Biology subjects

Ceri, S.

Publications and source records attributed to Ceri, S..

8 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↗

bioRxiv2025

Multi-scale early warning system for influenza A spillovers

Spillovers of Influenza A viruses into farmed animals and humans have the potential to trigger epidemics or even global pandemics. We introduce FluWarning, a highly efficient and elegant computational method based on anomaly detection of codon bias and dinucleotide composition for early flagging of divergent viral HA segments. Applied to H1N1 specimens collected between 2008-2009, FluWarning accurately identifies the emergence of pdm09 - the virus that caused the 2009 flu pandemic; warnings precede the observed progression of the pandemic. Applied to H5N1 specimens collected between 2019 and 2025, FluWarning flagged the emergence of the B3.13 genotype, linked to a spillover event in dairy cows in the United States. In summary, FluWarning is an effective multi-scale warning system for IAVs, detecting spillovers with few available sequences. One-Sentence SummaryEarly detection of zoonoses using a few viral sequences is critical for the timely implementation of mitigation strategies.

bioinformatics↗

bioRxiv2024

The molecular basis of the anticancer effect of statins

Statins, one of the most used class of cardiovascular drugs with the primary function of reducing blood cholesterol levels, exert their effect by inhibiting the enzyme HMG-CoA reductase, the key player in cholesterol biosynthesis. While the primary indication for statins is the prevention of cardiovascular diseases, there has been growing interest in their potential anticancer effects. However, the current evidence on these effects is largely based on epidemiological observations and preclinical research, not yet substantiated by knowledge of the mechanisms behind it. Here we show that statins have an anticancer effect as they exploit the principle of Synthetic Lethality, a concept in which the combination of two non-lethal genetic or molecular events results in cell death or impairment. When either of these events occurs alone, it is not lethal, but when they happen coupled, they create a lethal condition for the cell. In this work we report that statins emerged from a computational data analysis that we performed on approximately 37,000 synthetic lethality couples. We performed this analysis to select repurposable drugs that could target genes involved in Synthetic Lethality couples with metastatic genes. We validated our discovery in vitro by drug tests performed on cell lines derived from cancers of the breast, ovary, and cervix. Our data-driven drug repurposing strategy allowed us to understand the molecular basis of the anticancer effect of statins, a discovery which can be directly translated into practical clinical applications in oncology.

cancer biology↗

bioRxiv2023

Data-driven recombination detection in viral genomes

Recombination is a key molecular mechanism for the evolution and adaptation of viruses. The first recombinant SARS-CoV-2 genomes were recognized in 2021; as of today, more than ninety SARS-CoV-2 lineages are designated as recombinant. In the wake of the COVID-19 pandemic, several methods for detecting recombination in SARS-CoV-2 have been proposed; however, none could faithfully confirm manual analyses by experts in the field. We hereby present RecombinHunt, a novel, automated method for the identification of recombinant/mosaic genomes purely based on a data-driven approach. RecombinHunt compares favorably with other state-of-the-art methods and recognizes recombinant SARS-CoV-2 genomes (or lineages) with one or two breakpoints with high accuracy, within reduced turn-around times and small discrepancies with respect to the expert manually-curated standard nomenclature. Strikingly, applied to the complete collection of viral sequences from the recent monkeypox epidemic, RecombinHunt identifies recombinant viral genomes in high concordance with manually curated analyses by experts, suggesting that our approach is robust and can be applied to any epidemic/pandemic virus. In conclusion, RecombinHunt represents a breakthrough in the detection of recombinant viral lineages in pandemic/epidemic scenarios and could substantially improve/advance community-based approaches for the detection of recombinant viral genomes based on phylogenetic analyses.

