Harnessing low dimensionality to visualize the antibody-virus landscape for influenza

Antibodies constitute a key line of defense against the diverse pathogens we encounter in our lives. Although the interactions between a single antibody and a single virus are routinely characterized in exquisite detail, the inherent tradeoffs between attributes such as potency and breadth remain un...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Nature Computational Science 2023-02, Vol.3 (2), p.164-173
Hauptverfasser: Einav, Tal, Creanga, Adrian, Andrews, Sarah F, McDermott, Adrian B, Kanekiyo, Masaru
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:Antibodies constitute a key line of defense against the diverse pathogens we encounter in our lives. Although the interactions between a single antibody and a single virus are routinely characterized in exquisite detail, the inherent tradeoffs between attributes such as potency and breadth remain unclear. Moreover, there is a wide gap between the discrete interactions of single antibodies and the collective behavior of antibody mixtures. Here we develop a form of antigenic cartography called a 'neutralization landscape' that visualizes and quantifies antibody-virus interactions for antibodies targeting the influenza hemagglutinin stem. This landscape transforms the potency-breadth tradeoff into a readily solvable geometry problem. With it, we decompose the collective neutralization from multiple antibodies to characterize the composition and functional properties of the stem antibodies within. Looking forward, this framework can leverage the serological assays routinely performed for influenza surveillance to analyze how an individual's antibody repertoire evolves after vaccination or infection.
ISSN:2662-8457
2662-8457
DOI:10.1038/s43588-022-00375-1