A single mutation in dairy cow-associated H5N1 viruses increases receptor binding breadth

Clade 2.3.4.4b H5N1 is causing an unprecedented outbreak in dairy cows in the United States. To understand if recent H5N1 viruses are changing their receptor use, we screened recombinant hemagglutinin (HA) from historical and recent 2.3.4.4b H5N1 viruses for binding to distinct glycans bearing terminal sialic acids using a glycan microarray. We find that H5 from A/Texas/37/2024, an isolate from the dairy cow outbreak, has increased binding breadth to core glycans bearing terminal α2,3 sialic acids, the avian receptor, compared to historical and recent 2.3.4.4b H5N1 viruses. We do not observe any binding to α2,6 sialic acids, the receptor used by human seasonal influenza viruses. Using molecular dynamics and a cryo-EM structure of A/Texas/37/2024 H5, we show A/Texas/37/2024 H5 is more flexible within the receptor-binding site compared to a 2.3.4.4b H5 from 2022. We identify a single mutation outside of the receptor binding site, T199I, is responsible for increased binding breadth, as it increases receptor binding site flexibility. Together, these data show recent H5N1 viruses are evolving increased receptor binding breadth which could impact the host range and cell types infected with H5N1.

Authors

Institutions

Publication Details

Journal
Nature Communications
Published
2024-12-30
DOI
https://doi.org/10.1038/s41467-024-54934-3
Citations
52
Primary Topic
Influenza Virus Research Studies
Type
article
Field-Weighted Citation Impact
20.10

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A single mutation in dairy cow-associated H5N1 viruses increases receptor binding breadth

Marina R. Good, Monica L. Fernández‐Quintero, Jenna J. Guthmiller, Julianna Han et al.
52 citations
Nature Communications
Influenza Virus Research Studies
20.10
article

A single mutation in dairy cow-associated H5N1 viruses increases receptor binding breadth

Marina R. Good, Monica L. Fernández‐Quintero, Jenna J. Guthmiller, Julianna Han, Andrew B. Ward, Alesandra J. Rodriguez, Wei Ji
article en
52 citations

Abstract

Clade 2.3.4.4b H5N1 is causing an unprecedented outbreak in dairy cows in the United States. To understand if recent H5N1 viruses are changing their receptor use, we screened recombinant hemagglutinin (HA) from historical and recent 2.3.4.4b H5N1 viruses for binding to distinct glycans bearing terminal sialic acids using a glycan microarray. We find that H5 from A/Texas/37/2024, an isolate from the dairy cow outbreak, has increased binding breadth to core glycans bearing terminal α2,3 sialic acids, the avian receptor, compared to historical and recent 2.3.4.4b H5N1 viruses. We do not observe any binding to α2,6 sialic acids, the receptor used by human seasonal influenza viruses. Using molecular dynamics and a cryo-EM structure of A/Texas/37/2024 H5, we show A/Texas/37/2024 H5 is more flexible within the receptor-binding site compared to a 2.3.4.4b H5 from 2022. We identify a single mutation outside of the receptor binding site, T199I, is responsible for increased binding breadth, as it increases receptor binding site flexibility. Together, these data show recent H5N1 viruses are evolving increased receptor binding breadth which could impact the host range and cell types infected with H5N1.

Nature CommunicationsVol. 15(1)
Scripps Research Institute (US), University of Colorado Anschutz Medical Campus (US)
Howard Hughes Medical Institute, American Heart Association, National Institute of Allergy and Infectious Diseases
Good health and well-being
Openalex Percentile: Top 0%
Influenza Virus Research Studies
20.10
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.