Evidence map›Paper›PMID 39593238›Full record

ArticleJournal of proteome research2025

Dynamic Cellular Proteome Remodeling during SARS-CoV-2 Infection. Identification of Plasma Protein Readouts.

Fátima Milhano Dos Santos, Jorge Vindel-Alfageme, Sergio Ciordia, Victoria Castro, Irene Orera, Urtzi Garaigorta, Pablo Gastaminza, Fernando Corrales

Abstract read
In one paragraph

Article in Journal of proteome research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Review
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

8 authors.

Fátima Milhano Dos SantosFunctional Proteomics Laboratory, National Center for Biotechnology (CNB-CSIC), Darwin 3, Madrid 28049, Spain.ORCID 0000-0002-4041-1504
Jorge Vindel-AlfagemeFunctional Proteomics Laboratory, National Center for Biotechnology (CNB-CSIC), Darwin 3, Madrid 28049, Spain.
Sergio CiordiaFunctional Proteomics Laboratory, National Center for Biotechnology (CNB-CSIC), Darwin 3, Madrid 28049, Spain.
Victoria CastroDepartment of Molecular and Cell Biology, National Center for Biotechnology (CNB-CSIC), Darwin 3, Madrid 28049, Spain.ORCID 0000-0001-9151-5138
Irene OreraProteomics Research Core Facility, Instituto Aragonés de Ciencias de la Salud (IACS), Zaragoza 50009, Spain.
Urtzi GaraigortaDepartment of Molecular and Cell Biology, National Center for Biotechnology (CNB-CSIC), Darwin 3, Madrid 28049, Spain.ORCID 0000-0002-0683-5725
Pablo GastaminzaDepartment of Molecular and Cell Biology, National Center for Biotechnology (CNB-CSIC), Darwin 3, Madrid 28049, Spain.ORCID 0000-0002-7873-5491
Fernando CorralesFunctional Proteomics Laboratory, National Center for Biotechnology (CNB-CSIC), Darwin 3, Madrid 28049, Spain.ORCID 0000-0002-0231-5159

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The outbreak of COVID-19, led to an ongoing pandemic with devastating consequences for the global economy and human health. With the global spread of SARS-CoV-2, multidisciplinary initiatives were launched to explore new diagnostic, therapeutic, and vaccination strategies. From this perspective, proteomics could help to understand the mechanisms associated with SARS-CoV-2 infection and to identify new therapeutic options. A TMT-based quantitative proteomics and phosphoproteomics analysis was performed to study the proteome remodeling of human lung alveolar cells expressing human ACE2 (A549-ACE2) after infection with SARS-CoV-2. Detectability and the prognostic value of selected proteins was analyzed by targeted PRM. A total of 6802 proteins and 6428 phospho-sites were identified in A549-ACE2 cells after infection with SARS-CoV-2. The differential proteins here identified revealed that A549-ACE2 cells undergo a time-dependent regulation of essential processes, delineating the precise intervention of the cellular machinery by the viral proteins. From this mechanistic background and by applying machine learning modeling, 29 differential proteins were selected and detected in the serum of COVID-19 patients, 14 of which showed promising prognostic capacity. Targeting these proteins and the protein kinases responsible for the reported phosphorylation changes may provide efficient alternative strategies for the clinical management of COVID-19.

Indexed as

Blood ProteinsCOVID-19ProteomeProteomicsSARS-CoV-2A549 CellsAngiotensin-Converting Enzyme 2HumansMachine LearningPhosphoproteinsPhosphorylationACE2 protein, humanAngiotensin-Converting Enzyme 2Blood ProteinsPhosphoproteinsProteomeCOVID-19machine learningproteomicsSARS-CoV-2

Identifiers

PMID39593238
PMCPMC11705369

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.