Dynamic label-free analysis of SARS-CoV-2 infection reveals virus-induced subcellular remodeling

Nell Saunders, Blandine Monel, Nadège Cayet, Lorenzo Archetti, Hugo Moreno, Alexandre Jeanne, Agathe Marguier, Julian Buchrieser, Timothy Wai, Olivier Schwartz () and Mathieu Fréchin ()
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Nell Saunders: Université Paris Cité, CNRS
Blandine Monel: Université Paris Cité, CNRS
Nadège Cayet: Ultrastructural Bioimaging Unit
Lorenzo Archetti: Nanolive SA
Hugo Moreno: Nanolive SA
Alexandre Jeanne: Nanolive SA
Agathe Marguier: Nanolive SA
Julian Buchrieser: Université Paris Cité, CNRS
Timothy Wai: Université Paris Cité, CNRS
Olivier Schwartz: Université Paris Cité, CNRS
Mathieu Fréchin: Nanolive SA

Nature Communications, 2024, vol. 15, issue 1, 1-15

Abstract: Abstract Assessing the impact of SARS-CoV-2 on organelle dynamics allows a better understanding of the mechanisms of viral replication. We combine label-free holotomographic microscopy with Artificial Intelligence to visualize and quantify the subcellular changes triggered by SARS-CoV-2 infection. We study the dynamics of shape, position and dry mass of nucleoli, nuclei, lipid droplets and mitochondria within hundreds of single cells from early infection to syncytia formation and death. SARS-CoV-2 infection enlarges nucleoli, perturbs lipid droplets, changes mitochondrial shape and dry mass, and separates lipid droplets from mitochondria. We then used Bayesian network modeling on organelle dry mass states to define organelle cross-regulation networks and report modifications of organelle cross-regulation that are triggered by infection and syncytia formation. Our work highlights the subcellular remodeling induced by SARS-CoV-2 infection and provides an Artificial Intelligence-enhanced, label-free methodology to study in real-time the dynamics of cell populations and their content.

Date: 2024
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DOI: 10.1038/s41467-024-49260-7

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