bioinformatics↗

bioRxiv2021

Analysis of amino acid change dynamics reveals SARS-CoV-2 variant emergence

Since its emergence in late 2019, the diffusion of SARS-CoV-2 is associated with the evolution of its viral genome1,2. The co-occurrence of specific amino acid changes, collectively named virus variant, requires scrutiny (as variants may hugely impact the agents transmission, pathogenesis, or antigenicity); variant evolution is studied using phylogenetics3-6. Yet, never has this problem been tackled by digging into data with ad hoc analysis techniques. Here we show that the emergence of variants can in fact be traced through data-driven methods, further capitalizing on the value of large collections of SARS-CoV-2 sequences. For all countries with sufficient data, we compute weekly counts of amino acid changes, unveil time-varying clusters of changes with similar - rapidly growing - dynamics, and then follow their evolution. Our method succeeds in timely associating clusters to variants of interest/concern, provided their change composition is well characterized. This allows us to detect variants emergence, rise, peak, and eventual decline under competitive pressure of another variant. Our early warning system, exclusively relying on deposited sequences, shows the power of big data in this context, and concurs to calling for the wide spreading of public SARS-CoV-2 genome sequencing for improved surveillance and control of the COVID-19 pandemic.

bioinformatics↗

bioRxiv2020

ViruSurf: an integrated database to investigate viral sequences

ViruSurf, available at http://gmql.eu/virusurf/, is a large public database of viral sequences and integrated and curated metadata from heterogeneous sources (GenBank, COG-UK and NMDC); it also exposes computed nucleotide and amino acid variants, called from original sequences. A GISAID-specific ViruSurf database, available at http://gmql.eu/virusurf_gisaid/, offers a subset of these functionalities. Given the current pandemic outbreak, SARS-CoV-2 data are collected from the four sources; but ViruSurf contains other virus species harmful to humans, including SARS-CoV, MERS-CoV, Ebola, and Dengue. The database is centered on sequences, described from their biological, technological, and organizational dimensions. In addition, the analytical dimension characterizes the sequence in terms of its annotations and variants. The web interface enables expressing complex search queries in a simple way; arbitrary search queries can freely combine conditions on attributes from the four dimensions, extracting the resulting sequences. Several example queries on the database confirm and possibly improve results from recent research papers; results can be recomputed over time and upon selected populations. Effective search over large and curated sequence data may enable faster responses to future threats that could arise from new viruses.

genomics↗

bioRxiv2020

Empowering Virus Sequences Research through Conceptual Modeling

The pandemic outbreak of the coronavirus disease has attracted attention towards the genetic mechanisms of viruses. We hereby present the Viral Conceptual Model (VCM), centered on the virus sequence and described from four perspectives: biological (virus type and hosts/sample), analytical (annotations and variants), organizational (sequencing project) and technical (experimental technology). VCM is inspired by GCM, our previously developed Genomic Conceptual Model, but it introduces many novel concepts, as viral sequences significantly differ from human genomes. When applied to SARS-CoV2 virus, complex conceptual queries upon VCM are able to replicate the search results of recent articles, hence demonstrating huge potential in supporting virology research. In addition to VCM, we also illustrate the data dictionary for patients phenotype used by the COVID-19 Host Genetic Initiative. Our effort is part of a broad vision: availability of conceptual models for both human genomics and viruses will provide important opportunities for research, especially if interconnected by the same human being, playing the role of virus host as well as provider of genomic and phenotype information.

genomics↗

bioRxiv2019

The CTCF Anatomy of Topologically Associating Domains

Topologically associated domains (TADs) are defined as regions of self-interaction. To date, it is unclear how to reconcile TAD structure with CTCF site orientation, which is known to coordinate chromatin loops anchored by Cohesin rings at convergent CTCF site pairs. We first approached this problem by 4C analysis of the FKBP5 locus. This uncovered a CTCF loop encompassing FKBP5 but not its entire TAD. However, adjacent CTCF sites were able to form back-up loops and these were located at TAD boundaries. We then analysed the spatial distribution of CTCF patterns along the genome together with a boundary identity conservation gradient obtained from primary blood cells. This revealed that divergent CTCF sites are enriched at boundaries and that convergent CTCF sites mark the interior of TADs. This conciliation of CTCF site orientation and TAD structure has deep implications for the further study and engineering of TADs and their boundaries.

genomics↗