tetano
Editor, Senior Moderator
Emerg Infect Dis
. 2025 Mar 26;31(13).
doi: 10.3201/eid3113.250087. Online ahead of print.
Establishing Methods to Monitor Influenza (A)H5N1 Virus in Dairy Cattle Milk, Massachusetts, USA
Elyse Stachler, Andreas Gnirke, Kyle McMahon, Michael Gomez, Liam Stenson, Charelisse Guevara-Reyes, Hannah Knoll, Toni Hill, Sellers Hill, Katelyn S Messer, Jon Arizti-Sanz, Fatinah Albeez, Elizabeth Curtis, Pedram Samani, Natalia Wewior, David H O'Connor, William Vuyk, Sophia E Khoury, Matthew K Schnizlein, Nicole C Rockey, Zachariah Broemmel, Michael Mina, Lawrence C Madoff, Shirlee Wohl, Lorraine O'Connor, Catherine M Brown, Al Ozonoff, Daniel J Park, Bronwyn L MacInnis, Pardis C Sabeti
Highly pathogenic avian influenza A(H5N1) virus has caused a multistate outbreak among US dairy cattle, spreading across 16 states and infecting hundreds of herds since its onset. We rapidly developed and optimized PCR-based detection assays and sequencing protocols to support H5N1 molecular surveillance. Using 214 retail milk samples from 20 states for methods development, we found that H5N1 virus concentrations by digital PCR strongly correlated with quantitative PCR cycle threshold values; digital PCR exhibited greater sensitivity. Metagenomic sequencing after hybrid selection was best for higher concentration samples, whereas amplicon sequencing performed best for lower concentrations. By establishing these methods, we were able to support the creation of a statewide surveillance program to perform monthly testing of bulk milk samples from all dairy cattle farms in Massachusetts, USA, which remain negative to date. The methods, workflow, and recommendations described provide a framework for others aiming to conduct H5N1 surveillance efforts.
Keywords: H5N1 subtype; PCR; United States; cattle; disease outbreak; farms; influenza; influenza A virus; milk; public health; public health surveillance; viral RNA; viruses; workflow.
. 2025 Mar 26;31(13).
doi: 10.3201/eid3113.250087. Online ahead of print.
Establishing Methods to Monitor Influenza (A)H5N1 Virus in Dairy Cattle Milk, Massachusetts, USA
Elyse Stachler, Andreas Gnirke, Kyle McMahon, Michael Gomez, Liam Stenson, Charelisse Guevara-Reyes, Hannah Knoll, Toni Hill, Sellers Hill, Katelyn S Messer, Jon Arizti-Sanz, Fatinah Albeez, Elizabeth Curtis, Pedram Samani, Natalia Wewior, David H O'Connor, William Vuyk, Sophia E Khoury, Matthew K Schnizlein, Nicole C Rockey, Zachariah Broemmel, Michael Mina, Lawrence C Madoff, Shirlee Wohl, Lorraine O'Connor, Catherine M Brown, Al Ozonoff, Daniel J Park, Bronwyn L MacInnis, Pardis C Sabeti
- PMID: 40138725
- DOI: 10.3201/eid3113.250087
Highly pathogenic avian influenza A(H5N1) virus has caused a multistate outbreak among US dairy cattle, spreading across 16 states and infecting hundreds of herds since its onset. We rapidly developed and optimized PCR-based detection assays and sequencing protocols to support H5N1 molecular surveillance. Using 214 retail milk samples from 20 states for methods development, we found that H5N1 virus concentrations by digital PCR strongly correlated with quantitative PCR cycle threshold values; digital PCR exhibited greater sensitivity. Metagenomic sequencing after hybrid selection was best for higher concentration samples, whereas amplicon sequencing performed best for lower concentrations. By establishing these methods, we were able to support the creation of a statewide surveillance program to perform monthly testing of bulk milk samples from all dairy cattle farms in Massachusetts, USA, which remain negative to date. The methods, workflow, and recommendations described provide a framework for others aiming to conduct H5N1 surveillance efforts.
Keywords: H5N1 subtype; PCR; United States; cattle; disease outbreak; farms; influenza; influenza A virus; milk; public health; public health surveillance; viral RNA; viruses; workflow.