz, María del Carmen Ramos, Saleta Sierra, Sara Martínez-Martínez, Marisol Ruiz-Meana and 5 more

Open access · hybridAbstract read
In one paragraph

Article in Molecular & cellular proteomics : MCP, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 54 papers.

0numbers the graph read from it
0cells of the map it votes in
54citing papers in PubMed
2.9field-weighted citation impact, top 9% 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

54 citing papers in PubMed, 104 citations in OpenAlex.

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  15. Proteomics ofToxins · 2023
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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 5 institutions in 1 country.

Elena Bonzon-KulichenkoLaboratory of Protein Chemistry and Proteomics, Centro de Biología Molecular Severo Ochoa (CSIC-UAM), Madrid, E-28049, Spain.
Daniel Pérez-Hernández
Estefanía Núñez
Pablo Martínez-Acedo
Pedro Navarro
Marco Trevisan-Herraz
María del Carmen Ramos
Saleta Sierra
Sara Martínez-Martínez
Marisol Ruiz-Meana
Elizabeth Miró-Casas
David García-Dorado
Juan Miguel Redondo
Javier S Burgos
Jesús Vázquez
Consejo Superior de Investigaciones Científicas · ESNeuron BioPharma (Spain) · ESUniversidad Autónoma de Madrid · ESVall d'Hebron Hospital Universitari · ESSpanish National Centre for Cardiovascular Research · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

MS-based quantitative proteomics plays an increasingly important role in biological and medical research and the development of these techniques remains one of the most important challenges in mass spectrometry. Numerous stable isotope labeling approaches have been proposed. However, and particularly in the case of (18)O-labeling, a standard protocol of general applicability is still lacking, and statistical issues associated to these methods remain to be investigated. In this work we present an improved high-throughput quantitative proteomics method based on whole proteome concentration by SDS-PAGE, optimized in-gel digestion, peptide (18)O-labeling, and separation by off-gel isoelectric focusing followed by liquid chromatography-LIT-MS. We demonstrate that the off-gel technique is fully compatible with (18)O peptide labeling in any pH range. A recently developed statistical model indicated that partial digestions and methionine oxidation do not alter protein quantification and that variances at the scan, peptide, and protein levels are stable and reproducible in a variety of proteomes of different origin. We have also analyzed the dynamic range of quantification and demonstrated the practical utility of the method by detecting expression changes in a model of activation of Jurkat T-cells. Our protocol provides a general approach to perform quantitative proteomics by (18)O-labeling in high-throughput studies, with the added value that it has a validated statistical model for the null hypothesis. To the best of our knowledge, this is the first report where a general protocol for stable isotope labeling is tested in practice using a collection of samples and analyzed at this degree of statistical detail.

Indexed as

Analysis of VarianceAnimalsCell Line, TumorChemical FractionationCytoplasmElectrophoresis, Polyacrylamide GelHigh-Throughput Screening AssaysHumansIsoelectric FocusingIsotope LabelingMethionineNeoplasm ProteinsOxidation-ReductionOxygen IsotopesPeptidesProteomeMethionineNeoplasm ProteinsOxygen IsotopesPeptidesProteome

Identifiers

PMID20807836
PMCPMC3013457
OpenAlexW2146169610

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.