Evidence map›Paper›PMID 32522207›Full record

ArticleJournal of translational medicine2020

COVID-19: viral-host interactome analyzed by network based-approach model to study pathogenesis of SARS-CoV-2 infection.

Francesco Messina, Emanuela Giombini, Chiara Agrati, Francesco Vairo, Tommaso Ascoli Bartoli, Samir Al Moghazi, Mauro Piacentini, Franco Locatelli, Gary Kobinger, Markus Maeurer and 5 more

Open access · goldAbstract read
In one paragraph

Article in Journal of translational medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 54 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
54citing papers in PubMed, 1 pooled it
2.6field-weighted citation impact, top 6% 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, 1 synthesis or guideline pooled it, 113 citations in OpenAlex.

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  13. Prediction of viral-host interactions of COVID-19 by computational methods.Chemometrics and intelligent laboratory systems : an international journal sponsored by the Chemometrics Society · 2022
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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 5 countries.

Francesco MessinaNational Institute for Infectious Diseases "Lazzaro Spallanzani" IRCCS, Rome, Italy.
Emanuela GiombiniNational Institute for Infectious Diseases "Lazzaro Spallanzani" IRCCS, Rome, Italy.
Chiara AgratiNational Institute for Infectious Diseases "Lazzaro Spallanzani" IRCCS, Rome, Italy.
Francesco VairoNational Institute for Infectious Diseases "Lazzaro Spallanzani" IRCCS, Rome, Italy.
Tommaso Ascoli BartoliNational Institute for Infectious Diseases "Lazzaro Spallanzani" IRCCS, Rome, Italy.
Samir Al MoghaziNational Institute for Infectious Diseases "Lazzaro Spallanzani" IRCCS, Rome, Italy.
Mauro PiacentiniNational Institute for Infectious Diseases "Lazzaro Spallanzani" IRCCS, Rome, Italy.
Franco LocatelliDepartment of Pediatric Hematology and Oncology, IRCCS Ospedale Pediatrico Bambino Gesu, Rome, Italy.
Gary KobingerDépartement de Microbiologie-Infectiologie et d'Immunologie, Université Laval, Quebec, QC, Canada.
Markus MaeurerImmunoSurgery Unit, Champalimaud Centre for the Unknown, Lisbon, Portugal.
Alimuddin ZumlaDepartment of Infection, Division of Infection and Immunity, University College London, London, UK.
Maria R CapobianchiNational Institute for Infectious Diseases "Lazzaro Spallanzani" IRCCS, Rome, Italy. maria.capobianchi@inmi.it.ORCID http://orcid.org/0000-0003-3465-0071
Francesco Nicola LauriaNational Institute for Infectious Diseases "Lazzaro Spallanzani" IRCCS, Rome, Italy.
Giuseppe IppolitoNational Institute for Infectious Diseases "Lazzaro Spallanzani" IRCCS, Rome, Italy.
COVID 19 INMI Network Medicine for IDs Study Group
Istituto Nazionale per le Malattie Infettive Lazzaro Spallanzani · ITChampalimaud Foundation · PTUniversity College London Hospitals NHS Foundation Trust · GBUniversity of Rome Tor Vergata · ITUniversité Laval · CA

Funding

Horizon 2020 Framework Programme PANDORA-ID-NETMinistero della Salute Ricerca Corrente Linea 1
6 · The paper itself

Abstract

backgroundEpidemiological, virological and pathogenetic characteristics of SARS-CoV-2 infection are under evaluation. A better understanding of the pathophysiology associated with COVID-19 is crucial to improve treatment modalities and to develop effective prevention strategies. Transcriptomic and proteomic data on the host response against SARS-CoV-2 still have anecdotic character; currently available data from other coronavirus infections are therefore a key source of information.

methodsWe investigated selected molecular aspects of three human coronavirus (HCoV) infections, namely SARS-CoV, MERS-CoV and HCoV-229E, through a network based-approach. A functional analysis of HCoV-host interactome was carried out in order to provide a theoretic host-pathogen interaction model for HCoV infections and in order to translate the results in prediction for SARS-CoV-2 pathogenesis. The 3D model of S-glycoprotein of SARS-CoV-2 was compared to the structure of the corresponding SARS-CoV, HCoV-229E and MERS-CoV S-glycoprotein. SARS-CoV, MERS-CoV, HCoV-229E and the host interactome were inferred through published protein-protein interactions (PPI) as well as gene co-expression, triggered by HCoV S-glycoprotein in host cells.

resultsAlthough the amino acid sequences of the S-glycoprotein were found to be different between the various HCoV, the structures showed high similarity, but the best 3D structural overlap shared by SARS-CoV and SARS-CoV-2, consistent with the shared ACE2 predicted receptor. The host interactome, linked to the S-glycoprotein of SARS-CoV and MERS-CoV, mainly highlighted innate immunity pathway components, such as Toll Like receptors, cytokines and chemokines.

conclusionsIn this paper, we developed a network-based model with the aim to define molecular aspects of pathogenic phenotypes in HCoV infections. The resulting pattern may facilitate the process of structure-guided pharmaceutical and diagnostic research with the prospect to identify potential new biological targets.

Indexed as

Gene Regulatory NetworksHost-Pathogen InteractionsModels, BiologicalProtein Interaction MappingBetacoronavirusCoronavirus InfectionsCOVID-19HumansMembrane GlycoproteinsPandemicsPneumonia, ViralSARS-CoV-2Signal TransductionViral Envelope ProteinsMembrane GlycoproteinsViral Envelope ProteinsCoronavirus infectionSpike glycoproteinVirus–host interactome

Identifiers

PMID32522207
PMCPMC7286221
OpenAlexW3034111647

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.