Evidence map›Paper›PMID 35554907›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2022

Profiling SARS-CoV-2 Infection by High-Throughput Shotgun Proteomics.

Lucia Grenga, Duarte Gouveia, Jean Armengaud

Abstract read
PubMed Publisher
In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
1.3field-weighted citation impact, top 25% 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

1 citing paper in PubMed, 2 citations in OpenAlex.

  1. 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

3 authors at 2 institutions in 1 country.

Lucia GrengaDépartement Médicaments et Technologies pour la Santé (DMTS), Université Paris-Saclay, CEA, INRAE, SPI, Bagnols-sur-Cèze, France.
Duarte GouveiaDépartement Médicaments et Technologies pour la Santé (DMTS), Université Paris-Saclay, CEA, INRAE, SPI, Bagnols-sur-Cèze, France.
Jean ArmengaudDépartement Médicaments et Technologies pour la Santé (DMTS), Université Paris-Saclay, CEA, INRAE, SPI, Bagnols-sur-Cèze, France. jean.armengaud@cea.fr.
Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement · FRCEA Paris-Saclay · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A comprehensive cartography of viral and host proteins expressed during the different stages of SARS-CoV-2 infection is key to decipher the molecular mechanisms of pathogenesis. For the most detailed analysis, proteins should be first purified and then proteolyzed with trypsin in the presence of detergents. The resulting peptide mixtures are resolved by reverse phase ultrahigh pressure liquid chromatography and then identified by a high-resolution tandem mass spectrometer. The thousands of spectra acquired for each fraction can then be assigned to peptide sequences using a relevant protein sequence database, comprising viral and host proteins and potential contaminants from the growth medium or from the operator. The peptides are evidencing proteins and their intensities are used to infer the abundance of their corresponding proteins. Data analysis allows for highlighting the viral and host proteins dynamics. Here, we describe the sample preparation method adapted to profile SARS-CoV-2 -infected cell models, the shotgun proteomics pipeline to record experimental data, and the workflow for data interpretation to analyze infection-induced proteomic changes in a time-resolved manner.

Indexed as

COVID-19ProteomicsHumansPeptidesSARS-CoV-2Tandem Mass SpectrometryPeptidesCoronavirusData analysisHigh-throughput proteomicsPeptide preparationProtein extractionQuantitative proteomicsTandem mass spectrometryVirus

Identifiers

PMID35554907
OpenAlexW4285145252

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.