Multimodal SARS-CoV-2 interactome sketches the virus-host spatial organization

An accurate spatial representation of protein-protein interaction networks is needed to achieve a realistic and biologically relevant representation of interactomes. Here, we leveraged the spatial information included in Proximity-Dependent Biotin Identification (BioID) interactomes of SARS-CoV-2 proteins to calculate weighted distances and model the organization of the SARS-CoV-2-human interactome in three dimensions (3D) within a cell-like volume. Cell regions with viral occupancy were highlighted, along with the coordination of viral proteins exploiting the cellular machinery. Profiling physical intra-virus and virus-host contacts enabled us to demonstrate both the accuracy and the predictive value of our 3D map for direct interactions, meaning that proteins in closer proximity tend to interact physically. Several functionally important virus-host complexes were detected, and robust structural models were obtained, opening the way to structure-directed drug discovery screens. This PPI discovery pipeline approach brings us closer to a realistic spatial representation of interactomes, which, when applied to viruses or other pathogens, can provide significant information for infection. Thus, it represents a promising tool for coping with emerging infectious diseases.

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Publication Details

Journal
Communications Biology
Published
2025-03-26
DOI
https://doi.org/10.1038/s42003-025-07933-z
Citations
3
Primary Topic
Biotin and Related Studies
Type
article
Field-Weighted Citation Impact
3.45

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article

Multimodal SARS-CoV-2 interactome sketches the virus-host spatial organization

Sylvie van der Werf, Estelle Laurent, Jean‐Pascal Gimeno, Sandie Munier et al.
3 citations
Communications Biology
Biotin and Related Studies
3.45
article

Multimodal SARS-CoV-2 interactome sketches the virus-host spatial organization

Sylvie van der Werf, Estelle Laurent, Jean‐Pascal Gimeno, Sandie Munier, Stevenn Volant, Patrick Aloy, Nicolas Soler, Yves Jacob, Anastassia V. Komarova, Caroline Demeret, Mélanie Dos Santos, Payman Samavarchi‐Tehrani, Yorgos Sofianatos, Faustine Amara, Étienne Coyaud, Kamel Bachiri, Flora Donati, Mikaël Attia, Natalia Pietrosemoli, Guillaume Dugied, Yannis Rahou, Anne‐Claude Gingras, Georgios A. Pavlopoulos, Pascal Falter‐Braun
article en
3 citations

Abstract

An accurate spatial representation of protein-protein interaction networks is needed to achieve a realistic and biologically relevant representation of interactomes. Here, we leveraged the spatial information included in Proximity-Dependent Biotin Identification (BioID) interactomes of SARS-CoV-2 proteins to calculate weighted distances and model the organization of the SARS-CoV-2-human interactome in three dimensions (3D) within a cell-like volume. Cell regions with viral occupancy were highlighted, along with the coordination of viral proteins exploiting the cellular machinery. Profiling physical intra-virus and virus-host contacts enabled us to demonstrate both the accuracy and the predictive value of our 3D map for direct interactions, meaning that proteins in closer proximity tend to interact physically. Several functionally important virus-host complexes were detected, and robust structural models were obtained, opening the way to structure-directed drug discovery screens. This PPI discovery pipeline approach brings us closer to a realistic spatial representation of interactomes, which, when applied to viruses or other pathogens, can provide significant information for infection. Thus, it represents a promising tool for coping with emerging infectious diseases.

Communications BiologyVol. 8(1)
Institució Catalana de Recerca i Estudis Avançats (ES), Mount Sinai Hospital (CA), Centre National de la Recherche Scientifique (FR), Inserm (FR), Institut Pasteur (FR), Université Paris Cité (FR), Lunenfeld-Tanenbaum Research Institute (CA), Université de Lille (FR), Helmholtz Zentrum München (DE), Centre Hospitalier Universitaire de Lille (FR), Institute for Research in Biomedicine (ES), Target (Germany) (DE), Protéomique, Réponse Inflammatoire et Spectrométrie de Masse (FR), Alexander Fleming Biomedical Sciences Research Center (GR), Ludwig-Maximilians-Universität München (DE)
Foundation for the National Institutes of Health, Horizon 2020 Framework Programme
Good health and well-being
Openalex Percentile: Top 9%
Biotin and Related Studies
3.45
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