Abstract Title
Empowering surveillance of H5N1 mutations with animal and public health impacts using FluMut
Abstract
The recent global spread and host range expansion of clade 2.3.4.4b highly pathogenic avian influenza (HPAI) viruses of the H5 subtype has led to an increase in reports of mammalian infections. This represents a warning sign for the emergence of viruses with increased pandemic potential. In this scenario, real-time genomic surveillance is crucial to promptly identify variants with possible increased zoonotic risk. However, such analyses are often challenging due to the lack of updated molecular marker databases and software suited for analyses of large datasets.
To fill this gap, we developed FluMut (https://github.com/izsvenezie-virology/FluMut), an open-source bioinformatics tool that efficiently analyses large quantities of nucleotide sequences to identify molecular markers with potential impact on H5N1 virus phenotypes. This cross-platform software can be installed as a basic command-line utility or a user-friendly graphical interface, thus accommodating different levels of computational expertise. The output of the analysis consists of several tables listing the detected markers for each input sequence and the associated biological effects. FluMut’s algorithm relies on an extensive hand-curated and literature-based database of mutations with known correlations to host adaptation, increased virulence, or antiviral resistance. This dataset will be kept up-to-date as new markers are described in novel studies, as well as by integrating submissions from users who are encouraged to report additional markers of interest.
FluMut fills a critical gap for monitoring the viral evolution and pandemic potential of HPAI H5N1 mutations. With future updates, FluMut will be extended to all influenza subtypes.
To fill this gap, we developed FluMut (https://github.com/izsvenezie-virology/FluMut), an open-source bioinformatics tool that efficiently analyses large quantities of nucleotide sequences to identify molecular markers with potential impact on H5N1 virus phenotypes. This cross-platform software can be installed as a basic command-line utility or a user-friendly graphical interface, thus accommodating different levels of computational expertise. The output of the analysis consists of several tables listing the detected markers for each input sequence and the associated biological effects. FluMut’s algorithm relies on an extensive hand-curated and literature-based database of mutations with known correlations to host adaptation, increased virulence, or antiviral resistance. This dataset will be kept up-to-date as new markers are described in novel studies, as well as by integrating submissions from users who are encouraged to report additional markers of interest.
FluMut fills a critical gap for monitoring the viral evolution and pandemic potential of HPAI H5N1 mutations. With future updates, FluMut will be extended to all influenza subtypes.
Co-Author(s)
Edoardo Giussani¹, Alessandro Sartori¹, Angela Salomoni¹, Lara Cavicchio¹, Cristian de Battisti¹, Ambra Pastori¹, Maria Varotto¹, Bianca Zecchin¹, Joseph Hughes², Isabella Monne¹, Alice Fusaro¹
¹ Istituto Zooprofilattico Sperimentale delle Venezie, viale dell'Università, 10, Legnaro (PD), Italy.
² MRC-University of Glasgow Centre for Virus Research, 464 Bearsden Road, Glasgow, United Kingdom.
Abstract Category
Avian influenza in mammals, pandemic preparedness, and one health