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Sponsored Artificial Intelligence: A Modern Approach, Global Edition Artificial Intelligence: A Modern Approach, Global Edition

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R. Kondor

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Open access Aug 2026

Detection and characterization of antiviral-resistant viruses during the influenza season of 2024–25

ABSTRACT During the high severity season of 2024–25, CDC with public health partners sequenced and analyzed genomes of >10,000 influenza viruses for antiviral resistance markers. Available sequence-flagged and representative viruses were tested with antivirals using in vitro assays. In the US, three oseltamivir-resistant A(H3N2) viruses had treatment-emergent neuraminidase (NA) mutations, either E119V or R292K. Oseltamivir-resistant A(H1N1)pdm09 viruses with NA-H275Y were detected in 15 states, albeit at a low frequency (0.53%). They belonged to several phylogenetic groups, with hemagglutinin (HA) subclade D.3.1 combined with either NA subclade D.1 or D.2 being most common. Based on shared sequence data, nearly all H275Y viruses from Australia, Canada, and Chile also belonged to these HA and NA subclades. Conversely, most H275Y viruses (68/81) from China belonged to HA subclade C.1.9 and NA subclade D and shared the permissive mutation R257K. Influenza polymerase acidic (PA) mutations conferring 4- to 92-fold decreased baloxavir susceptibility were detected in nine influenza A viruses. Viruses with PA-I38T showed mild attenuation of replicative fitness in three cell lines. Based on available data, NA-H275Y and PA-I38T viruses were collected from patients with no exposure to antivirals. Baseline susceptibility to all US-approved influenza antivirals remained largely unchanged compared to previous seasons. All swine-origin viruses detected in the US had adamantane resistance-conferring marker, M2-S31N, but remained susceptible to other approved antivirals. Monitoring antiviral susceptibility has substantially improved with increased sequencing capacities and bioinformatic support at public health laboratories. Information gained through influenza surveillance has been used to guide recommendations on antiviral use. IMPORTANCE Circulation of influenza viruses with reduced susceptibility to antivirals can diminish the usefulness of medications prescribed for influenza. This study informs on the prevalence of drug-resistant influenza viruses in the US during the high severity season of 2024–25. It provides information on susceptibility profile to all approved antiviral medications and on replicative fitness of representative drug-resistant viruses. Most drug-resistant viruses were collected from patients who were not exposed to antivirals indicating their ability to transmit from human to human. Whole-genome sequence (WGS)-based analysis is the cornerstone for surveillance, and numerous laboratories have been utilizing this approach. However, CDC laboratory is the only laboratory in the US conducting phenotypic testing of circulating viruses needed to confirm the outcomes of sequence-based analysis and to identify new molecular markers of resistance. Data gathered through virologic surveillance give much-needed information on drug susceptibility of influenza viruses which are used to guide recommendations on antiviral use. Circulation of influenza viruses with reduced susceptibility to antivirals can diminish the usefulness of medications prescribed for influenza. This study informs on the prevalence of drug-resistant influenza viruses in the US during the high severity season of 2024–25. It provides information on susceptibility profile to all approved antiviral medications and on replicative fitness of representative drug-resistant viruses. Most drug-resistant viruses were collected from patients who were not exposed to antivirals indicating their ability to transmit from human to human. Whole-genome sequence (WGS)-based analysis is the cornerstone for surveillance, and numerous laboratories have been utilizing this approach. However, CDC laboratory is the only laboratory in the US conducting phenotypic testing of circulating viruses needed to confirm the outcomes of sequence-based analysis and to identify new molecular markers of resistance. Data gathered through virologic surveillance give much-needed information on drug susceptibility of influenza viruses which are used to guide recommendations on antiviral use.

Mira C. Patel, Ha T. Nguyen, P. N. Q. Pascua et al. · 0 citations
Open access Aug 2026

Alignment-free prediction of cross-reactivity in influenza A (H3N2) anticipates antigenic drift

Since its introduction in 1968, Influenza A (H3N2) has undergone continuous antigenic evolution, necessitating frequent vaccine updates. To predict antigenicity and characterize antigenic drift without multiple sequence alignments, we present FluEmbed, a computational framework that leverages protein language models. FluEmbed accurately quantified the antigenic impact of viral evolution from RNA sequences, achieving strong predictive performance against hemagglutination inhibition (HI) assay titers (Spearman correlation: ρ = 0.67–0.80). FluEmbed also outperformed sequence-distance baselines (e.g., Hamming and BLOSUM62) and phylogenetic tree-based models that require sequence alignment. Using this model, we conducted in-silico mutagenesis experiments to identify site/amino acid combinations that differentially impacted antigenicity. To systematically investigate how specific mutations influence immune escape, we defined two classes of mutations: ‘constrained’, where only the most likely amino acid changes at historically mutation-prone sites were considered (thereby limiting the mutation space) and ‘unconstrained’, where all possible substitutions were allowed, providing a full exploration of potential antigenic shifts. Constrained mutations often confer limited antigenic changes, whereas unconstrained mutations exhibit greater escape potential, particularly outside the dominant viral lineages. Notably, 3C.2a was the only major lineage in which constrained and unconstrained mutations showed no significant difference (p ≈ 0.95), suggesting ongoing intra-clade competition rather than inter-lineage antigenic replacement. By enabling rapid, alignment-free antigenic prediction directly from sequence data, FluEmbed could complement traditional HI assays in real-time influenza surveillance and inform vaccine strain selection decisions.

A. Forna, Lambodhar Damodaran, C. Gunning et al. · 0 citations