Herve, A. | Search bioRxiv

bioRxiv2025

Protein and genomic language models chart a vast landscape of antiphage defenses

The bacterial pangenome encodes an immense array of antiphage systems, yet much of their diversity remains uncharted. In this study, we developed language models to predict novel antiphage proteins in two ways: first via fine-tuning ESM2, a protein language model capable of detecting distant homology to known defense proteins, second via a genomic language model with ALBERT architecture which predicts defensive function based on genomic context. We demonstrate that applying these approaches to Actinomycetota - a phylum largely unexplored for antiphage defenses, can accurately predict previously unknown functional defense mechanisms, leading to the discovery and experimental validation of six defense systems with novel antiphage proteins. Analysis of over 30,000 bacterial genomes predicted more than 45,000 uncharacterized protein families potentially involved in antiphage defense, underscoring the vast, untapped diversity of these systems.

microbiology↗

bioRxiv2021

Systematic and quantitative view of the antiviral arsenal of prokaryotes

Facing the abundance and diversity of phages, bacteria have developed multiple anti-phage mechanisms. In the past three years, the number of known anti-phage mechanisms has been expanded by at least 5-fold rendering our view of prokaryotic immunity obsolete. Most anti-phage systems have been studied as standalone mechanisms, however many examples demonstrate strains encode not one but several anti-viral mechanisms. How these different systems integrate into an anti-viral arsenal at the strain level remains to be elucidated. Much could be learned from establishing fundamental description of features such as the number and diversity of anti-phage systems encoded in a given genome. To address this question, we developed DefenseFinder, a tool that automatically detects known anti-phage systems in prokaryotic genomes. We applied DefenseFinder to >20 000 fully sequenced genomes, generating a systematic and quantitative view of the anti-viral arsenal of prokaryotes. We show prokaryotic genomes encode on average five anti-phage systems from three different families of systems. This number varies drastically from one strain to another and is influenced by the genome size and the number of prophages encoded. Distributions of different systems are also very heterogenous with some systems being enriched in prophages and in specific clades. Finally, we provide a detailed comparison of the anti-viral arsenal of 15 common bacterial species, revealing drastic differences in anti-viral strategies. Overall, our work provides a free and open-source software, available as a command line tool or, on a webserver. It allows the rapid detection of anti-phage systems, enables a comprehensive description of the anti-viral arsenal of prokaryotes and paves the way for large scale genomics study in the field of anti-phage defense.

microbiology↗