New Look at RSV Infection: Tissue Clearing and 3D Imaging of the Entire Mouse Lung at Cellular Resolution.


Journal

Viruses
ISSN: 1999-4915
Titre abrégé: Viruses
Pays: Switzerland
ID NLM: 101509722

Informations de publication

Date de publication:
28 01 2021
Historique:
received: 18 12 2020
revised: 16 01 2021
accepted: 19 01 2021
entrez: 2 2 2021
pubmed: 3 2 2021
medline: 3 3 2021
Statut: epublish

Résumé

Respiratory Syncytial Virus (RSV) is the major cause of severe acute respiratory tract illness in young children worldwide and a main pathogen for the elderly and immune-compromised people. In the absence of vaccines or effective treatments, a better characterization of the pathogenesis of RSV infection is required. To date, the pathophysiology of the disease and its diagnosis has mostly relied on chest X-ray and genome detection in nasopharyngeal swabs. The development of new imaging approaches is instrumental to further the description of RSV spread, virus-host interactions and related acute respiratory disease, at the level of the entire lung. By combining tissue clearing, 3D microscopy and image processing, we developed a novel visualization tool of RSV infection in undissected mouse lungs. Whole tissue analysis allowed the identification of infected cell subtypes, based on both morphological traits and position within the cellular network. Furthermore, 3D imaging was also valuable to detect the cytoplasmic viral factories, also called inclusion bodies, a hallmark of RSV infection. Whole lung clearing and 3D deep imaging represents an unprecedented visualization method of infected lungs to allow insight into RSV pathophysiology and improve the 2D histology analyses.

Sections du résumé

BACKGROUND
Respiratory Syncytial Virus (RSV) is the major cause of severe acute respiratory tract illness in young children worldwide and a main pathogen for the elderly and immune-compromised people. In the absence of vaccines or effective treatments, a better characterization of the pathogenesis of RSV infection is required. To date, the pathophysiology of the disease and its diagnosis has mostly relied on chest X-ray and genome detection in nasopharyngeal swabs. The development of new imaging approaches is instrumental to further the description of RSV spread, virus-host interactions and related acute respiratory disease, at the level of the entire lung.
METHODS
By combining tissue clearing, 3D microscopy and image processing, we developed a novel visualization tool of RSV infection in undissected mouse lungs.
RESULTS
Whole tissue analysis allowed the identification of infected cell subtypes, based on both morphological traits and position within the cellular network. Furthermore, 3D imaging was also valuable to detect the cytoplasmic viral factories, also called inclusion bodies, a hallmark of RSV infection.
CONCLUSIONS
Whole lung clearing and 3D deep imaging represents an unprecedented visualization method of infected lungs to allow insight into RSV pathophysiology and improve the 2D histology analyses.

Identifiants

pubmed: 33525646
pii: v13020201
doi: 10.3390/v13020201
pmc: PMC7912480
pii:
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

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Auteurs

Maxence Frétaud (M)

Université Paris-Saclay, INRAE, UVSQ, VIM, 78350 Jouy-en-Josas, France.

Delphyne Descamps (D)

Université Paris-Saclay, INRAE, UVSQ, VIM, 78350 Jouy-en-Josas, France.

Daphné Laubreton (D)

Université Paris-Saclay, INRAE, UVSQ, VIM, 78350 Jouy-en-Josas, France.
CIRI, Centre International de Recherche en Infectiologie, Univ Lyon, Inserm, U1111, Université Claude Bernard Lyon 1, CNRS, UMR5308, ENS de Lyon, F-69007 Lyon, France.

Marie-Anne Rameix-Welti (MA)

Université Paris-Saclay, INSERM, Université de Versailles St. Quentin, UMR 1173 (2I), 78000 Versailles, France.
Assistance Publique Hôpitaux de Paris, Université Paris Saclay, Hôpital Ambroise Paré, Laboratoire de Microbiologie, 92100 Boulogne-Billancourt, France.

Jean-François Eléouët (JF)

Université Paris-Saclay, INRAE, UVSQ, VIM, 78350 Jouy-en-Josas, France.

Thibaut Larcher (T)

INRAE, Oniris, UMR 703 APEX, 44307 Nantes, France.

Marie Galloux (M)

Université Paris-Saclay, INRAE, UVSQ, VIM, 78350 Jouy-en-Josas, France.

Christelle Langevin (C)

Université Paris-Saclay, INRAE, UVSQ, VIM, 78350 Jouy-en-Josas, France.
INRAE, IERP, Université Paris-Saclay, 78350 Jouy-en-Josas, France.

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Classifications MeSH