Biology subjects

Leprince, A.

Publications and source records attributed to Leprince, A..

3 recordsLinked to original sources

bioRxiv2026

Uncovering novel phage defense systems through genomic island analysis in Streptococcus thermophilus

Bacteria encode diverse antiviral defense systems, yet the evolutionary reservoirs that generate this immune innovation remain poorly defined. Although genomic context has been instrumental in discovering defense systems, genomic islands (GIs), variable chromosomal regions enriched in defense genes and proteins of unknown function, have not been systematically explored as sources of new bacterial immunity. Here, using comparative genomics of Streptococcus thermophilus, we identified 30 defense-associated GIs displaying extensive accessory gene diversity. Investigation of candidate loci from three GIs uncovered 15 previously uncharacterized antiviral systems, including 10 with novel architectures or features, revealing the potential within even a small subset of GIs. Several systems were not located near known defense genes, highlighting that GI-based discovery complements the traditional guilt-by-association approach, revealing systems that would otherwise remain undetected. Together, our findings establish GIs as reservoirs of antiviral innovation and provide a framework for uncovering the diversity of bacterial immune systems.

microbiology↗

bioRxiv2025

Empathi: Embedding-based Phage Protein Annotation Tool by Hierarchical Assignment

Bacteriophages, viruses infecting bacteria, are estimated to outnumber their cellular hosts by 10-fold, acting as key players in all microbial ecosystems. Under evolutionary pressure by their host, they evolve rapidly and encode a large diversity of protein sequences. Consequently, the majority of functions carried by phage proteins remain elusive. Current tools to comprehensively identify phage protein functions from their sequence either lack sensitivity (those relying on homology for instance) or specificity (assigning a single coarse grain function to a protein). Here, we introduce Empathi, a protein-embedding-based classifier that assigns functions in a hierarchical manner - from general functional categories such as "structural" and "DNA-associated" proteins to more specific ones including "nucleases", "tail appendages" and "endolysins" to name only a few. These categories were specifically tailored for phage protein functions and organized such that molecular-level functions are respected in each category, making it well suited for training machine learning classifiers based on protein embeddings. We show on a dataset of cultured phage genomes that Empathi significantly outperforms homology-based methods, tripling the number of annotated homologous groups. On the EnVhog database, the most recent and extensive database of metagenomically-sourced phage proteins, Empathi doubled the annotated fraction of protein families from 16% to 33%. On complete genomes taken from new viromes, almost twice as many proteins are annotated using our method, predictions are consistent when compared to existing tools and Empathi predictions are highly colocalized. In addition, by leveraging Empathis ability to assign multiple labels to the same protein, it is possible to identify multifunctional proteins such as virion-associated lysins. Having a more global view of the repertoire of functions a phage possesses will assuredly help to understand them and their interactions with bacteria better.

bioinformatics↗

bioRxiv2024

Strengthening Phage Resistance of Streptococcus thermophilus by Leveraging Complementary Defense Systems

CRISPR-Cas and restriction-modification systems represent the core defense arsenal in Streptococcus thermophilus to block lytic phages, but their effectiveness is compromised by phages encoding anti-CRISPR proteins (ACRs) and other counter-defense strategies. Here, we explored the resistome of 263 S. thermophilus strains to uncover other anti-phage systems. The defense landscape of S. thermophilus was enriched by 21 accessory defense systems, 13 of which had not been previously investigated in this species. Experimental validation of 17 systems with 14 phages showed varying anti-phage levels, uncovering intra-genus specificities among the five viral genera infecting S. thermophilus. Interestingly, the resistance levels were even higher when some defense systems (Dodola and PD-Lambda-1) were expressed from a low-copy plasmid or when integrated into the chromosome. We also observed a synergistic effect when combining Gabija with CRISPR-Cas, underscoring the potential of these additional defense systems for developing more robust industrial S. thermophilus strains, particularly against ACR-encoding phages.

microbiology↗