Evidence map›Paper›PMID 23617947›Full record

ArticleProteome science2013

Whole gel processing procedure for GeLC-MS/MS based proteomics.

Sander R Piersma, Marc O Warmoes, Meike de Wit, Inge de Reus, Jaco C Knol, Connie R Jiménez

Abstract read
In one paragraph

Article in Proteome science, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers.

0numbers the graph read from it
0cells of the map it votes in
43citing 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

43 citing papers in PubMed.

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  10. Affinity-Based Interactome Analysis of Endogenous LINE-1 Macromolecules.Methods in molecular biology (Clifton, N.J.) · 2023
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  12. Bioconjugation Strategies for Tobacco Mild Green Mosaic Virus.Chembiochem : a European journal of chemical biology · 2022
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  16. Novel Extract from BeetleAntioxidants (Basel, Switzerland) · 2021
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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

6 authors.

Sander R PiersmaDepartment of Medical Oncology, OncoProteomics Laboratory, VU University Medical Center, Amsterdam, The Netherlands. s.piersma@vumc.nl.
Marc O Warmoes
Meike de Wit
Inge de Reus
Jaco C Knol
Connie R Jiménez

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSDS-PAGE followed by in-gel digestion (IGD) is a popular workflow in mass spectrometry-based proteomics. In GeLC-MS/MS, a protein lysate of a biological sample is separated by SDS-PAGE and each gel lane is sliced in 5-20 slices which, after IGD, are analyzed by LC-MS/MS. The database search results for all slices of a biological sample are combined yielding global protein identification and quantification for each sample. In large scale GeLC-MS/MS experiments the manual processing steps including washing, reduction and alkylation become a bottleneck. Here we introduce the whole gel (WG) procedure where, prior to gel slice cutting, the processing steps are carried out on the whole gel.

resultsIn two independent experiments human HCT116 cell lysate and mouse tumor tissue lysate were separated by 1D SDS PAGE. In a back to back comparison of the IGD procedure and the WG procedure, both protein identification (>80% overlap) and label-free protein quantitation (R2=0.94) are highly similar between procedures. Triplicate analysis of the WG procedure of both HCT116 cell lysate and formalin-fixed paraffin embedded (FFPE) tumor tissue showed identification reproducibility of >88% with a CV<20% on protein quantitation.

conclusionsThe whole gel procedure allows for reproducible large-scale differential GeLC-MS/MS experiments, without a prohibitive amount of manual processing and with similar performance as conventional in-gel digestion. This procedure will especially enable clinical proteomics for which GeLC-MS/MS is a popular workflow and sample numbers are relatively high.

Identifiers

PMID23617947
PMCPMC3656797

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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.