Biology subjects

Ferrandi, E.

Publications and source records attributed to Ferrandi, E..

3 recordsLinked to original sources

bioRxiv2025

Distinctive viral genome signatures are linked to repeated mammalian spillovers of H5N1 in North America

Highly pathogenic avian influenza H5N1 rarely infects mammals. In 2024-2025, however, genotypes B3.13 and D1.1 caused two independent spillovers into U.S. dairy cattle. By analysing 26,930 complete H5N1 genomes from global surveillance, we identified 73 major viral groups, most of which show continent-specific distribution in Europe, Asia, Africa, and North America. North American viruses exhibit higher genetic diversity in specific viral segments, including variants potentially associated with mammalian adaptation. Both dairy-cattle-associated B3.13 and D1.1 genotypes originate from the same geographic macro-area, suggesting a possible regional hotspot where avian-mammalian interfaces may facilitate viral adaptation. Our findings place the U.S. outbreaks in a global framework and indicate that North American H5N1 may be predisposed to cross-species transmission. TeaserComparative genomics and geographic analyses delineate distinctive genomic features of H5N1 genotypes associated with U.S. dairy cattle spillover.

evolutionary biology↗

bioRxiv2024

A small molecule enhances arrestin-3 binding to the β2-adrenergic receptor

G protein-coupled receptor (GPCR) signaling is terminated by arrestin binding to a phosphorylated receptor. Binding propensity has been shown to be modulated by stabilizing the pre-activated state of arrestin through point mutations or C-tail truncation. Here, we hypothesize that pre-activated rotated states can be stabilized by small molecules, and this can promote binding to phosphorylation-deficient receptors, which underly a variety of human disorders. We performed virtual screening on druggable pockets identified on pre-activated conformations in Molecular Dynamics trajectories of arrestin-3, and found a compound targeting an activation switch, the back loop at the inter-domain interface. According to our model, consistent with available biochemical and structural data, the compound destabilized the ionic lock between the finger and the back loop, and enabled transition of the gate loop towards the pre-activated state, which stabilizes pre-activated inter-domain rotation. The predicted binding pocket is consistent with saturation-transfer difference NMR data indicating close contact between the piperazine moiety of the compound and C/finger loops. The compound increases in-cell arrestin-3 binding to phosphorylation-deficient and wild-type {beta}2-adrenergic receptor, but not to muscarinic M2 receptor, as verified by FRET and NanoBiT. This study demonstrates that the back loop can be targeted to modulate interaction of arrestin with phosphorylation-deficient GPCRs in a receptor-specific manner.

cell biology↗

bioRxiv2021

Unsupervised classification of SARS-CoV-2 genomic sequences uncovers hidden genetic diversity and suggests an efficient strategy for genomic surveillance

Accurate and timely monitoring of emerging genomic diversity is crucial for limiting the spread of potentially more transmissible/pathogenic strains of SARS-CoV-2. At the time of writing, over 1.8M distinct viral genome sequences have been made publicly available, and a sophisticated nomenclature system based on phylogenetic evidence and expert manual curation has allowed the relatively rapid classification of emerging lineages of potential concern. Here, we propose a complementary approach that integrates fine-grained spatiotemporal estimates of allele frequency with unsupervised clustering of viral haplotypes, and demonstrate that multiple highly frequent genetic variants, arising within large and/or rapidly expanding SARS-CoV-2 lineages, have highly biased geographic distributions and are not adequately captured by current SARS-CoV-2 nomenclature standards. Our results advocate a partial revision of current methods used to track SARS-CoV-2 genomic diversity and highlight the importance of the application of strategies based on the systematic analysis and integration of regional data. Here we provide a complementary, completely automated and reproducible framework for the mapping of genetic diversity in time and across different geographic regions, and for the prioritization of virus variants of potential concern. We believe that the approach outlined in this study will contribute to relevant advances to current genomic surveillance methods.

genomics↗