Evidence map›Paper›PMID 39147987›Full record

ArticleCellular and molecular life sciences : CMLS2024

SARS-CoV2 infection in whole lung primarily targets macrophages that display subset-specific responses.

Thien-Phong Vu Manh, Carla Gouin, Julien De Wolf, Luc Jouneau, Florentina Pascale, Claudia Bevilacqua, Meriadeg Ar Gouilh, Bruno Da Costa, Christophe Chevalier, Matthieu Glorion and 10 more

Abstract read
In one paragraph

Article in Cellular and molecular life sciences : CMLS, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Single-Cell Insights Into Macrophage Subtypes in Pulmonary Infections.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Review
  5. 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

20 authors.

Thien-Phong Vu ManhAix-Marseille University, CNRS, INSERM, CIML, Centre d'Immunologie de Marseille-Luminy, Turing Center for Living Systems, 13009, Marseille, France. thien-phong.vu-manh@cnrs.fr.
Carla Gouin *Université Paris-Saclay, INRAE, UVSQ, VIM, 78350, Jouy-en-Josas, France.
Julien De Wolf *Université Paris-Saclay, INRAE, UVSQ, VIM, 78350, Jouy-en-Josas, France.
Luc Jouneau *Université Paris-Saclay, INRAE, UVSQ, VIM, 78350, Jouy-en-Josas, France.
Florentina PascaleUniversité Paris-Saclay, INRAE, UVSQ, VIM, 78350, Jouy-en-Josas, France.
Claudia BevilacquaUniversité Paris-Saclay, INRAE, AgroParisTech, GABI, 78350, Jouy-en-Josas, France.
Meriadeg Ar GouilhDepartment of Virology, Univ Caen Normandie, Dynamicure INSERM UMR 1311, CHU Caen, 14000, Caen, France.
Bruno Da CostaUniversité Paris-Saclay, INRAE, UVSQ, VIM, 78350, Jouy-en-Josas, France.
Christophe ChevalierUniversité Paris-Saclay, INRAE, UVSQ, VIM, 78350, Jouy-en-Josas, France.
Matthieu GlorionUniversité Paris-Saclay, INRAE, UVSQ, VIM, 78350, Jouy-en-Josas, France.
Laurent HannoucheAix-Marseille University, CNRS, INSERM, CIML, Centre d'Immunologie de Marseille-Luminy, Turing Center for Living Systems, 13009, Marseille, France.
Céline UrienUniversité Paris-Saclay, INRAE, UVSQ, VIM, 78350, Jouy-en-Josas, France.
Jérôme EstephanUniversité Paris-Saclay, INRAE, UVSQ, VIM, 78350, Jouy-en-Josas, France.
Antoine MagnanUniversité Paris-Saclay, INRAE, UVSQ, VIM, 78350, Jouy-en-Josas, France.
Morgan Le GuenUniversité Paris-Saclay, INRAE, UVSQ, VIM, 78350, Jouy-en-Josas, France.
Quentin MarquantUniversité Paris-Saclay, INRAE, UVSQ, VIM, 78350, Jouy-en-Josas, France.
Delphyne DescampsUniversité Paris-Saclay, INRAE, UVSQ, VIM, 78350, Jouy-en-Josas, France.
Marc DalodAix-Marseille University, CNRS, INSERM, CIML, Centre d'Immunologie de Marseille-Luminy, Turing Center for Living Systems, 13009, Marseille, France.
Isabelle Schwartz-CornilUniversité Paris-Saclay, INRAE, UVSQ, VIM, 78350, Jouy-en-Josas, France. Isabelle.schwartz@inrae.fr.ORCID http://orcid.org/0000-0002-3485-1765
Edouard SageUniversité Paris-Saclay, INRAE, UVSQ, VIM, 78350, Jouy-en-Josas, France.

Funding

Fondation pour la Recherche Médicale selection by the Flash ANR COVID-19 call
6 · The paper itself

Abstract

Deciphering the initial steps of SARS-CoV-2 infection, that influence COVID-19 outcomes, is challenging because animal models do not always reproduce human biological processes and in vitro systems do not recapitulate the histoarchitecture and cellular composition of respiratory tissues. To address this, we developed an innovative ex vivo model of whole human lung infection with SARS-CoV-2, leveraging a lung transplantation technique. Through single-cell RNA-seq, we identified that alveolar and monocyte-derived macrophages (AMs and MoMacs) were initial targets of the virus. Exposure of isolated lung AMs, MoMacs, classical monocytes and non-classical monocytes (ncMos) to SARS-CoV-2 variants revealed that while all subsets responded, MoMacs produced higher levels of inflammatory cytokines than AMs, and ncMos contributed the least. A Wuhan lineage appeared to be more potent than a D614G virus, in a dose-dependent manner. Amidst the ambiguity in the literature regarding the initial SARS-CoV-2 cell target, our study reveals that AMs and MoMacs are dominant primary entry points for the virus, and suggests that their responses may conduct subsequent injury, depending on their abundance, the viral strain and dose. Interfering on virus interaction with lung macrophages should be considered in prophylactic strategies.

Indexed as

COVID-19CytokinesLungMacrophagesMacrophages, AlveolarSARS-CoV-2FemaleHumansMaleMiddle AgedMonocytesSingle-Cell AnalysisCytokines10X genomicsAzimuth softwareEx vivo lung perfusionViral nebulization

Identifiers

PMID39147987
PMCPMC11335275

What OpenQuestion holds

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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.