Development of an Immunoassay for Highly Pathogenic Avian Influenza (H5N1) across Diverse Sample Matrices

Avian influenza of the highly pathogenic subtype H5N1 has emerged as a global health concern, becoming endemic in wild birds and increasingly transmitting to poultry, livestock, and humans. This study aimed to develop a robust immunoassay for the rapid detection of the H5N1 highly pathogenic avian influenza virus across various sample matrices, including sera, milk, eggs, and bird samples. The assay targets the hemagglutinin (HA) protein, chosen for its abundance and accessibility on the virus surface. Utilizing gold nanospheres conjugated with α-HA IgG antibodies, the assay generated distinct colorimetric signals for both negative and positive samples. The test initially demonstrated an effective colorimetric response with a limit of detection (LOD) of 0.16 nM in human serum and was further optimized for running in whole milk, exhibiting an LOD of 1.72 nM. The assay exhibited versatility across different serum types and dairy products, although high-viscosity samples like heavy cream presented challenges. Furthermore, the immunoassay successfully detected HA of H5N1 in complex sample matrices such as oral, cloacal, and fecal samples from birds. This rapid and sensitive immunoassay represents a significant advance in HPAI surveillance tools, improving prospects for real-time detection to control outbreaks.

Authors

Institutions

Publication Details

Journal
ACS Nanoscience Au
Published
2025-02-13
DOI
https://doi.org/10.1021/acsnanoscienceau.4c00072
Citations
4
Primary Topic
Influenza Virus Research Studies
Type
article
Field-Weighted Citation Impact
5.42

Funders

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

Development of an Immunoassay for Highly Pathogenic Avian Influenza (H5N1) across Diverse Sample Matrices

Miguel Zacarías Pérez Sosa, Josselyn Mata Calidonio, Kimberly Hamad‐Schifferli, D. Patel et al.
4 citations
ACS Nanoscience Au
Influenza Virus Research Studies
5.42
article

Development of an Immunoassay for Highly Pathogenic Avian Influenza (H5N1) across Diverse Sample Matrices

Miguel Zacarías Pérez Sosa, Josselyn Mata Calidonio, Kimberly Hamad‐Schifferli, D. Patel, Nichola J. Hill, Arianna I. Maddox, Jonathan B. Dain
article en
4 citations

Abstract

Avian influenza of the highly pathogenic subtype H5N1 has emerged as a global health concern, becoming endemic in wild birds and increasingly transmitting to poultry, livestock, and humans. This study aimed to develop a robust immunoassay for the rapid detection of the H5N1 highly pathogenic avian influenza virus across various sample matrices, including sera, milk, eggs, and bird samples. The assay targets the hemagglutinin (HA) protein, chosen for its abundance and accessibility on the virus surface. Utilizing gold nanospheres conjugated with α-HA IgG antibodies, the assay generated distinct colorimetric signals for both negative and positive samples. The test initially demonstrated an effective colorimetric response with a limit of detection (LOD) of 0.16 nM in human serum and was further optimized for running in whole milk, exhibiting an LOD of 1.72 nM. The assay exhibited versatility across different serum types and dairy products, although high-viscosity samples like heavy cream presented challenges. Furthermore, the immunoassay successfully detected HA of H5N1 in complex sample matrices such as oral, cloacal, and fecal samples from birds. This rapid and sensitive immunoassay represents a significant advance in HPAI surveillance tools, improving prospects for real-time detection to control outbreaks.

ACS Nanoscience AuVol. 5(2)
University of Massachusetts Boston (US)
Directorate for Biological Sciences, National Cancer Institute
Zero hunger
Openalex Percentile: Top 5%
Influenza Virus Research Studies
5.42
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.