Publikationsdatenbank

Multi-proteomic profiling of the varicella-zoster virus–host interface reveals host susceptibilities to severe infection (2025)

Art

Zeitschriftenartikel / wissenschaftlicher Beitrag

Autoren

Girault, Virginie

Stukalov, Alexey

Carter-Timofte, Madalina Elena

Hertzog, Jonny

Verin, Melissa

Austen, Katharina

Haas, Darya A.

Oubraham, Lila

Piras, Antonio

Maidl, Susanne

Öllinger, Rupert

Rad, Roland

Protzer, Ulrike

Kaufer, Benedikt B. (WE 5)

Lebbink, Robert J.

Rehwinkel, Jan

Mogensen, Trine H.

Pichlmair, Andreas

Quelle

Nature microbiology

Bandzählung: 10

Heftzählung: 8

Seiten: 2048 – 2072

ISSN: 2058-5276

Sprache

Englisch

Verweise

URL (Volltext): https://www.nature.com/articles/s41564-025-02068-7

DOI: 10.1038/s41564-025-02068-7

Pubmed: 40739040

Kontakt

Institut für Virologie

Robert-von-Ostertag-Str. 7-13
14163 Berlin
+49 30 838 51833
virologie@vetmed.fu-berlin.de

Abstract / Zusammenfassung

Varicella-zoster virus (VZV) infects most humans and causes chickenpox, shingles and central nervous system pathologies. The molecular basis for these phenotypes remains elusive. Here we conducted a multi-proteomic survey on 64 individual VZV proteins and infection-induced perturbations in a neuronal cell line, identifying 900 interactors and 3,618 regulated host proteins. Data integration suggested molecular functions of viral proteins, such as a mechanism for the ORF61-mediated IFI16 degradation via the recruitment of E3 ligase co-factors. Moreover, we identified proviral host factors (MPP8 and ZNF280D) as potential targets to limit infection. Integration of exome sequencing analysis from patients with VZV-associated central nervous system pathologies identified nephrocystin 4 as a viral restriction factor, and its S862N variant, which showed reduced activity and decreased binding to the regulatory proteins 14-3-3. Collectively, our study provides a comprehensive herpesvirus-host interface resource, which aids our understanding of disease-associated molecular perturbations and data-driven identification of antiviral treatment options.