Stachler Elyse, Gnirke Andreas, McMahon Kyle, Gomez Michael, Stenson Liam, Guevara-Reyes Charelisse, Knoll Hannah, Hill Toni, Hill Sellers, Messer Katelyn S, Arizti-Sanz Jon, Albeez Fatinah, Curtis Elizabeth, Samani Pedram, Wewior Natalia, O'Connor David H, Vuyk William, Khoury Sophia, Schnizlein Matthew K, Rockey Nicole C, Broemmel Zachariah, Mina Michael, Madoff Lawrence C, Wohl Shirlee, O'Connor Lorraine, Brown Catherine M, Ozonoff Al, Park Daniel J, MacInnis Bronwyn L, Sabeti Pardis C
Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.
University of Puerto Rico - Rio Piedras, San Juan, Puerto Rico, USA.
medRxiv. 2024 Dec 5:2024.12.04.24318491. doi: 10.1101/2024.12.04.24318491.
Highly Pathogenic Avian Influenza strain H5N1 has caused a multi-state outbreak among US dairy cattle, spreading across 15 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 from 20 states for methods development, we found that H5N1 concentrations by digital PCR strongly correlated with qPCR cycle threshold (Ct) values, with dPCR exhibiting greater sensitivity. We also found that metagenomic sequencing after hybrid selection was best for higher concentration samples while amplicon sequencing performs best for lower concentrations. By establishing these methods, we were able to support the creation of a statewide surveillance program to test bulk milk samples monthly from all cattle dairy farms within Massachusetts, which remain negative to date. The methods, workflow, and recommendations described here provide a framework for others aiming to conduct H5N1 surveillance efforts.
高致病性禽流感H5N1毒株已在美国奶牛中引发多州疫情，自疫情爆发以来已蔓延至15个州，感染了数百个牛群。我们迅速开发并优化了基于PCR的检测方法和测序方案，以支持H5N1分子监测。利用来自20个州的214份零售牛奶进行方法开发，我们发现数字PCR检测到的H5N1浓度与qPCR循环阈值（Ct）值密切相关，数字PCR表现出更高的灵敏度。我们还发现，杂交选择后的宏基因组测序最适合高浓度样本，而扩增子测序对低浓度样本效果最佳。通过建立这些方法，我们得以支持创建一个全州范围的监测计划，每月对马萨诸塞州所有奶牛场的散装牛奶样本进行检测，迄今为止这些样本均为阴性。本文所述的方法、工作流程和建议为其他旨在开展H5N1监测工作的人员提供了一个框架。
